WorldWideScience

Sample records for random noise filtering

  1. Signal preserving and seismic random noise attenuation by Hurst exponent based time-frequency peak filtering

    Science.gov (United States)

    Zhang, Chao; Li, Yue; Lin, Hongbo; Yang, Baojun

    2015-11-01

    Attenuating random noise is of great significance in seismic data processing. In recent years, time-frequency peak filtering (TFPF) has been successfully applied to seismic random noise attenuation field. However, a fixed window length (WL) is used in the conventional TFPF. Since a short WL in the TFPF is used to preserve signals while a long WL can eliminate random noise effectively, signal preserving and noise attenuation cannot be balanced by a fixed WL especially when the signal-to-noise ratio of the noisy seismic record is low. Thus, we need to divide a noisy signal into signal and noise segments before the filtering. Then a short WL is used to the signal segments to preserve signals and a long WL is chosen for noise segments to eliminate random noise. In this paper, we test the smoothness of signals and random noise in time using the Hurst exponent which is a statistic for representing smoothness characteristics of signals. The time-series of signals with higher smoothness which lead to larger Hurst exponent values, however random noise is a random series in time without fixed waveforms and thus its smoothness is low, so the signal and noise segments can be divided by the Hurst exponent values. After the segmentation, we can adopt different filtering WLs in the TFPF for different segments to make a trade-off between signal preserving and random noise attenuation. Synthetic and real data experiments demonstrate that the proposed method can remove random noise from seismic record and preserve reflection events effectively.

  2. Frequency-space prediction filtering for acoustic clutter and random noise attenuation in ultrasound imaging

    Science.gov (United States)

    Shin, Junseob; Huang, Lianjie

    2016-04-01

    Frequency-space prediction filtering (FXPF), also known as FX deconvolution, is a technique originally developed for random noise attenuation in seismic imaging. FXPF attempts to reduce random noise in seismic data by modeling only real signals that appear as linear or quasilinear events in the aperture domain. In medical ultrasound imaging, channel radio frequency (RF) signals from the main lobe appear as horizontal events after receive delays are applied while acoustic clutter signals from off-axis scatterers and electronic noise do not. Therefore, FXPF is suitable for preserving only the main-lobe signals and attenuating the unwanted contributions from clutter and random noise in medical ultrasound imaging. We adapt FXPF to ultrasound imaging, and evaluate its performance using simulated data sets from a point target and an anechoic cyst. Our simulation results show that using only 5 iterations of FXPF achieves contrast-to-noise ratio (CNR) improvements of 67 % in a simulated noise-free anechoic cyst and 228 % in a simulated anechoic cyst contaminated with random noise of 15 dB signal-to-noise ratio (SNR). Our findings suggest that ultrasound imaging with FXPF attenuates contributions from both acoustic clutter and random noise and therefore, FXPF has great potential to improve ultrasound image contrast for better visualization of important anatomical structures and detection of diseased conditions.

  3. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter.

    Science.gov (United States)

    Huang, Lei

    2015-09-30

    To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required.

  4. Distributed Fusion Filtering in Networked Systems with Random Measurement Matrices and Correlated Noises

    Directory of Open Access Journals (Sweden)

    Raquel Caballero-Águila

    2015-01-01

    Full Text Available The distributed fusion state estimation problem is addressed for sensor network systems with random state transition matrix and random measurement matrices, which provide a unified framework to consider some network-induced random phenomena. The process noise and all the sensor measurement noises are assumed to be one-step autocorrelated and different sensor noises are one-step cross-correlated; also, the process noise and each sensor measurement noise are two-step cross-correlated. These correlation assumptions cover many practical situations, where the classical independence hypothesis is not realistic. Using an innovation methodology, local least-squares linear filtering estimators are recursively obtained at each sensor. The distributed fusion method is then used to form the optimal matrix-weighted sum of these local filters according to the mean squared error criterion. A numerical simulation example shows the accuracy of the proposed distributed fusion filtering algorithm and illustrates some of the network-induced stochastic uncertainties that can be dealt with in the current system model, such as sensor gain degradation, missing measurements, and multiplicative noise.

  5. Kalman Filtering for Discrete Stochastic Systems with Multiplicative Noises and Random Two-Step Sensor Delays

    Directory of Open Access Journals (Sweden)

    Dongyan Chen

    2015-01-01

    Full Text Available This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE. Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.

  6. Spatial Prediction Filtering of Acoustic Clutter and Random Noise in Medical Ultrasound Imaging.

    Science.gov (United States)

    Shin, Junseob; Huang, Lianjie

    2017-02-01

    One of the major challenges in array-based medical ultrasound imaging is the image quality degradation caused by sidelobes and off-axis clutter, which is an inherent limitation of the conventional delay-and-sum (DAS) beamforming operating on a finite aperture. Ultrasound image quality is further degraded in imaging applications involving strong tissue attenuation and/or low transmit power. In order to effectively suppress acoustic clutter from off-axis targets and random noise in a robust manner, we introduce in this paper a new adaptive filtering technique called frequency-space (F-X) prediction filtering or FXPF, which was first developed in seismic imaging for random noise attenuation. Seismologists developed FXPF based on the fact that linear and quasilinear events or wavefronts in the time-space (T-X) domain are manifested as a superposition of harmonics in the frequency-space (F-X) domain, which can be predicted using an auto-regressive (AR) model. We describe the FXPF technique as a spectral estimation or a direction-of-arrival problem, and explain why adaptation of this technique into medical ultrasound imaging is beneficial. We apply our new technique to simulated and tissue-mimicking phantom data. Our results demonstrate that FXPF achieves CNR improvements of 26% in simulated noise-free anechoic cyst, 109% in simulated anechoic cyst contaminated with random noise of 15 dB SNR, and 93% for experimental anechoic cyst from a custom-made tissue-mimicking phantom. Our findings suggest that FXPF is an effective technique to enhance ultrasound image contrast and has potential to improve the visualization of clinically important anatomical structures and diagnosis of diseased conditions.

  7. Seismic random noise removal by delay-compensation time-frequency peak filtering

    Science.gov (United States)

    Yu, Pengjun; Li, Yue; Lin, Hongbo; Wu, Ning

    2017-06-01

    Over the past decade, there has been an increasing awareness of time-frequency peak filtering (TFPF) due to its outstanding performance in suppressing non-stationary and strong seismic random noise. The traditional approach based on time-windowing achieves local linearity and meets the unbiased estimation. However, the traditional TFPF (including the improved algorithms with alterable window lengths) could hardly relieve the contradiction between removing noise and recovering the seismic signal, and this situation is more obvious in wave crests and troughs, even for alterable window lengths (WL). To improve the efficiency of the algorithm, the following TFPF in the time-space domain is applied, such as in the Radon domain and radial trace domain. The time-space transforms obtain a reduced-frequency input to reduce the TFPF error and stretch the desired signal along a certain direction, therefore the time-space development brings an improvement by both enhancing reflection events and attenuating noise. It still proves limited in application because the direction should be matched as a straight line or quadratic curve. As a result, waveform distortion and false seismic events may appear when processing the complex stratum record. The main emphasis in this article is placed on the time-space TFPF applicable expansion. The reconstructed signal in delay-compensation TFPF, which is generated according to the similarity among the reflection events, overcomes the limitation of the direction curve fitting. Moreover, the reconstructed signal just meets the TFPF linearity unbiased estimation and integrates signal reservation with noise attenuation. Experiments on both the synthetic model and field data indicate that delay-compensation TFPF has a better performance over the conventional filtering algorithms.

  8. Optimal Gaussian Filter for Effective Noise Filtering

    OpenAIRE

    Kopparapu, Sunil; Satish, M

    2014-01-01

    In this paper we show that the knowledge of noise statistics contaminating a signal can be effectively used to choose an optimal Gaussian filter to eliminate noise. Very specifically, we show that the additive white Gaussian noise (AWGN) contaminating a signal can be filtered best by using a Gaussian filter of specific characteristics. The design of the Gaussian filter bears relationship with the noise statistics and also some basic information about the signal. We first derive a relationship...

  9. Statistical properties of a filtered Poisson process with additive random noise: Distributions, correlations and moment estimation

    CERN Document Server

    Theodorsen, Audun; Rypdal, Martin

    2016-01-01

    The filtered Poisson process is often used as a reference model for intermittent fluctuations in physical systems. Here, this process is extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The moments, probability density function, auto- correlation function and power spectral density are derived and used to compare the effects of the different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of parameter estimation and to identify methods for separating the noise types. It is shown that the probability density function and the three lowest moments provide accurate estimations of the parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of determining the noise type. The number of times the signal passes a prescribed threshold in t...

  10. Seismic random noise attenuation by time-frequency peak filtering based on joint time-frequency distribution

    Science.gov (United States)

    Zhang, Chao; Lin, Hong-bo; Li, Yue; Yang, Bao-jun

    2013-09-01

    Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner-Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner-Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.

  11. Frequently asked questions on filtered noise

    DEFF Research Database (Denmark)

    Blanke, Mogens

    This note was made in response to several returning questions on noise and ways to calculate covariance of filtered random signals, where filters could origin from residual generators. Reference is made to stochastic signals treated in appendix 2 of the book Diagnosis and Fault-tolerant Control...

  12. A Robust Recursive Filter for Nonlinear Systems with Correlated Noises, Packet Losses, and Multiplicative Noises

    Directory of Open Access Journals (Sweden)

    Hua-Ming Qian

    2014-01-01

    Full Text Available A robust filtering problem is formulated and investigated for a class of nonlinear systems with correlated noises, packet losses, and multiplicative noises. The packet losses are assumed to be independent Bernoulli random variables. The multiplicative noises are described as random variables with bounded variance. Different from the traditional robust filter based on the assumption that the process noises are uncorrelated with the measurement noises, the objective of the addressed robust filtering problem is to design a recursive filter such that, for packet losses and multiplicative noises, the state prediction and filtering covariance matrices have the optimized upper bounds in the case that there are correlated process and measurement noises. Two examples are used to illustrate the effectiveness of the proposed filter.

  13. Shielded multi-stage EMI noise filter

    Science.gov (United States)

    Kisner, Roger Allen; Fugate, David Lee

    2016-11-08

    Electromagnetic interference (EMI) noise filter embodiments and methods for filtering are provided herein. EMI noise filters include multiple signal exclusion enclosures. The multiple signal exclusion enclosures contain filter circuit stages. The signal exclusion enclosures can attenuate noise generated external to the enclosures and/or isolate noise currents generated by the corresponding filter circuits within the enclosures. In certain embodiments, an output of one filter circuit stage is connected to an input of the next filter circuit stage. The multiple signal exclusion enclosures can be chambers formed using conductive partitions to divide an outer signal exclusion enclosure. EMI noise filters can also include mechanisms to maintain the components of the filter circuit stages at a consistent temperature. For example, a metal base plate can distribute heat among filter components, and an insulating material can be positioned inside signal exclusion enclosures.

  14. Filter apparatus for actively reducing noise

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; Nijsse, G.

    2010-01-01

    A filter apparatus for reducing noise from a primary noise source, comprising a secondary source signal connector for generating secondary noise to reduce said primary noise and a sensor connector for connecting to a sensor for measuring said primary and secondary noise as an error signal. A first

  15. A filter apparatus for actively reducing noise

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; Nijsse, G.

    2006-01-01

    A filter apparatus for reducing noise from a primary noise source, comprising a secondary source signal connector for generating secondary noise to reduce said primary noise and a sensor connector for connecting to a sensor for measuring said primary and secondary noise as an error signal. A first

  16. LMS filter for noise cancellation using Simulink

    Science.gov (United States)

    Talele, K. T.; Shrivastav, Ashish; Utekar, Kunal; Deshpande, Abhishek

    2011-06-01

    In this paper we have proposed the simplified implementation of adaptive noise cancellation using LMS filter. The LMS algorithm belongs to the family of stochastic gradient algorithms. It is one of the efficient algorithms in adaptive filtering.

  17. Noise in time-discrete analog filters

    Science.gov (United States)

    Kroemer, B.; Mueller, R.; Stegherr, M.; Klar, H.; Ulbrich, W.

    The most important noise sources in time-discrete analog filters which can be monolithically integrated as CCD and switched-capacitor structures are described. In CCD filters, these sources are thermal kTC noise of the input and output levels and unloading processes at the surface attraction sites. Attainable signal-to-noise ratios and optimization possibilities are stated. For SC filters, the most important noise sources are kTC noise and l/f noise. On-chip clock jitter noise can be suppressed by differential processing. The present measurements on integrated MOS switching transistors with small areas confirm the thermal kTC noise limit and show that there is no additional l/f contribution to the noise from the switches. For the integrator, good agreement is obtained between theory and experiment when an operational amplifier with finite unity-gain frequency is included.

  18. Adaptive noise Wiener filter for scanning electron microscope imaging system.

    Science.gov (United States)

    Sim, K S; Teh, V; Nia, M E

    2016-01-01

    Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. © Wiley Periodicals, Inc.

  19. Randomized Filtering Algorithms

    DEFF Research Database (Denmark)

    Katriel, Irit; Van Hentenryck, Pascal

    2008-01-01

    of AllDifferent and is generalization, the Global Cardinality Constraint. The first delayed filtering scheme is a Monte Carlo algorithm: its running time is superior, in the worst case, to that of enforcing are consistency after every domain event, while its filtering effectiveness is analyzed...

  20. Molecular circuits for dynamic noise filtering.

    Science.gov (United States)

    Zechner, Christoph; Seelig, Georg; Rullan, Marc; Khammash, Mustafa

    2016-04-26

    The invention of the Kalman filter is a crowning achievement of filtering theory-one that has revolutionized technology in countless ways. By dealing effectively with noise, the Kalman filter has enabled various applications in positioning, navigation, control, and telecommunications. In the emerging field of synthetic biology, noise and context dependency are among the key challenges facing the successful implementation of reliable, complex, and scalable synthetic circuits. Although substantial further advancement in the field may very well rely on effectively addressing these issues, a principled protocol to deal with noise-as provided by the Kalman filter-remains completely missing. Here we develop an optimal filtering theory that is suitable for noisy biochemical networks. We show how the resulting filters can be implemented at the molecular level and provide various simulations related to estimation, system identification, and noise cancellation problems. We demonstrate our approach in vitro using DNA strand displacement cascades as well as in vivo using flow cytometry measurements of a light-inducible circuit in Escherichia coli.

  1. Complex noise suppression using a sparse representation and 3D filtering of images

    Science.gov (United States)

    Kravchenko, V. F.; Ponomaryov, V. I.; Pustovoit, V. I.; Palacios-Enriquez, A.

    2017-08-01

    A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.

  2. Noise variance estimation for Kalman filter

    Science.gov (United States)

    Beniak, Ryszard; Gudzenko, Oleksandr; Pyka, Tomasz

    2017-10-01

    In this paper, we propose an algorithm that evaluates noise variance with a numerical integration method. For noise variance estimation, we use Krogh method with a variable integration step. In line with common practice, we limit our study to fourth-order method. First, we perform simulation tests for randomly generated signals, related to the transition state and steady state. Next, we formulate three methodologies (research hypotheses) of noise variance estimation, and then compare their efficiency.

  3. Implementasi Metode Kombinasi Mean Filter Dan Median Filter Untuk Mereduksi Gaussian Noise, Salt And Pepper Noise, Speckle Noise, Dan Exponential Noise Pada Citra Digital

    OpenAIRE

    Fadillah, Azhar

    2014-01-01

    Nowadays, the use of image as form of information is currently increasing. Poor quality of image can reduce its information contained in image. For example, the image contains noise so the information that contained in the image are not clear. Noise on the digital image can be either Gaussian noise, Salt and Pepper Noise, Speckle Noise, and Exponential Noise. One of the mechanisms used to reduce the noise is filtering. Mean Filter method and Median Filter method are a very good method to redu...

  4. An adaptive dynamically weighted median filter for impulse noise removal

    Science.gov (United States)

    Khan, Sajid; Lee, Dong-Ho

    2017-12-01

    A new impulsive noise removal filter, adaptive dynamically weighted median filter (ADWMF), is proposed. A popular method for removing impulsive noise is a median filter whereas the weighted median filter and center weighted median filter were also investigated. ADWMF is based on weighted median filter. In ADWMF, instead of fixed weights, weightages of the filter are dynamically assigned with the results of noise detection. A simple and efficient noise detection method is also used to detect noise candidates and dynamically assign zero or small weights to the noise candidates in the window. This paper proposes an adaptive method which increases the window size according to the amounts of impulsive noise. Simulation results show that the AMWMF works better for both images with low and high density of impulsive noise than existing methods work.

  5. Simulation for noise cancellation using LMS adaptive filter

    Science.gov (United States)

    Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

    2017-06-01

    In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

  6. Optimal Correlation Filters for Images with Signal-Dependent Noise

    Science.gov (United States)

    Downie, John D.; Walkup, John F.

    1994-01-01

    We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

  7. Noise resonance : Technological sound reproduction and the logic of filtering

    NARCIS (Netherlands)

    Kromhout, M.J.

    2017-01-01

    What is it about noise that attracted musicians and listeners over the past century? Noise Resonance: Technological Sound Reproduction and the Logic of Filtering sets out to answer this question through an extensive conceptual revaluation of the role of noise and distortion in sound and music. The

  8. Noise robustness of nonlinear filters for image recognition.

    Science.gov (United States)

    Towghi, N; Pan, L; Javidi, B

    2001-09-01

    We analyze the performance of the Fourier plane nonlinear filters in terms of signal-to-noise ratio (SNR). We obtain a range of nonlinearities for which SNR is robust to the variations in input-noise bandwidth. This is shown both by analytical estimates of the SNR for nonlinear filters and by experimental simulations. Specifically, we analyze the SNR when Fourier plane nonlinearity is applied to the input signal. Using the Karhunen-Loève series expansion of the noise process, we obtain precise analytic expressions of the SNR for Fourier plane nonlinear filters in the presence of various types of additive-noise processes. We find a range of nonlinearities that need to be applied that keep the output SNR of the filter stable relative to changes in the noise bandwidth.

  9. Noise Filtering and Prediction in Biological Signaling Networks

    CERN Document Server

    Hathcock, David; Weisenberger, Casey; Ilker, Efe; Hinczewski, Michael

    2016-01-01

    Information transmission in biological signaling circuits has often been described using the metaphor of a noise filter. Cellular systems need accurate, real-time data about their environmental conditions, but the biochemical reaction networks that propagate, amplify, and process signals work with noisy representations of that data. Biology must implement strategies that not only filter the noise, but also predict the current state of the environment based on information delayed due to the finite speed of chemical signaling. The idea of a biochemical noise filter is actually more than just a metaphor: we describe recent work that has made an explicit mathematical connection between signaling fidelity in cellular circuits and the classic theories of optimal noise filtering and prediction that began with Wiener, Kolmogorov, Shannon, and Bode. This theoretical framework provides a versatile tool, allowing us to derive analytical bounds on the maximum mutual information between the environmental signal and the re...

  10. Inversion-based data-driven time-space domain random noise attenuation method

    Science.gov (United States)

    Zhao, Yu-Min; Li, Guo-Fa; Wang, Wei; Zhou, Zhen-Xiao; Tang, Bo-Wen; Zhang, Wen-Bo

    2017-12-01

    Conventional time-space domain and frequency-space domain prediction filtering methods assume that seismic data consists of two parts, signal and random noise. That is, the so-called additive noise model. However, when estimating random noise, it is assumed that random noise can be predicted from the seismic data by convolving with a prediction error filter. That is, the source-noise model. Model inconsistencies, before and after denoising, compromise the noise attenuation and signal-preservation performances of prediction filtering methods. Therefore, this study presents an inversion-based time-space domain random noise attenuation method to overcome the model inconsistencies. In this method, a prediction error filter (PEF), is first estimated from seismic data; the filter characterizes the predictability of the seismic data and adaptively describes the seismic data's space structure. After calculating PEF, it can be applied as a regularized constraint in the inversion process for seismic signal from noisy data. Unlike conventional random noise attenuation methods, the proposed method solves a seismic data inversion problem using regularization constraint; this overcomes the model inconsistency of the prediction filtering method. The proposed method was tested on both synthetic and real seismic data, and results from the prediction filtering method and the proposed method are compared. The testing demonstrated that the proposed method suppresses noise effectively and provides better signal-preservation performance.

  11. High internal noise and poor external noise filtering characterize perception in autism spectrum disorder.

    Science.gov (United States)

    Park, Woon Ju; Schauder, Kimberly B; Zhang, Ruyuan; Bennetto, Loisa; Tadin, Duje

    2017-12-14

    An emerging hypothesis postulates that internal noise is a key factor influencing perceptual abilities in autism spectrum disorder (ASD). Given fundamental and inescapable effects of noise on nearly all aspects of neural processing, this could be a critical abnormality with broad implications for perception, behavior, and cognition. However, this proposal has been challenged by both theoretical and empirical studies. A crucial question is whether and how internal noise limits perception in ASD, independently from other sources of perceptual inefficiency, such as the ability to filter out external noise. Here, we separately estimated internal noise and external noise filtering in ASD. In children and adolescents with and without ASD, we computationally modeled individuals' visual orientation discrimination in the presence of varying levels of external noise. The results revealed increased internal noise and worse external noise filtering in individuals with ASD. For both factors, we also observed high inter-individual variability in ASD, with only the internal noise estimates significantly correlating with severity of ASD symptoms. We provide evidence for reduced perceptual efficiency in ASD that is due to both increased internal noise and worse external noise filtering, while highlighting internal noise as a possible contributing factor to variability in ASD symptoms.

  12. Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals

    Science.gov (United States)

    Liu, Cai; Song, Chao; Lu, Qi

    2017-09-01

    In this paper, we present a method using singular value decomposition (SVD) which aims at eliminating the random noise and direct wave from ground penetrating radar (GPR) signals. To demonstrate the validity and high efficiency of the SVD method in eliminating random noise, we compare the SVD de-noising method with wavelet threshold de-noising method and bandpass filtering method on both noisy synthetic data and field data. After that, we compare the SVD method with the mean trace deleting in eliminating direct wave on synthetic data and field data. We set general and quantitative criteria on choosing singular values to carry out the random noise de-noising and direct wave eliminating process. We find that by choosing appropriate singular values, SVD method can eliminate the random noise and direct wave in the GPR data validly and efficiently to improve the signal-to-noise ratio (SNR) of the GPR profiles and make effective reflection signals clearer.

  13. White noise theory of robust nonlinear filtering with correlated state and observation noises

    NARCIS (Netherlands)

    Bagchi, Arunabha; Karandikar, Rajeeva

    1994-01-01

    In the existing `direct¿ white noise theory of nonlinear filtering, the state process is still modelled as a Markov process satisfying an Itô stochastic differential equation, while a `finitely additive¿ white noise is used to model the observation noise. We remove this asymmetry by modelling the

  14. White noise theory of robust nonlinear filtering with correlated state and observation noises

    NARCIS (Netherlands)

    Bagchi, Arunabha; Karandikar, Rajeeva

    1992-01-01

    In the direct white noise theory of nonlinear filtering, the state process is still modeled as a Markov process satisfying an Ito stochastic differential equation, while a finitely additive white noise is used to model the observation noise. In the present work, this asymmetry is removed by modeling

  15. Random signals and noise a mathematical introduction

    CERN Document Server

    Engelberg, Shlomo

    2011-01-01

    Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory.A Firm FoundationBefore launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and incl

  16. Applications of adaptive filters in active noise control

    Science.gov (United States)

    Darlington, Paul

    The active reduction of acoustic noise is achieved by the addition of a cancelling acoustic signal to the unwanted sound. Successful definition of the cancelling signal amounts to a system identification problem. Recent advances in adaptive signal processing have allowed this problem to be tackled using adaptive filters, which offer significant advantages over conventional solutions. The extension of adaptive noise cancelling techniques, which were developed in the electrical signal conditioning context, to the control of acoustic systems is studied. An analysis is presented of the behavior of the Widrow-Hoff LMS adaptive noise canceller with a linear filter in its control loop. The active control of plane waves propagating axially in a hardwalled duct is used as a motivating model problem. The model problem also motivates the study of the effects of feedback around an LMS adaptive filter. An alternative stochastic gradient algorithm for controlling adaptive filters in the presence of feedback is presented.

  17. Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm

    Directory of Open Access Journals (Sweden)

    Hyun-Tae Cho

    2016-01-01

    Full Text Available Due to the growing number of vehicles using the national road networks that link major urban centers, traffic noise is becoming a major issue in relation to the transportation system. Thus, it is important to determine noise model parameters to predict road traffic noise levels as part of an environmental assessment, according to traffic volume and pavement surface type. To determine the parameters of a noise prediction model, statistical pass-by and close proximity tests are required. This paper provides a parameter determination procedure for noise prediction models through an adaptive particle filter (PF algorithm, based on using a weigh-in-motion system, which obtains vehicle velocities and types, as well as step-up microphones, which measure the combined noises emitted by various vehicle types. Finally, an evaluation of the adaptive noise parameter determination algorithm was carried out to assess the agreement between predictions and measurements.

  18. Particle filters for random set models

    CERN Document Server

    Ristic, Branko

    2013-01-01

    “Particle Filters for Random Set Models” presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. The resulting  algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from  navigation and autonomous vehicles to bio-informatics and finance. While particle filters have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models. This book...

  19. Performance Analysis of LMS Adaptive FIR Filter and RLS Adaptive FIR Filter for Noise Cancellation

    OpenAIRE

    Jyotsna Yadav; Mukesh Kumar; Rohini Saxena; Jaiswal, A K

    2013-01-01

    Interest in adaptive filters continues to grow as they begin to find practical real-time applications in areas such as channel equalization, echo cancellation, noise cancellation and many other adaptive signal processing applications. The key to successful adaptive signal processing understands the fundamental properties of adaptive algorithms such as LMS, RLS etc. Adaptive filter is used for the cancellation of the noise component which is overlap with undesired si...

  20. Dental drill noise reduction using a combination of active noise control, passive noise control and adaptive filtering

    OpenAIRE

    Kaymak, E; Atherton, MA; Rotter, K; Millar, B

    2007-01-01

    Dental drills produce a characteristic high frequency, narrow band noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise control methods, namely, Passive Noise Control (PNC), Adaptive Filtering (AF) and Active Noise Control (ANC). This paper discusses the application of the three ...

  1. Kalman-Takens filtering in the presence of dynamical noise

    Science.gov (United States)

    Hamilton, Franz; Berry, Tyrus; Sauer, Timothy

    2017-12-01

    The use of data assimilation for the merging of observed data with dynamical models is becoming standard in modern physics. If a parametric model is known, methods such as Kalman filtering have been developed for this purpose. If no model is known, a hybrid Kalman-Takens method has been recently introduced, in order to exploit the advantages of optimal filtering in a nonparametric setting. This procedure replaces the parametric model with dynamics reconstructed from delay coordinates, while using the Kalman update formulation to assimilate new observations. In this article, we study the efficacy of this method for identifying underlying dynamics in the presence of dynamical noise. Furthermore, by combining the Kalman-Takens method with an adaptive filtering procedure we are able to estimate the statistics of the observational and dynamical noise. This solves a long-standing problem of separating dynamical and observational noise in time series data, which is especially challenging when no dynamical model is specified.

  2. Removing Noises Induced by Gamma Radiation in Cerenkov Luminescence Imaging Using a Temporal Median Filter

    Directory of Open Access Journals (Sweden)

    Xu Cao

    2016-01-01

    Full Text Available Cerenkov luminescence imaging (CLI can provide information of medical radionuclides used in nuclear imaging based on Cerenkov radiation, which makes it possible for optical means to image clinical radionuclide labeled probes. However, the exceptionally weak Cerenkov luminescence (CL from Cerenkov radiation is susceptible to lots of impulse noises introduced by high energy gamma rays generating from the decays of radionuclides. In this work, a temporal median filter is proposed to remove this kind of impulse noises. Unlike traditional CLI collecting a single CL image with long exposure time and smoothing it using median filter, the proposed method captures a temporal sequence of CL images with shorter exposure time and employs a temporal median filter to smooth a temporal sequence of pixels. Results of in vivo experiments demonstrated that the proposed temporal median method can effectively remove random pulse noises induced by gamma radiation and achieve a robust CLI image.

  3. Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction

    Directory of Open Access Journals (Sweden)

    Piotr PIETRZAK

    2008-12-01

    Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.

  4. Reduced Rank Adaptive Filtering in Impulsive Noise Environments

    KAUST Repository

    Soury, Hamza

    2014-01-06

    An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

  5. Introduction to Random Signals and Noise

    NARCIS (Netherlands)

    van Etten, Wim

    Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding,

  6. Single-channel noise reduction using optimal rectangular filtering matrices.

    Science.gov (United States)

    Long, Tao; Chen, Jingdong; Benesty, Jacob; Zhang, Zhenxi

    2013-02-01

    This paper studies the problem of single-channel noise reduction in the time domain and presents a block-based approach where a vector of the desired speech signal is recovered by filtering a frame of the noisy signal with a rectangular filtering matrix. With this formulation, the noise reduction problem becomes one of estimating an optimal filtering matrix. To achieve such estimation, a method is introduced to decompose a frame of the clean speech signal into two orthogonal components: One correlated and the other uncorrelated with the current desired speech vector to be estimated. Different optimization cost functions are then formulated from which non-causal optimal filtering matrices are derived. The relationships among these optimal filtering matrices are discussed. In comparison with the classical sample-based technique that uses only forward prediction, the block-based method presented in this paper exploits both the forward and backward prediction as well as the temporal interpolation and, therefore, can improve the noise reduction performance by fully taking advantage of the speech property of self correlation. There is also a side advantage of this block-based method as compared to the sample-based technique, i.e., it is computationally more efficient and, as a result, more suitable for practical implementation.

  7. Weighted Measurement Fusion White Noise Deconvolution Filter with Correlated Noise for Multisensor Stochastic Systems

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2012-01-01

    Full Text Available For the multisensor linear discrete time-invariant stochastic control systems with different measurement matrices and correlated noises, the centralized measurement fusion white noise estimators are presented by the linear minimum variance criterion under the condition that noise input matrix is full column rank. They have the expensive computing burden due to the high-dimension extended measurement matrix. To reduce the computing burden, the weighted measurement fusion white noise estimators are presented. It is proved that weighted measurement fusion white noise estimators have the same accuracy as the centralized measurement fusion white noise estimators, so it has global optimality. It can be applied to signal processing in oil seismic exploration. A simulation example for Bernoulli-Gaussian white noise deconvolution filter verifies the effectiveness.

  8. Operating regimes of signaling cycles: statics, dynamics, and noise filtering.

    Directory of Open Access Journals (Sweden)

    Carlos Gomez-Uribe

    2007-12-01

    Full Text Available A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades. Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive input-output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input-output characteristics. These results are obtained using the total quasi-steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act--in all four regimes--as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

  9. Operating regimes of signaling cycles: statics, dynamics, and noise filtering.

    Science.gov (United States)

    Gomez-Uribe, Carlos; Verghese, George C; Mirny, Leonid A

    2007-12-01

    A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades). Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive) input-output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input-output characteristics. These results are obtained using the total quasi-steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act--in all four regimes--as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

  10. Improving ambient noise correlation functions with an SVD-based Wiener filter

    Science.gov (United States)

    Moreau, L.; Stehly, L.; Boué, P.; Lu, Y.; Larose, E.; Campillo, M.

    2017-10-01

    This paper introduces a technique for improving seismic noise correlation functions (NCF) via a singular value decomposition (SVD) of a list of NCF and the Wiener filter. SVD is commonly used for denoising signals by keeping singular values associated with signal while rejecting others. However, singular vectors associated with signal may contain non-coherent information, so the reconstructed matrix generally still contains random perturbations. The Wiener filter is a different approach where signals statistics are used to remove incoherent signal parts. We suggest to combine both these approaches by applying the Wiener filter to the singular vectors, in order to maximize coherency directly in the signal subspace prior to reconstructing the NCF matrix. This denoising method significantly enhances signal-to-noise ratio in NCF. Benefits are demonstrated to be both in the convergence towards the Green's function for tomography purposes, and in the time-resolution improvement for monitoring applications.

  11. Volterra Filtering Techniques for Removal of Gaussian and Mixed Gaussian-Impulse Noise

    OpenAIRE

    M. B. Meenavathi; K. Rajesh

    2007-01-01

    In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider ...

  12. Noise pollution filters bird communities based on vocal frequency.

    Directory of Open Access Journals (Sweden)

    Clinton D Francis

    Full Text Available BACKGROUND: Human-generated noise pollution now permeates natural habitats worldwide, presenting evolutionarily novel acoustic conditions unprecedented to most landscapes. These acoustics not only harm humans, but threaten wildlife, and especially birds, via changes to species densities, foraging behavior, reproductive success, and predator-prey interactions. Explanations for negative effects of noise on birds include disruption of acoustic communication through energetic masking, potentially forcing species that rely upon acoustic communication to abandon otherwise suitable areas. However, this hypothesis has not been adequately tested because confounding stimuli often co-vary with noise and are difficult to separate from noise exposure. METHODOLOGY/PRINCIPAL FINDINGS: Using a natural experiment that controls for confounding stimuli, we evaluate whether species vocal features or urban-tolerance classifications explain their responses to noise measured through habitat use. Two data sets representing nesting and abundance responses reveal that noise filters bird communities nonrandomly. Signal duration and urban tolerance failed to explain species-specific responses, but birds with low-frequency signals that are more susceptible to masking from noise avoided noisy areas and birds with higher frequency vocalizations remained. Signal frequency was also negatively correlated with body mass, suggesting that larger birds may be more sensitive to noise due to the link between body size and vocal frequency. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that acoustic masking by noise may be a strong selective force shaping the ecology of birds worldwide. Larger birds with lower frequency signals may be excluded from noisy areas, whereas smaller species persist via transmission of higher frequency signals. We discuss our findings as they relate to interspecific relationships among body size, vocal amplitude and frequency and suggest that they are

  13. Reduced rank adaptive filtering in impulsive noise environments

    KAUST Repository

    Soury, Hamza

    2014-11-01

    An impulsive noise environment is considered in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction, while the minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each method is discussed. © 2014 IEEE.

  14. Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

    Science.gov (United States)

    K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

    2016-07-01

    We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

  15. Using Kalman Filters to Reduce Noise from RFID Location System

    Directory of Open Access Journals (Sweden)

    Pedro Henriques Abreu

    2014-01-01

    Full Text Available Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes—linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11–13% of improvement.

  16. Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters

    Directory of Open Access Journals (Sweden)

    Sicuranza Giovanni L

    2004-01-01

    Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.

  17. An area efficient low noise 100 Hz low-pass filter

    DEFF Research Database (Denmark)

    Ølgaard, Christian; Sassene, Haoues; Perch-Nielsen, Ivan R.

    1996-01-01

    A technique based on scaling a filter's capacitor currents to improve the noise performance of low frequency continuous-time filters is presented. Two 100 Hz low-pass filters have been implemented: a traditional low pass filter (as reference), and a filter utilizing the above mentioned current...... scaling technique. The two filters utilize approximately the same silicon area. The scaled filter implements the scaling by use of a MOS based current conveyor type CCII. Measurements indicate that the current scaled filter results in a noise improvement of approximately 5.5 dB over the reference filter...... when a class A/B biasing scheme is used in the current divider. Obtaining identical noise performance from the reference filter would require a 3.6 times larger filter capacitor. This would increase the reference filter's die area by 100%. Therefore, the current scaling technique allows filters...

  18. Non-Causal Time-Domain Filters for Single-Channel Noise Reduction

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

    2012-01-01

    shown that the output SNRs of the filters always increase as we increase the length of the filter when the desired signal is stationary. From both the theoretical and practical evaluations of the filters, it is clearly shown that the performance of time-domain filtering methods for noise reduction can......In many existing time-domain filtering methods for noise reduction in, e.g., speech processing, the filters are causal. Such causal filters can be implemented directly in practice. However, it is possible to improve the performance of such noise reduction filtering methods in terms of both noise...... suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose...

  19. Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

    Science.gov (United States)

    Zhu, Yuhong; Li, Hongyang; Jiang, Huageng

    2017-12-01

    This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

  20. Filter Out High Frequency Noise in EEG Data Using The Method of Maximum Entropy

    OpenAIRE

    Tseng, Chih-Yuan; Lee, HC

    2007-01-01

    We propose a maximum entropy (ME) based approach to smooth noise not only in data but also to noise amplified by second order derivative calculation of the data especially for electroencephalography (EEG) studies. The approach includes two steps, applying method of ME to generate a family of filters and minimizing noise variance after applying these filters on data selects the preferred one within the family. We examine performance of the ME filter through frequency and noise variance analysi...

  1. Implicit particle filtering for models with partial noise, and an application to geomagnetic data assimilation

    Directory of Open Access Journals (Sweden)

    M. Morzfeld

    2012-06-01

    Full Text Available Implicit particle filtering is a sequential Monte Carlo method for data assimilation, designed to keep the number of particles manageable by focussing attention on regions of large probability. These regions are found by minimizing, for each particle, a scalar function F of the state variables. Some previous implementations of the implicit filter rely on finding the Hessians of these functions. The calculation of the Hessians can be cumbersome if the state dimension is large or if the underlying physics are such that derivatives of F are difficult to calculate, as happens in many geophysical applications, in particular in models with partial noise, i.e. with a singular state covariance matrix. Examples of models with partial noise include models where uncertain dynamic equations are supplemented by conservation laws with zero uncertainty, or with higher order (in time stochastic partial differential equations (PDE or with PDEs driven by spatially smooth noise processes. We make the implicit particle filter applicable to such situations by combining gradient descent minimization with random maps and show that the filter is efficient, accurate and reliable because it operates in a subspace of the state space. As an example, we consider a system of nonlinear stochastic PDEs that is of importance in geomagnetic data assimilation.

  2. Variational Bayesian labeled multi-Bernoulli filter with unknown sensor noise statistics

    Directory of Open Access Journals (Sweden)

    Qiu Hao

    2016-10-01

    Full Text Available It is difficult to build accurate model for measurement noise covariance in complex backgrounds. For the scenarios of unknown sensor noise variances, an adaptive multi-target tracking algorithm based on labeled random finite set and variational Bayesian (VB approximation is proposed. The variational approximation technique is introduced to the labeled multi-Bernoulli (LMB filter to jointly estimate the states of targets and sensor noise variances. Simulation results show that the proposed method can give unbiased estimation of cardinality and has better performance than the VB probability hypothesis density (VB-PHD filter and the VB cardinality balanced multi-target multi-Bernoulli (VB-CBMeMBer filter in harsh situations. The simulations also confirm the robustness of the proposed method against the time-varying noise variances. The computational complexity of proposed method is higher than the VB-PHD and VB-CBMeMBer in extreme cases, while the mean execution times of the three methods are close when targets are well separated.

  3. Multichannel active control of random noise in a small reverberant room

    DEFF Research Database (Denmark)

    Laugesen, Søren; Elliott, Stephen J.

    1993-01-01

    An algorithm for multichannel adaptive IIR (infinite impulse response) filtering is presented and applied to the active control of broadband random noise in a small reverberant room. Assuming complete knowledge of the primary noise, the theoretically optimal reductions of acoustic energy...... with the primary noise field generated by a panel excited by a loudspeaker in an adjoining room. These results show that far better performances are provided by IIR and FIR filters when the primary source has a lightly damped dynamic behavior which the active controller must model...... multichannel FIR (finite impulse response) and IIR filters are then compared for a four-secondary-source, eight-error microphone active control system, and it is found that for the present application FIR filters are sufficient when the primary noise source is a loudspeaker. Some experiments are then presented...

  4. A modified LLCL-filter with the reduced conducted EMI noise

    DEFF Research Database (Denmark)

    Wu, Weimin; Sun, Yunjie; Lin, Zhe

    2014-01-01

    mode EMI noises are investigated for the LCL- and LLCL-filter-based single-phase full-bridge grid-tied inverters. Based on this, a modified LLCL-filter topology is proposed to provide enough attenuation on the conducted EMI noise as well as to reduce the dc-side leakage current. The parameter design...... method of the filter is also developed. The comparative analysis and discussion on four filter cases (the conventional LCL filter, the conventional LLCL filter, the modified LCL filter, and the modified LLCL filter) are carried out and verified through simulations and experiments on a 0.5-kW, 110 V/50 Hz...

  5. The application of random phase filter in the image recognition

    Science.gov (United States)

    Yang, Xiujuan; Zhong, Mei; Shao, Zhufeng

    2016-03-01

    We define one kind of new correlation, i.e. random phase correlation, which based on the Random Fourier Transform (RFT). An optical pattern recognition system, random phase filtering, is given according to random phase correlation. Furthermore its electro-optical setup is given for the application in image recognition. By the numerical simulation on computer, when the, we have found the proposed random phase filter can recognize the small change of object image and has higher recognition capability comparing of other three conventional correlators, the classical marched filter, the phase-only filter and the pure phase correlator.

  6. High Degree Cubature Federated Filter for Multisensor Information Fusion with Correlated Noises

    Directory of Open Access Journals (Sweden)

    Lijun Wang

    2016-01-01

    Full Text Available This paper proposes an improved high degree cubature federated filter for the nonlinear fusion system with cross-correlation between process and measurement noises at the same time using the fifth-degree cubature rule and the decorrelated principle in its local filters. The master filter of the federated filter adopts the no-reset mode to fuse local estimates of local filters to generate a global estimate according to the scalar weighted rule. The air-traffic maneuvering target tracking simulations are performed between the proposed filter and the fifth-degree cubature federated filter. Simulations results demonstrate that the proposed filter not only can achieve almost the same accuracy as the fifth-degree cubature federated filter with independent white noises, but also has superior performance to the fifth-degree cubature federated filter while the noises are cross-correlated at the same time.

  7. IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform

    Science.gov (United States)

    Rahmatillah, Akif; Ataulkarim

    2017-05-01

    Powerline noise has been one of significant noises of Electrocardiogram (ECG) signal measurement. This noise is characterized by a sinusoidal signal which has 50 Hz of noise and 0.3 mV of maximum amplitude. This paper describes the design of IIR Notch filter design to reject a 50 Hz power line noise. IIR filter coefficients were calculated using pole placement method with three variations of band stop cut off frequencies of (49-51)Hz, (48 - 52)Hz, and (47 - 53)Hz. The algorithm and coefficients of filter were embedded to Arduino DUE (ARM 32 bit microcontroller). IIR notch filter designed has been able to reject power line noise with average square of error value of 0.225 on (49-51) Hz filter design and 0.2831 on (48 - 52)Hz filter design.

  8. Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

    Directory of Open Access Journals (Sweden)

    Volodymyr I. Ponomaryov

    2014-01-01

    Full Text Available A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.. In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM as well as subjective perception via the human vision system in the different color videos.

  9. An Innovations-Based Noise Cancelling Technique on Inverse Kepstrum Whitening Filter and Adaptive FIR Filter in Beamforming Structure

    Science.gov (United States)

    Jeong, Jinsoo

    2011-01-01

    This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure. PMID:22163987

  10. LMS-based active noise cancellation methods for fMRI using sub-band filtering.

    Science.gov (United States)

    Milani, Ali A; Panahi, Issa; Briggs, Richard

    2006-01-01

    We present application of adaptive LMS-based method using two different sub-band filtering techniques for active reduction of 3T-fMRI acoustic noise. Analysis and design of the sub-band filters are discussed based on the characteristics of the noise. Using the fMRI-brain scanner acoustic noise, performance of the methods are analyzed and compared for different number of sub-band filters.

  11. On low-frequency errors of uniformly modulated filtered white-noise models for ground motions

    Science.gov (United States)

    Safak, Erdal; Boore, David M.

    1988-01-01

    Low-frequency errors of a commonly used non-stationary stochastic model (uniformly modulated filtered white-noise model) for earthquake ground motions are investigated. It is shown both analytically and by numerical simulation that uniformly modulated filter white-noise-type models systematically overestimate the spectral response for periods longer than the effective duration of the earthquake, because of the built-in low-frequency errors in the model. The errors, which are significant for low-magnitude short-duration earthquakes, can be eliminated by using the filtered shot-noise-type models (i. e. white noise, modulated by the envelope first, and then filtered).

  12. Noise and speckle reduction in synthetic aperture radar imagery by nonparametric Wiener filtering.

    Science.gov (United States)

    Caprari, R S; Goh, A S; Moffatt, E K

    2000-12-10

    We present a Wiener filter that is especially suitable for speckle and noise reduction in multilook synthetic aperture radar (SAR) imagery. The proposed filter is nonparametric, not being based on parametrized analytical models of signal statistics. Instead, the Wiener-Hopf equation is expressed entirely in terms of observed signal statistics, with no reference to the possibly unobservable pure signal and noise. This Wiener filter is simple in concept and implementation, exactly minimum mean-square error, and directly applicable to signal-dependent and multiplicative noise. We demonstrate the filtering of a genuine two-look SAR image and show how a nonnegatively constrained version of the filter substantially reduces ringing.

  13. Two-microphone spatial filtering improves speech reception for cochlear-implant users in reverberant conditions with multiple noise sources.

    Science.gov (United States)

    Goldsworthy, Raymond L

    2014-10-20

    This study evaluates a spatial-filtering algorithm as a method to improve speech reception for cochlear-implant (CI) users in reverberant environments with multiple noise sources. The algorithm was designed to filter sounds using phase differences between two microphones situated 1 cm apart in a behind-the-ear hearing-aid capsule. Speech reception thresholds (SRTs) were measured using a Coordinate Response Measure for six CI users in 27 listening conditions including each combination of reverberation level (T60=0, 270, and 540 ms), number of noise sources (1, 4, and 11), and signal-processing algorithm (omnidirectional response, dipole-directional response, and spatial-filtering algorithm). Noise sources were time-reversed speech segments randomly drawn from the Institute of Electrical and Electronics Engineers sentence recordings. Target speech and noise sources were processed using a room simulation method allowing precise control over reverberation times and sound-source locations. The spatial-filtering algorithm was found to provide improvements in SRTs on the order of 6.5 to 11.0 dB across listening conditions compared with the omnidirectional response. This result indicates that such phase-based spatial filtering can improve speech reception for CI users even in highly reverberant conditions with multiple noise sources. © The Author(s) 2014.

  14. Two-Microphone Spatial Filtering Improves Speech Reception for Cochlear-Implant Users in Reverberant Conditions With Multiple Noise Sources

    Directory of Open Access Journals (Sweden)

    Raymond L. Goldsworthy

    2014-10-01

    Full Text Available This study evaluates a spatial-filtering algorithm as a method to improve speech reception for cochlear-implant (CI users in reverberant environments with multiple noise sources. The algorithm was designed to filter sounds using phase differences between two microphones situated 1 cm apart in a behind-the-ear hearing-aid capsule. Speech reception thresholds (SRTs were measured using a Coordinate Response Measure for six CI users in 27 listening conditions including each combination of reverberation level (T60 = 0, 270, and 540 ms, number of noise sources (1, 4, and 11, and signal-processing algorithm (omnidirectional response, dipole-directional response, and spatial-filtering algorithm. Noise sources were time-reversed speech segments randomly drawn from the Institute of Electrical and Electronics Engineers sentence recordings. Target speech and noise sources were processed using a room simulation method allowing precise control over reverberation times and sound-source locations. The spatial-filtering algorithm was found to provide improvements in SRTs on the order of 6.5 to 11.0 dB across listening conditions compared with the omnidirectional response. This result indicates that such phase-based spatial filtering can improve speech reception for CI users even in highly reverberant conditions with multiple noise sources.

  15. Implementasi Order-Statistic Filters Untuk Mereduksi Noise Pada Citra Digital

    OpenAIRE

    Sihotang, Juni Santo

    2014-01-01

    Salt-and-pepper Noise or Gaussian Noise is noise there is usually found in digital images. Noise on the image usually occurs due to errors in image acquisition technique or because the image has been stored too long. To reduce noise we need a proper filter method so that the image resulted in accordance with the original. Order-Statistic Filters method is a non-linear filter whose results determined in accordance with the sorting image pixels that fil the area that are in the scope of the fil...

  16. A Nonlinear Hybrid Filter for Salt & Pepper Noise Removal from Color Images

    Directory of Open Access Journals (Sweden)

    Isma Irum

    2015-02-01

    Full Text Available Impulse noise reduction or removal is a very active research area of image processing. A nonlinear hybrid filter for removing fixed impulse noise (salt & pepper noise from color images has been proposed in this study. Technique is based on mathematical morphology and trimmed standard median filter. Proposed filter is composed of a sequence of morphological standard and well known operations erosion-dilation and trimmed standard median filter. It removes the fixed impulse noise (salt & pepper very well without distorting the image features, color components and edges. It does not introduce blurring and moving effects even in high noise densities (up to 90%. The standard similarity measure peak signal to noise ratio (PSNR and computation time have been used to evaluate the performance of proposed hybrid filter.

  17. Signal-to-noise ratio adaptive post-filtering method for intelligibility enhancement of telephone speech.

    Science.gov (United States)

    Jokinen, Emma; Yrttiaho, Santeri; Pulakka, Hannu; Vainio, Martti; Alku, Paavo

    2012-12-01

    Post-filtering can be utilized to improve the quality and intelligibility of telephone speech. Previous studies have shown that energy reallocation with a high-pass type filter works effectively in improving the intelligibility of speech in difficult noise conditions. The present study introduces a signal-to-noise ratio adaptive post-filtering method that utilizes energy reallocation to transfer energy from the first formant to higher frequencies. The proposed method adapts to the level of the background noise so that, in favorable noise conditions, the post-filter has a flat frequency response and the effect of the post-filtering is increased as the level of the ambient noise increases. The performance of the proposed method is compared with a similar post-filtering algorithm and unprocessed speech in subjective listening tests which evaluate both intelligibility and listener preference. The results indicate that both of the post-filtering methods maintain the quality of speech in negligible noise conditions and are able to provide intelligibility improvement over unprocessed speech in adverse noise conditions. Furthermore, the proposed post-filtering algorithm performs better than the other post-filtering method under evaluation in moderate to difficult noise conditions, where intelligibility improvement is mostly required.

  18. Aplikasi Filter Multivariate Empirical Mode Decomposition (MEMD Untuk Mereduksi Noise Pada Data VLF-EM

    Directory of Open Access Journals (Sweden)

    Muhammad Shafran Shofyan

    2017-01-01

    Full Text Available Alat VLF-EM menangkap gelombang elektromagnetik dari medium-medium disekitarnya. Sehingga, alat VLF-EM ini sangat sensitif terhadap benda-benda yang memiliki komponen listrik dan magnet yang besar. Benda-benda tersebut dapat dikatakan sebagai sumber noise. Selain itu, radiasi medan elektromagnetik akibat kilat dan petir juga merupakan sumber noise pada pengukuran VLF-EM. Noise-noise tersebut akan memengaruhi data dan mengakibatkan kesalahan interpretasi. Oleh sebab itu, perlu dilakukan penelitian yang berjudul “Aplikasi Filter Multivariate Empirical Mode Decomposition (MEMD Untuk Mereduksi Noise Pada Data VLF-EM” untuk menghilangkan noise-noise yang ada sehingga hasil akan lebih mudah untuk diinterpretasi. Penggunaan filter MEMD ini dikarenakan filter ini baik digunakan untuk mengolah sinyal secara multivariate. Pada penelitian ini dilakukan perbandingan antara data yang di­-filter dengan filter moving average dengan data yang di-filter dengan filter MEMD. Dari hasil penelitian ini, diketahui bahwa filter MEMD dapat mereduksi noise-noise yang memiliki frekuensi yang tinggi, terlihat dari hasil penampang resistivitas yang dihasilkan dari proses inversi.

  19. An innovations-based noise cancelling technique on inverse kepstrum whitening filter and adaptive FIR filter in beamforming structure

    National Research Council Canada - National Science Library

    Jeong, Jinsoo

    2011-01-01

    ...) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal...

  20. Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises.

    Science.gov (United States)

    Jin, Qiyu; Grama, Ion; Liu, Quansheng

    2017-01-01

    In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise.

  1. Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises.

    Directory of Open Access Journals (Sweden)

    Qiyu Jin

    Full Text Available In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise.

  2. A new simple method for analysing of thermal noise in switched-capacitor filters

    Science.gov (United States)

    Rashtian, Mohammad; Afshin Hemmatyar, Ali Mohammad; Hashemipour, Omid

    2012-12-01

    Thermal noise is one of the most important challenges in analogue integrated circuits design. This problem is more crucial in switched-capacitor (SC) filters due to the aliasing effect of wide-band thermal noise. In this article, a new simple method is proposed for estimating the power spectrum density of output thermal noise in SC filters, which have acceptable accuracy and short running time. In the proposed method, first using HSPICE simulator, accurate value of accumulated sampled noise on sampler capacitors in each clock state is achieved. Next, using difference equations of the SC filter, frequency response of the SC filter is shaped by time domain analysis. Based on the proposed method, a SC low-pass filter and a second-order SC band-pass filter are analysed. The results are validated by comparing to the previously measured data.

  3. Unscented Kalman filters for polarization state tracking and phase noise mitigation.

    Science.gov (United States)

    Jignesh, Jokhakar; Corcoran, Bill; Zhu, Chen; Lowery, Arthur

    2016-09-19

    Simultaneous polarization and phase noise tracking and compensation is proposed based on an unscented Kalman filter (UKF). We experimentally demonstrate the tracking under noise-loading and after 800-km single-mode fiber transmission with 20-Gbaud QPSK and 16-QAM signals. These experiments show that the proposed UKF outperforms both conventional blind tracing algorithms and a previously proposed extended Kalman filter, at the cost of higher complexity. Additionally, we propose and test modified Kalman filter algorithms to reduce computational complexity.

  4. Optimum receiver filter for a noise-based frequency-offset modulation system

    NARCIS (Netherlands)

    Bilal, Ibrahim; Meijerink, Arjan; Bentum, Marinus Jan

    2016-01-01

    A frequency-offset transmit-reference (TR) system using a noise carrier is considered in additive white Gaussian noise. The system is studied for any given spectrum of the noise carrier, and the expression for the transfer function of an optimal receiver front-end filter is derived. The maximum

  5. Application of RPF in MEMS gyro random drift filtering

    Science.gov (United States)

    Guowei, GAO; Yan, XIE

    2017-08-01

    With the development of micro-mechanical inertial technology, how to suppress the MEMS gyro’s random drift increasingly become a hot topic. In order to filter a certain type of MEMS gyro’s random drift, this paper introduces the regularized particle filter algorithm. The derivation of the algorithm and its application in MEMS gyro’s filtering process are described in detail in this paper: First, acquiring MEMS gyro’s static drift data and conducting data pre-treatment; then establishing the AR model by using time series analysis method, and transforming it into the corresponding state space model; finally, executing the estimation and compensation for MEMS gyro’s random drift with regular particle filter algorithm, and comparing it with other common methods in engineering. Tests and simulation results show that the regularized particle filter algorithm could achieve a good effect on the suppression of MEMS gyro’s random drift, it has a higher practical application value.

  6. Bayesian Filtering for Phase Noise Characterization and Carrier Synchronization of up to 192 Gb/s PDM 64-QAM

    DEFF Research Database (Denmark)

    Zibar, Darko; Carvalho, L.; Piels, Molly

    2014-01-01

    We show that phase noise estimation based on Bayesian filtering outperforms conventional time-domain approaches in the presence of moderate measurement noise. Additionally, carrier synchronization based on Bayesian filtering, in combination with expectation maximization, is demonstrated for the f...

  7. A modified LLCL-filter with the reduced conducted EMI noise

    DEFF Research Database (Denmark)

    Wu, Weimin; Sun, Yunjie; Lin, Zhe

    2013-01-01

    ) and the Differential-Mode (DM) EMI noises are investigated for the LCL- and LLCL-filters based single-phase full-bridge grid-tied inverter. Based on this, a modified LLCL-filter topology is proposed to provide enough attenuation on the conducted EMI noise as well as to reduce the DC-side leakage current. The parameter...... design method of the filter is also developed. The comparative analysis and discussion on four filter cases (the conventional LCL-filter, the conventional LLCL-filter, the modified LCL-filter, and the modified LLCL-filter) are carried out and verified through simulations and experiments on a 0.5 kW, 110...

  8. Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

    Science.gov (United States)

    Downie, John D.

    1995-01-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  9. A moving hum filter to suppress rotor noise in high-resolution airborne magnetic data

    Science.gov (United States)

    Xia, J.; Doll, W.E.; Miller, R.D.; Gamey, T.J.; Emond, A.M.

    2005-01-01

    A unique filtering approach is developed to eliminate helicopter rotor noise. It is designed to suppress harmonic noise from a rotor that varies slightly in amplitude, phase, and frequency and that contaminates aero-magnetic data. The filter provides a powerful harmonic noise-suppression tool for data acquired with modern large-dynamic-range recording systems. This three-step approach - polynomial fitting, bandpass filtering, and rotor-noise synthesis - significantly reduces rotor noise without altering the spectra of signals of interest. Two steps before hum filtering - polynomial fitting and bandpass filtering - are critical to accurately model the weak rotor noise. During rotor-noise synthesis, amplitude, phase, and frequency are determined. Data are processed segment by segment so that there is no limit on the length of data. The segment length changes dynamically along a line based on modeling results. Modeling the rotor noise is stable and efficient. Real-world data examples demonstrate that this method can suppress rotor noise by more than 95% when implemented in an aeromagnetic data-processing flow. ?? 2005 Society of Exploration Geophysicists. All rights reserved.

  10. Single-Channel Noise Reduction using Unified Joint Diagonalization and Optimal Filtering

    DEFF Research Database (Denmark)

    Nørholm, Sidsel Marie; Benesty, Jacob; Jensen, Jesper Rindom

    2014-01-01

    In this paper, the important problem of single-channel noise reduction is treated from a new perspective. The problem is posed as a filtering problem based on joint diagonalization of the covariance matrices of the desired and noise signals. More specifically, the eigenvectors from the joint...... solutions. In the distortionless case, the proposed filter achieves only a slightly worse output SNR, compared to the Wiener filter, along with no signal distortion. Moreover, when distortion is allowed, it is possible to achieve higher output SNRs compared to the Wiener filter. Alternatively, when a lower...

  11. REMOVAL OF IMPULSIVE NOISE USING WEIGHTED FUZZY MEAN FILTER BASED ON CLOUD MODEL

    Directory of Open Access Journals (Sweden)

    K. Kannan

    2013-08-01

    Full Text Available This paper proposes a weighted fuzzy mean filter based on cloud model and reports its performance in removing the impulsive noise from the digital image. In addition, the performance of the proposed weighted fuzzy mean filter is compared with already existing variants of median and switching filters using root mean square error, peak signal to noise ratio and quality index. Even though the image is corrupted by 90%, this weighted fuzzy mean filter is capable of recovering the original image with good detail preservation.

  12. Noise filtering in a multi-channel system using a tunable liquid crystal photonic bandgap fiber

    DEFF Research Database (Denmark)

    Petersen, Martin Nordal; Scolari, Lara; Tokle, Torger

    2008-01-01

    This paper reports on the first application of a liquid crystal infiltrated photonic bandgap fiber used as a tunable filter in an optical transmission system. The device allows low-cost amplified spontaneous emission (ASE) noise filtering and gain equalization with low insertion loss and broad...... tunability. System experiments show that the use of this filter increases for times the distance over which the optical signal-to-noise ratio (OSNR) is sufficient for error-free transmission with respect to the case in which no filtering is used....

  13. SIMULATION AND PERFORMANCE ANALYASIS OF ADAPTIVE FILTER IN NOISE CANCELLATION

    OpenAIRE

    RAJ KUMAR THENUA,; S.K. AGARWAL

    2010-01-01

    Noise problems in the environment have gained attention due to the tremendous growth of technology that has led to noisy engines, heavy machinery, high speed wind buffeting and other noise sources. The problem of controlling the noise level has become the focus of a tremendous amount of research over the years. In last few years various adaptive algorithms are developed for noise cancellation. In this paper we present an implementation of LMS (Least Mean Square), NLMS (Normalized Least Mean S...

  14. Noise Reduction Analysis of Radar Rainfall Using Chaotic Dynamics and Filtering Techniques

    Directory of Open Access Journals (Sweden)

    Soojun Kim

    2014-01-01

    Full Text Available The aim of this study is to evaluate the filtering techniques which can remove the noise involved in the time series. For this, Logistic series which is chaotic series and radar rainfall series are used for the evaluation of low-pass filter (LF and Kalman filter (KF. The noise is added to Logistic series by considering noise level and the noise added series is filtered by LF and KF for the noise reduction. The analysis for the evaluation of LF and KF techniques is performed by the correlation coefficient, standard error, the attractor, and the BDS statistic from chaos theory. The analysis result for Logistic series clearly showed that KF is better tool than LF for removing the noise. Also, we used the radar rainfall series for evaluating the noise reduction capabilities of LF and KF. In this case, it was difficult to distinguish which filtering technique is better way for noise reduction when the typical statistics such as correlation coefficient and standard error were used. However, when the attractor and the BDS statistic were used for evaluating LF and KF, we could clearly identify that KF is better than LF.

  15. Round-Off Noise of Multiplicative FIR Filters Implemented on an FPGA Platform

    Directory of Open Access Journals (Sweden)

    Jean-Jacques Vandenbussche

    2014-03-01

    Full Text Available The paper analyzes the effects of round-off noise on Multiplicative Finite Impulse Response (MFIR filters used to approximate the behavior of pole filters. General expressions to calculate the signal to round-off noise ratio of a cascade structure of Finite Impulse Response (FIR filters are obtained and applied on the special case of MFIR filters. The analysis is based on fixed-point implementations, which are most common in digital signal processing algorithms implemented in Field-Programmable Gate-Array (FPGA technology. Three well known scaling methods, i.e., L2 bound; infinity bound and absolute bound scaling are considered and compared. The paper shows that the ordering of the MFIR stages, in combination with the scaling methods, have an important impact on the round-off noise. An optimal ordering of the stages for a chosen scaling method can improve the round-off noise performance by 20 dB.

  16. Motor Bourn Magnetic Noise Filtering for Magnetometers in Micro-Rotary Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Nathan J. UNWIN

    2015-10-01

    Full Text Available Avionics systems of micro aerial vehicles (MAV pose unique problems in system design, sensor signal handling and control. This is evident in micro-rotary aircraft as their whole body rotates with the sensors of the flight control. The precise calculation of attitude and heading from magnetometer readings is complex due to the body rotation. It is made even more difficult by noise induced in the geomagnetic signal by fluctuating magnetic field of the closely positioned motors. Filtering that noise is challenging since the rotation speed of motors and the vehicle can be very close. This paper presents analysis of motor induced noise, based on experimental data of brushless micro motors. A novel time domain filter is proposed, designed, implemented in FPGA hardware, tested and compared to other filters. This filter provides good performance even when the rotational rate of the motor and vehicle are close and traditional frequency domain filters would perform poorly.

  17. A Bayes Formula for Nonlinear Filtering with Gaussian and Cox Noise

    Directory of Open Access Journals (Sweden)

    Vidyadhar Mandrekar

    2011-01-01

    Full Text Available A Bayes-type formula is derived for the nonlinear filter where the observation contains both general Gaussian noise as well as Cox noise whose jump intensity depends on the signal. This formula extends the well-known Kallianpur-Striebel formula in the classical non-linear filter setting. We also discuss Zakai-type equations for both the unnormalized conditional distribution as well as unnormalized conditional density in case the signal is a Markovian jump diffusion.

  18. A New Adaptive Square-Root Unscented Kalman Filter for Nonlinear Systems with Additive Noise

    Directory of Open Access Journals (Sweden)

    Yong Zhou

    2015-01-01

    Full Text Available The Kalman filter (KF, extended KF, and unscented KF all lack a self-adaptive capacity to deal with system noise. This paper describes a new adaptive filtering approach for nonlinear systems with additive noise. Based on the square-root unscented KF (SRUKF, traditional Maybeck’s estimator is modified and extended to nonlinear systems. The square root of the process noise covariance matrix Q or that of the measurement noise covariance matrix R is estimated straightforwardly. Because positive semidefiniteness of Q or R is guaranteed, several shortcomings of traditional Maybeck’s algorithm are overcome. Thus, the stability and accuracy of the filter are greatly improved. In addition, based on three different nonlinear systems, a new adaptive filtering technique is described in detail. Specifically, simulation results are presented, where the new filter was applied to a highly nonlinear model (i.e., the univariate nonstationary growth model (UNGM. The UNGM is compared with the standard SRUKF to demonstrate its superior filtering performance. The adaptive SRUKF (ASRUKF algorithm can complete direct recursion and calculate the square roots of the variance matrixes of the system state and noise, which ensures the symmetry and nonnegative definiteness of the matrixes and greatly improves the accuracy, stability, and self-adaptability of the filter.

  19. Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

    Science.gov (United States)

    Azarpour, Masoumeh; Enzner, Gerald

    2017-12-01

    Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome

  20. Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.

    Science.gov (United States)

    Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

    2011-01-01

    Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

  1. Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems

    Directory of Open Access Journals (Sweden)

    Min Chul Kim

    2011-10-01

    Full Text Available Recently, the range of available Radio Frequency Identification (RFID tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

  2. Discrete random signal processing and filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2013-01-01

    Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe

  3. Filtering of measurement noise with the 3D reconstruction algorithm

    DEFF Research Database (Denmark)

    Cappellin, Cecilia; Pivnenko, Sergey

    2014-01-01

    Two different antenna models are set up in GRASP and CHAMP, and noise is added to the radiated field. The noisy field is then given as input to the 3D reconstruction of DIATOOL and the SWE coefficients and the far-field radiated by the reconstructed currents are compared with the noise-free results...

  4. Noise Pollution Filters Bird Communities Based on Vocal Frequency

    OpenAIRE

    Francis, Clinton D.; Ortega, Catherine P.; Alexander Cruz

    2011-01-01

    BACKGROUND: Human-generated noise pollution now permeates natural habitats worldwide, presenting evolutionarily novel acoustic conditions unprecedented to most landscapes. These acoustics not only harm humans, but threaten wildlife, and especially birds, via changes to species densities, foraging behavior, reproductive success, and predator-prey interactions. Explanations for negative effects of noise on birds include disruption of acoustic communication through energetic masking, potentially...

  5. Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals.

    Science.gov (United States)

    Melia, Umberto; Clariá, Francesc; Vallverdú, Montserrat; Caminal, Pere

    2014-04-01

    To remove peak and spike artifacts in biological time series has represented a hard challenge in the last decades. Several methods have been implemented mainly based on adaptive filtering in order to solve this problem. This work presents an algorithm for removing peak and spike artifacts based on a threshold built on the analytic signal envelope. The algorithm was tested on simulated and real EEG signals that contain peak and spike artifacts with random amplitude and frequency occurrence. The performance of the filter was compared with commonly used adaptive filters. Three indexes were used for testing the performance of the filters: Correlation coefficient (ρ), mean of coherence function (C), and rate of absolute error (RAE). All these indexes were calculated between filtered signal and original signal without noise. It was found that the new proposed filter was able to reduce the amplitude of peak and spike artifacts with ρ>0.85, C>0.8, and RAELMS adaptive filter (ρ1). Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  6. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  7. Accelerometer North Finding System Based on the Wavelet Packet De-noising Algorithm and Filtering Circuit

    Directory of Open Access Journals (Sweden)

    LU Yongle

    2014-07-01

    Full Text Available This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis acceleration caused by the earth’s rotation and the acceleration’s instantaneous velocity is much weaker than the g-sensitivity acceleration. To get a high accuracy and a shorter time for north finding system, in this paper, the Filtering Circuit and the wavelet packet de-nosing algorithm are used as the following. First, the hardware is designed as the alternating currents across by filtering circuit, so the DC will be isolated and the weak AC signal will be amplified. The DC is interfering signal generated by the earth's gravity. Then, we have used a wavelet packet to filter the signal which has been done through the filtering circuit. Finally, compare the north finding results measured by wavelet packet filtering with those measured by a low-pass filter. Wavelet filter de-noise data shows that wavelet packet filtering and wavelet filter measurement have high accuracy. Wavelet Packet filtering has stronger ability to remove burst noise and higher engineering environment adaptability than that of Wavelet filtering. Experimental results prove the effectiveness and project implementation of the accelerometer north finding method based on wavelet packet de-noising algorithm.

  8. Adaptive notch filter for removal of coherent noise from infrared scanner data

    Science.gov (United States)

    Jaggi, Sandeep

    1991-11-01

    This paper addresses the use of an adaptive noise canceling technique to eliminate the coherent noise generated in scanner data. The technique is based on a Finite Impulse Response (FIR) adaptive noise canceler. A two-weight FIR filter is used to adaptively learn the characteristics of a sinusoid. This sinusoid is then removed from the data. The least Mean Squares (LMS) algorithm is used to converge to the coefficients of the adaptive filter during the learning process. An image corrupted with a single frequency periodic noise is used for investigating the algorithm. It is observed that the efficiency of the algorithm is dependent on the convergence gains and the initial positioning of the weights of the FIR filter. Because of the computational simplicity of the algorithm, it is possible to implement this in real-time mode.

  9. A study of infrared spectroscopy de-noising based on LMS adaptive filter

    Science.gov (United States)

    Mo, Jia-qing; Lv, Xiao-yi; Yu, Xiao

    2015-12-01

    Infrared spectroscopy has been widely used, but which often contains a lot of noise, so the spectral characteristic of the sample is seriously affected. Therefore the de-noising is very important in the spectrum analysis and processing. In the study of infrared spectroscopy, the least mean square (LMS) adaptive filter was applied in the field firstly. LMS adaptive filter algorithm can reserve the detail and envelope of the effective signal when the method was applied to infrared spectroscopy of breast cancer which signal-to-noise ratio (SNR) is lower than 10 dB, contrast and analysis the result with result of wavelet transform and ensemble empirical mode decomposition (EEMD). The three evaluation standards (SNR, root mean square error (RMSE) and the correlation coefficient (ρ)) fully proved de-noising advantages of LMS adaptive filter in infrared spectroscopy of breast cancer.

  10. Optimal Linear Filters for Pulse Height Measurements in the Presence of Noise

    Energy Technology Data Exchange (ETDEWEB)

    Nygaard, K.

    1966-07-15

    For measurements of nuclear pulse height spectra a linear filter is used between the pulse amplifier and the pulse height recorder so as to improve the signal/noise ratio. The problem of finding the optimal filter is investigated with emphasis on technical realizability. The maximum available signal/noise ratio is theoretically calculated on the basis of all the information which can be found in the output of the pulse amplifier, and on an assumed a priori knowledge of the pulse time of arrival. It is then shown that the maximum available signal/noise ratio can be obtained with practical measurements without any a priori knowledge of pulse time of arrival, and a general description of the optimal linear filter is given. The solution is unique, technically realizable, and based solely on data (noise power spectrum and pulse shape) which can be measured at the output terminals of the pulse amplifier used.

  11. The use of wavelet filters for reducing noise in posterior fossa Computed Tomography images

    Energy Technology Data Exchange (ETDEWEB)

    Pita-Machado, Reinado [Centro de Ingeniería Clínica. Guacalote y Circunvalación, Santa Clara 50200 (Cuba); Perez-Diaz, Marlen, E-mail: mperez@uclv.edu.cu; Lorenzo-Ginori, Juan V., E-mail: mperez@uclv.edu.cu; Bravo-Pino, Rolando, E-mail: mperez@uclv.edu.cu [Centro de Estudios de Electrónica y Tecnologías de la Información (CEETI), Universidad Central Marta Abreu de las Villas, Carretera a Camajuaní, km. 5 1/2 Santa Clara 54830 (Cuba)

    2014-11-07

    Wavelet transform based de-noising like wavelet shrinkage, gives the good results in CT. This procedure affects very little the spatial resolution. Some applications are reconstruction methods, while others are a posteriori de-noising methods. De-noising after reconstruction is very difficult because the noise is non-stationary and has unknown distribution. Therefore, methods which work on the sinogram-space don’t have this problem, because they always work over a known noise distribution at this point. On the other hand, the posterior fossa in a head CT is a very complex region for physicians, because it is commonly affected by artifacts and noise which are not eliminated during the reconstruction procedure. This can leads to some false positive evaluations. The purpose of our present work is to compare different wavelet shrinkage de-noising filters to reduce noise, particularly in images of the posterior fossa within CT scans in the sinogram-space. This work describes an experimental search for the best wavelets, to reduce Poisson noise in Computed Tomography (CT) scans. Results showed that de-noising with wavelet filters improved the quality of posterior fossa region in terms of an increased CNR, without noticeable structural distortions.

  12. BLASST: Band Limited Atomic Sampling With Spectral Tuning With Applications to Utility Line Noise Filtering.

    Science.gov (United States)

    Ball, Kenneth Ray; Hairston, W David; Franaszczuk, Piotr J; Robbins, Kay A

    2017-09-01

    In this paper, we present and test a new method for the identification and removal of nonstationary utility line noise from biomedical signals. The method, band limited atomic sampling with spectral tuning (BLASST), is an iterative approach that is designed to 1) fit nonstationarities in line noise by searching for best-fit Gabor atoms at predetermined time points, 2) self-modulate its fit by leveraging information from frequencies surrounding the target frequency, and 3) terminate based on a convergence criterion obtained from the same surrounding frequencies. To evaluate the performance of the proposed algorithm, we generate several simulated and real instances of nonstationary line noise and test BLASST along with alternative filtering approaches. We find that BLASST is capable of fitting line noise well and/or preserving local signal features relative to tested alternative filtering techniques. BLASST may present a useful alternative to bandpass, notch, or other filtering methods when experimentally relevant features have significant power in a spectrum that is contaminated by utility line noise, or when the line noise in question is highly nonstationary. This is of particular significance in electroencephalography experiments, where line noise may be present in the frequency bands of neurological interest and measurements are typically of low enough strength that induced line noise can dominate the recorded signals. In conjunction with this paper, the authors have released a MATLAB toolbox that performs BLASST on real, vector-valued signals (available at https://github.com/VisLab/blasst).

  13. A Sensor Fusion Algorithm for Filtering Pyrometer Measurement Noise in the Czochralski Crystallization Process

    Directory of Open Access Journals (Sweden)

    M. Komperød

    2011-01-01

    Full Text Available The Czochralski (CZ crystallization process is used to produce monocrystalline silicon for solar cell wafers and electronics. Tight temperature control of the molten silicon is most important for achieving high crystal quality. SINTEF Materials and Chemistry operates a CZ process. During one CZ batch, two pyrometers were used for temperature measurement. The silicon pyrometer measures the temperature of the molten silicon. This pyrometer is assumed to be accurate, but has much high-frequency measurement noise. The graphite pyrometer measures the temperature of a graphite material. This pyrometer has little measurement noise. There is quite a good correlation between the two pyrometer measurements. This paper presents a sensor fusion algorithm that merges the two pyrometer signals for producing a temperature estimate with little measurement noise, while having significantly less phase lag than traditional lowpass- filtering of the silicon pyrometer. The algorithm consists of two sub-algorithms: (i A dynamic model is used to estimate the silicon temperature based on the graphite pyrometer, and (ii a lowpass filter and a highpass filter designed as complementary filters. The complementary filters are used to lowpass-filter the silicon pyrometer, highpass-filter the dynamic model output, and merge these filtered signals. Hence, the lowpass filter attenuates noise from the silicon pyrometer, while the graphite pyrometer and the dynamic model estimate those frequency components of the silicon temperature that are lost when lowpass-filtering the silicon pyrometer. The algorithm works well within a limited temperature range. To handle a larger temperature range, more research must be done to understand the process' nonlinear dynamics, and build this into the dynamic model.

  14. Transistor-based filter for inhibiting load noise from entering a power supply

    Science.gov (United States)

    Taubman, Matthew S

    2013-07-02

    A transistor-based filter for inhibiting load noise from entering a power supply is disclosed. The filter includes a first transistor having an emitter coupled to a power supply, a collector coupled to a load, and a base. The filter also includes a first capacitor coupled between the base of the first transistor and a ground terminal. The filter further includes an impedance coupled between the base and a node between the collector and the load, or a second transistor and second capacitor. The impedance can be a resistor or an inductor.

  15. Removal of jitter noise in 3D shape recovery from image focus by using Kalman filter.

    Science.gov (United States)

    Jang, Hoon-Seok; Muhammad, Mannan Saeed; Choi, Tae-Sun

    2018-02-01

    In regard to Shape from Focus, one critical factor impacting system application is mechanical vibration of the translational stage causing jitter noise along the optical axis. This noise is not detectable by simply observing the image. However, when focus measures are applied, inaccuracies in the depth occur. In this article, jitter noise and focus curves are modeled by Gaussian distribution and quadratic function, respectively. Then Kalman filter is designed and applied to eliminate this noise in the focus curves, as a post-processing step after the focus measure application. Experiments are implemented with simulated objects and real objects to show usefulness of proposed algorithm. © 2017 Wiley Periodicals, Inc.

  16. A Computationally Efficient Filter for Reducing Shot Noise in Low S/N Data.

    Directory of Open Access Journals (Sweden)

    Mami Okada

    Full Text Available Functional multineuron calcium imaging (fMCI provides a useful experimental platform to simultaneously capture the spatiotemporal patterns of neuronal activity from a large cell population in situ. However, fMCI often suffers from low signal-to-noise ratios (S/N. The main factor that causes the low S/N is shot noise that arises from photon detectors. Here, we propose a new denoising procedure, termed the Okada filter, which is designed to reduce shot noise under low S/N conditions, such as fMCI. The core idea of the Okada filter is to replace the fluorescence intensity value of a given frame time with the average of two values at the preceding and following frames unless the focused value is the median among these three values. This process is iterated serially throughout a time-series vector. In fMCI data of hippocampal neurons, the Okada filter rapidly reduces background noise and significantly improves the S/N. The Okada filter is also applicable for reducing shot noise in electrophysiological data and photographs. Finally, the Okada filter can be described using a single continuous differentiable equation based on the logistic function and is thus mathematically tractable.

  17. Seismic random noise attenuation using modified wavelet thresholding

    Directory of Open Access Journals (Sweden)

    Qi-sheng Zhang

    2017-01-01

    Full Text Available In seismic exploration, random noise deteriorates the quality of acquired data. This study analyzed existing denoising methods used in seismic exploration from the perspective of random noise. Wavelet thresholding offers a new approach to reducing random noise in simulation results, synthetic data, and real data. A modified wavelet threshold function was developed by considering the merits and demerits of conventional soft and hard thresholding schemes. A MATLAB (matrix laboratory simulation model was used to compare the signal-to-noise ratios (SNRs and mean square errors (MSEs of the soft, hard, and modified threshold functions. The results demonstrated that the modified threshold function can avoid the pseudo-Gibbs phenomenon and produce a higher SNR than the soft and hard threshold functions. A seismic convolution model was built using seismic wavelets to verify the effectiveness of different denoising methods. The model was used to demonstrate that the modified thresholding scheme can effectively reduce random noise in seismic data and retain the desired signal. The application of the proposed tool to a real raw seismogram recorded during a land seismic exploration experiment located in north China clearly demonstrated its efficiency for random noise attenuation.

  18. A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics

    Directory of Open Access Journals (Sweden)

    Joaquín Míguez

    2004-11-01

    Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.

  19. Effects of noise, nonlinear processing, and linear filtering on perceived speech quality.

    Science.gov (United States)

    Arehart, Kathryn H; Kates, James M; Anderson, Melinda C

    2010-06-01

    The purpose of this study was to measure subjective quality ratings in listeners with normal hearing and listeners with hearing loss for speech subjected to a wide range of processing conditions that are representative of real hearing aids. Speech quality was assessed using a rating scale in a group of 14 listeners with normal hearing and 15 listeners with mild to moderately severe sensorineural hearing loss. Controlled simulations of hearing aid processing were used to process speech that included speech subjected to (1) noise and nonlinear processing, (2) linear filtering, and (3) combinations of noise, nonlinear processing, and linear filtering. The 32 conditions of noise and nonlinear processing included stationary speech-shaped nose, multitalker babble, peak clipping, quantization noise, spectral subtraction, and dynamic range compression (in quiet, with babble, and with spectral subtraction). The 32 linear filtering conditions included high-pass filtering, low-pass filtering, band-pass filtering, positive and negative spectral tilt, and resonance peaks. Subsets of these conditions were used for the 36 conditions that combined noise and nonlinear processing with linear processing. Both listeners with normal hearing and listeners with hearing loss gave consistent (reliable) ratings. In both listener groups, sound quality was significantly affected by the noise, nonlinear processing, and linear filtering conditions. Compared with the listeners with normal hearing, the listeners with hearing loss showed significantly lower ratings of sound quality in nearly all of the processing conditions. For the conditions included in the current hearing aid simulation, noise and nonlinear conditions had a greater effect on quality judgments than did the linear filtering conditions. The data reported here provide a comprehensive dataset of speech quality ratings for simulated hearing aid processing conditions. The results indicate that quality ratings by listeners with hearing

  20. Sigma-delta modulator: loop filters and quantization noise

    Directory of Open Access Journals (Sweden)

    Golub V. S.

    2013-05-01

    Full Text Available In this paper the sigma-delta modulator was analyzed with the use of simulation. In particular, the author studied dependence of the quantization noise on the loop filtration. The obtained results explain certain operation features of the modulator and make it possible to give advice as to its application.

  1. High-order noise filtering in nontrivial quantum logic gates

    CSIR Research Space (South Africa)

    Green, T

    2012-07-01

    Full Text Available that must be accounted for in order to understand total average error rates. We develop a treatment based on effective Hamiltonian theory that allows us to efficiently model the effect of classical noise on nontrivial single-bit quantum logic operations...

  2. Noise Reduction on Nasal Skin Temperature Measured by Radiation Thermometer with Differential Revision Filtering

    Science.gov (United States)

    Mizuno, Tota; Nozawa, Akio; Ide, Hideto

    This paper shows noise reduction on nasal skin temperature measured by a radiation thermometer with differential revision filtering. We evaluated and examined emotion stress from the nasal skin temperature fluctuation of the space-time with the radiation thermometer. The measured data with the radiation thermometer consists of three kind of factor, because of one point [24±3φ/m] measurement system. Three kinds of factors are temperature fluctuation dependent feelings stress, noise of the radiation thermometer and the other parts which it should measure as the subject moves. We make threshold processing on a change of an area in time of a measurement signal provided in a radiation thermometer. We suggested Differential Revision Filtering (DRF) that a new method use a measurement value of change of one second and a low pass filter go through. By using this method, we got the possibility that decrease movement of a measurement and a noise of measurement device.

  3. Usefulness of noise adaptive non-linear gaussian filter in FDG-PET study.

    Science.gov (United States)

    Nagayoshi, Makoto; Murase, Kenya; Fujino, Kouichi; Uenishi, Yusuke; Kawamata, Minoru; Nakamura, Yukio; Kitamura, Keishi; Higuchi, Ichiro; Oku, Naohiko; Hatazawa, Jun

    2005-09-01

    In positron emission tomography (PET) studies, shortening transmission (TR) scan time can improve patient comfort and increase scanner throughput. However, PET images from short TR scans may be degraded due to the statistical noise included in the TR image. The purpose of this study was to apply non-linear Gaussian (NLG) and noise adaptive NLG (ANLG) filters to TR images, and to evaluate the extent of noise reduction by the ANLG filter in comparison with that by the NLG filter using phantom and clinical studies. In phantom studies, pool phantoms of various diameters and injected doses of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) were used and the coefficients of variation (CVs) of the counts in the TR images processed with the NLG and ANLG filters were compared. In clinical studies, two normal volunteers and 13 patients with tumors were studied. In volunteer studies, the CV values in the liver were compared. In patient studies, the standardized uptake values (SUVs) of tumors in the emission images were obtained after processing the TR images using the NLG and ANLG filters. In phantom studies, the CV values in the TR images processed with the ANLG filter were smaller than those in the images processed with the NLG filter. When using the ANLG filter, their dependency on the phantom size, injected dose of FDG and TR scan time was smaller than when using the NLG filter. In volunteer studies, the CV values in the images processed with the ANLG filter were smaller than those in the images processed with the NLG filter, and were almost constant regardless of the TR scan time. In patient studies, there was an excellent correlation between the SUVs obtained from the images with a TR scan time of 7 min processed with the NLG filter (x) and those obtained from the images with a TR scan time of 4 min processed with the ANLG filter (y) (r = 0.995, y = 1.034x - 0.075). Our results suggest that the ANLG filter is effective and useful for noise reduction in TR images and shortening TR

  4. Noise measurement system at electron temperature down to 20 mK with combinations of the low pass filters.

    Science.gov (United States)

    Hashisaka, Masayuki; Yamauchi, Yoshiaki; Chida, Kensaku; Nakamura, Shuji; Kobayashi, Kensuke; Ono, Teruo

    2009-09-01

    We developed a quantum noise measurement system in a dilution refrigerator by using three kinds of cryogenic low pass filters. One of them is a commercial low pass filter inserted into the noise measurement lines instead of the conventional powder filter, which assures well-defined circuit parameters necessary for the noise measurement at a finite frequency. We checked that this filter gives sufficiently large attenuation up to 20 GHz at room temperature, 77 and 4.2 K. The electron temperature of the mesoscopic device placed in the present system was confirmed to be down to around 20 mK by measuring the thermal noise of the device.

  5. Effects of random noise in a dynamical model of love

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

    2011-07-15

    Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

  6. Noise reduction in FLAIR2images using Total Generalized Variation, Gaussian and Wiener filtering.

    Science.gov (United States)

    Schranzer, René; Rauscher, Alexander; Haimburger, Evelin; Bredies, Kristian; Reishofer, Gernot; Grabner, Günther

    2017-12-09

    Multiplication of FLAIR and T2-weighted MRI scans results in images (called FLAIR 2 ) with an improved contrast-to-noise ratio (CNR) for multiple sclerosis (MS) lesions but with a reduced signal-to-noise ratio (SNR). Denoising of these images may therefore further improve FLAIR 2 image quality. The purpose of this work is to present a systematic investigation of FLAIR 2 image denoising methods using Gaussian, Wiener and Total Generalized Variation (TGV) filtering approaches. T2-weighted and FLAIR data of four MS patients were used. For CNR and SNR measurements, each scan was performed up to three times. TGV, Gaussian and Wiener filtering was applied to T2, FLAIR and the FLAIR 2 data. FLAIR 2 images were afterwards additionally created using all combinations of input data (native, filtered T2 and filtered FLAIR). SNR and CNR measurements were performed using the subtraction method for all FLAIR 2 approaches (native and filtered input data) and for twenty MS lesions. Additionally, quantitative analysis of filtering based image blurring was performed on all data sets. FLAIR 2 images denoised with TGV showed the highest SNR and CNR, while SNR values were similar for Gaussian and Wiener filtered images. The average CNR over 20 MS lesions within the native FLAIR 2 (32.99) achieved an improvement to 91.17, 82.33 and 56.07 corresponding to TGV, Wiener and Gaussian filtering. FLAIR multiplied with T2.denoised showed no improvement, while FLAIR.denoised multiplied with T2 showed an increase by a factor of two to the native, not filtered FLAIR 2 . Blurring was most pronounced in Gaussian filtered images and similar in TGV and Wiener filtered images. FLAIR images filtered with Wiener or TGV multiplied with the unfiltered T2 results in FLAIR 2 images with increased SNR and CNR and with minimal edge blurring. Copyright © 2017. Published by Elsevier GmbH.

  7. Adaptive Filtering for FSCW Signal-to-noise Ratio Enhancement of SAW Interrogation Units

    Directory of Open Access Journals (Sweden)

    Díaz Luis

    2016-01-01

    Full Text Available A digital filter that improves the signal-to-noise ratio of the response of a FSCW (Frequency Stepped Continuous Wave scheme is presented. An improvement in signal-to-noise ratio represents an enhanced readout distance. This work considers this architecture as an interrogation unit for SAW tags with time and phase encoding. The parameters of the proposed digital filter, which is a non-linear edge preserving filter, were studied and tested for this specific application. An improvement of around 20dB in the SNR level was achieved. This filter preserves the phase of the signal at the time position of the reflectors, which is critical for correct identification of the code in phase encoding schemes.

  8. Statistics-based filtering for low signal-to-noise ratios, applied to rocket plume imaging

    Science.gov (United States)

    Hovland, Harald

    2017-05-01

    Extracting information from low signal to noise ratio images poses significant challenges. Noise makes extracting spatial features difficult, in particular if extraction of both large, smooth features at the same time as point-like features is required. This work describes a new statistical approach, able to handle both simultaneously, with the capacity of handling both positive and negative contrast signatures. The basic idea in this approach is that each pixel value can represent underlying statistics to a varying degree, depending on how similar it is to samples taken close to it, spatially and/or temporally. If the sample is similar to its surroundings, it is strongly filtered and also affects the filtering of neighboring samples, but if it is significantly different, it will remain largely unfiltered and does not influence neighboring pixel filtering. Simulations show that the filtering maintains energy conservation, significantly limits noise and at the same time maintains signal integrity. The filter is found to adapt to noise characteristics and spatiotemporal variations of the background. The technique is found to be well suited to rocket plume imaging, but is adaptable to a broad range of other applications.

  9. Seismic noise filters, vertical resonance frequency reduction with geometric anti-springs: a feasibility study

    CERN Document Server

    Bertolini, A; DeSalvo, R; Sannibale, V

    1999-01-01

    The achievement of low resonance frequency in vertical action oscillators is the most difficult of the basic ingredients for seismic noise attenuation filters. These oscillations are achieved by means of 'anti-springs' systems coupled with more classical suspension springs. Magnetic anti-springs have been used so far. Geometric anti-springs have been studied and the concept tested in this work, opening the way to a simpler and better performance seismic attenuation filters. (author)

  10. Seismic noise filters, vertical resonance frequency reduction with geometric anti-springs: a feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Bertolini, A.; Cella, G.; DeSalvo, R.; Sannibale, V. E-mail: sannibale_v@ligo.caltech.edu

    1999-10-11

    The achievement of low resonance frequency in vertical action oscillators is the most difficult of the basic ingredients for seismic noise attenuation filters. These oscillations are achieved by means of 'anti-springs' systems coupled with more classical suspension springs. Magnetic anti-springs have been used so far. Geometric anti-springs have been studied and the concept tested in this work, opening the way to a simpler and better performance seismic attenuation filters. (author)

  11. Basilar-Membrane Responses to Broadband Noise Modeled Using Linear Filters With Rational Transfer Functions

    OpenAIRE

    Recio-Spinoso, Alberto; Fan, Yun-Hui; Ruggero, Mario A.

    2010-01-01

    Basilar-membrane responses to white Gaussian noise were recorded using laser velocimetry at basal sites of the chinchilla cochlea with characteristic frequencies near 10 kHz and first-order Wiener kernels were computed by cross correlation of the stimuli and the responses. The presence or absence of minimum-phase behavior was explored by fitting the kernels with discrete linear filters with rational transfer functions. Excellent fits to the kernels were obtained with filters with transfer fun...

  12. A Noise-Filtering Approach for Cancer Drug Sensitivity Prediction

    OpenAIRE

    Turki, Turki; Wei, Zhi

    2016-01-01

    Accurately predicting drug responses to cancer is an important problem hindering oncologists' efforts to find the most effective drugs to treat cancer, which is a core goal in precision medicine. The scientific community has focused on improving this prediction based on genomic, epigenomic, and proteomic datasets measured in human cancer cell lines. Real-world cancer cell lines contain noise, which degrades the performance of machine learning algorithms. This problem is rarely addressed in th...

  13. Mathematical Analysis of Random Noise - and Appendixes

    Science.gov (United States)

    1952-01-01

    ONLY; ADMINISTRATIVE/OPERATIONAL USE; 24 FEB 1999. OTHER REQUESTS SHALL BE REFERRED THROUGH DEFENSE TECHNICAL INFORMATION CENTER, DTIC-BCS, 8725 JOHN J...and (2.1-6) give fw(g) dg = .- , () slic 7r go (2.2-4) 00r) = j cos 2rfr d[j w(g) dg] 1’ This is done by Wiener,ŕ loc. cit., and by G. W. Kenrick ...pp. 176-196 (Jan. 1929). Kenrick appears to be one of the first to apply, to noise problems, the correlatir’ functi.rn mlthnd of camputing the power

  14. Random noise attenuation using an improved anisotropic total variation regularization

    Science.gov (United States)

    Gemechu, Diriba; Yuan, Huan; Ma, Jianwei

    2017-09-01

    In seismic data processing, attenuation of random noise from the observed data is the basic step which improves the signal-to-noise ratio (SNR) of seismic data. In this paper, we proposed an anisotropic total bounded variation regularization approach to attenuate noise. An improved constraint convex optimization model is formulated for this approach and then the split Bregman algorithm is used to solve the optimization model. Generalized cross validation (GCV) technique is used to estimate the regularization parameter. Synthetic and real seismic data are considered to show the out performance of the proposed method in terms of event-preserving denoising, in comparison with FX deconvolution, shearlet hard thresholding, and anisotropic total variation methods. The numerical results indicate that the proposed method effectively attenuates random noise by preserving the structure and important features of seismic data.

  15. A Noise Reduction Method for Dual-Mass Micro-Electromechanical Gyroscopes Based on Sample Entropy Empirical Mode Decomposition and Time-Frequency Peak Filtering.

    Science.gov (United States)

    Shen, Chong; Li, Jie; Zhang, Xiaoming; Shi, Yunbo; Tang, Jun; Cao, Huiliang; Liu, Jun

    2016-05-31

    The different noise components in a dual-mass micro-electromechanical system (MEMS) gyroscope structure is analyzed in this paper, including mechanical-thermal noise (MTN), electronic-thermal noise (ETN), flicker noise (FN) and Coriolis signal in-phase noise (IPN). The structure equivalent electronic model is established, and an improved white Gaussian noise reduction method for dual-mass MEMS gyroscopes is proposed which is based on sample entropy empirical mode decomposition (SEEMD) and time-frequency peak filtering (TFPF). There is a contradiction in TFPS, i.e., selecting a short window length may lead to good preservation of signal amplitude but bad random noise reduction, whereas selecting a long window length may lead to serious attenuation of the signal amplitude but effective random noise reduction. In order to achieve a good tradeoff between valid signal amplitude preservation and random noise reduction, SEEMD is adopted to improve TFPF. Firstly, the original signal is decomposed into intrinsic mode functions (IMFs) by EMD, and the SE of each IMF is calculated in order to classify the numerous IMFs into three different components; then short window TFPF is employed for low frequency component of IMFs, and long window TFPF is employed for high frequency component of IMFs, and the noise component of IMFs is wiped off directly; at last the final signal is obtained after reconstruction. Rotation experimental and temperature experimental are carried out to verify the proposed SEEMD-TFPF algorithm, the verification and comparison results show that the de-noising performance of SEEMD-TFPF is better than that achievable with the traditional wavelet, Kalman filter and fixed window length TFPF methods.

  16. A generalized model via random walks for information filtering

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

    2016-08-06

    There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

  17. Random matrix theory filters and currency portfolio optimisation

    Science.gov (United States)

    Daly, J.; Crane, M.; Ruskin, H. J.

    2010-04-01

    Random matrix theory (RMT) filters have recently been shown to improve the optimisation of financial portfolios. This paper studies the effect of three RMT filters on realised portfolio risk, using bootstrap analysis and out-of-sample testing. We considered the case of a foreign exchange and commodity portfolio, weighted towards foreign exchange, and consisting of 39 assets. This was intended to test the limits of RMT filtering, which is more obviously applicable to portfolios with larger numbers of assets. We considered both equally and exponentially weighted covariance matrices, and observed that, despite the small number of assets involved, RMT filters reduced risk in a way that was consistent with a much larger S&P 500 portfolio. The exponential weightings indicated showed good consistency with the value suggested by Riskmetrics, in contrast to previous results involving stocks. This decay factor, along with the low number of past moves preferred in the filtered, equally weighted case, displayed a trend towards models which were reactive to recent market changes. On testing portfolios with fewer assets, RMT filtering provided less or no overall risk reduction. In particular, no long term out-of-sample risk reduction was observed for a portfolio consisting of 15 major currencies and commodities.

  18. Separating precipitation and evapotranspiration from noise - a new filter routine for high resolution lysimeter data

    Science.gov (United States)

    Peters, A.; Nehls, T.; Schonsky, H.; Wessolek, G.

    2013-12-01

    Weighing lysimeters yield the most precise and realistic measures for evapotranspiration (ET) and precipitation (P), which are of great importance for many questions regarding soil and atmospheric sciences. An increase or a decrease of the system mass (lysimeter plus seepage) indicate P or ET. These real mass changes of the lysimeter system have to be separated from measurement noise (e.g. caused by wind). The typical way to filter noisy lysimeter data is (i) to introduce a smoothing routine, like a moving average with a certain averaging window w, and then (ii) to apply a certain threshold value δ, accounting for measurement accuracy, separating significant from insignificant weight changes. Thus, two filter parameters are used, namely w and δ. Especially the time variable noise due to wind and strong signals due to heavy precipitation pose challenges for such noise reduction algorithms. If w is too small, data noise might be interpreted as real system changes. If w is too wide, small weight changes in short time intervals might be disregarded. The same applies to too small or too large values for δ. Application of constant w and δ lead either to unnecessary losses of accuracy or to faulty data due to noise. The aim of this paper is to solve that problem with a new filter routine, which is appropriate for any event, ranging from smooth evaporation to strong wind and heavy precipitation. Therefore, the new routine uses adaptive w and δ in dependence on signal strength and noise (AWAT - Adaptive Window and Adaptive Threshold filter). The AWAT filter, a moving average filter and the Savitzky-Golay filter with constant w and δ were applied to real lysimeter data comprising the above mentioned events. The AWAT filter was the only filter which could handle the data of all events very well. A sensitivity study shows that the magnitude of the maximum threshold value has practically no influence on the results, so that only the maximum window width must be predefined

  19. Separating precipitation and evapotranspiration from noise - a new filter routine for high-resolution lysimeter data

    Science.gov (United States)

    Peters, A.; Nehls, T.; Schonsky, H.; Wessolek, G.

    2014-03-01

    Weighing lysimeters yield the most precise and realistic measures for evapotranspiration (ET) and precipitation (P), which are of great importance for many questions regarding soil and atmospheric sciences. An increase or a decrease of the system mass (lysimeter plus seepage) indicates P or ET. These real mass changes of the lysimeter system have to be separated from measurement noise (e.g., caused by wind). A promising approach to filter noisy lysimeter data is (i) to introduce a smoothing routine, like a moving average with a certain averaging window, w, and then (ii) to apply a certain threshold value, δ, accounting for measurement accuracy, separating significant from insignificant weight changes. Thus, two filter parameters are used, namely w and δ. In particular, the time-variable noise due to wind as well as strong signals due to heavy precipitation pose challenges for such noise-reduction algorithms. If w is too small, data noise might be interpreted as real system changes. If w is too wide, small weight changes in short time intervals might be disregarded. The same applies to too small or too large values for δ. Application of constant w and δ leads either to unnecessary losses of accuracy or to faulty data due to noise. The aim of this paper is to solve this problem with a new filter routine that is appropriate for any event, ranging from smooth evaporation to strong wind and heavy precipitation. Therefore, the new routine uses adaptive w and δ in dependence on signal strength and noise (AWAT - adaptive window and adaptive threshold filter). The AWAT filter, a moving-average filter and the Savitzky-Golay filter with constant w and δ were applied to real lysimeter data comprising the above-mentioned events. The AWAT filter was the only filter that could handle the data of all events very well. A sensitivity study shows that the magnitude of the maximum threshold value has practically no influence on the results; thus only the maximum window width

  20. Adaptive Filtering to Enhance Noise Immunity of Impedance and Admittance Spectroscopy: Comparison with Fourier Transformation

    Science.gov (United States)

    Stupin, Daniil D.; Koniakhin, Sergei V.; Verlov, Nikolay A.; Dubina, Michael V.

    2017-05-01

    The time-domain technique for impedance spectroscopy consists of computing the excitation voltage and current response Fourier images by fast or discrete Fourier transformation and calculating their relation. Here we propose an alternative method for excitation voltage and current response processing for deriving a system impedance spectrum based on a fast and flexible adaptive filtering method. We show the equivalence between the problem of adaptive filter learning and deriving the system impedance spectrum. To be specific, we express the impedance via the adaptive filter weight coefficients. The noise-canceling property of adaptive filtering is also justified. Using the RLC circuit as a model system, we experimentally show that adaptive filtering yields correct admittance spectra and elements ratings in the high-noise conditions when the Fourier-transform technique fails. Providing the additional sensitivity of impedance spectroscopy, adaptive filtering can be applied to otherwise impossible-to-interpret time-domain impedance data. The advantages of adaptive filtering are justified with practical living-cell impedance measurements.

  1. Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

    Directory of Open Access Journals (Sweden)

    Mustafa Rahimie

    2017-01-01

    Full Text Available The method of least mean square (LMS is the commonly used algorithm in Adaptive filter due to its simplicity and robustness in implementation. In Active Noise Control application, a filtered reference signal is used prior to LMS algorithm to overcome the constraint on stability and convergence performance of the system due to the existence of the auxiliary path. This is known as Filtered-X LMS algorithm. In conventional Filtered-X LMS algorithm, each filter weight is updated once on every audio sample. This paper proposes the improved version of Filtered-X LMS algorithm with the use of multiple iteration of filter weight on every sample of audio signal. The proposed work uses field programmable gate arrays to realize real-time simulation on hardware for the noise signal of 500 Hz. Results from the real-time hardware simulations have shown much faster error convergence and better adaptation performance for different selections of learning constant μ, as compared with the conventional method.

  2. A model for radar images and its application to adaptive digital filtering of multiplicative noise.

    Science.gov (United States)

    Frost, V S; Stiles, J A; Shanmugan, K S; Holtzman, J C

    1982-02-01

    Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

  3. Distortion analysis of subband adaptive filtering methods for FMRI active noise control systems.

    Science.gov (United States)

    Milani, Ali A; Panahi, Issa M; Briggs, Richard

    2007-01-01

    Delayless subband filtering structure, as a high performance frequency domain filtering technique, is used for canceling broadband fMRI noise (8 kHz bandwidth). In this method, adaptive filtering is done in subbands and the coefficients of the main canceling filter are computed by stacking the subband weights together. There are two types of stacking methods called FFT and FFT-2. In this paper, we analyze the distortion introduced by these two stacking methods. The effect of the stacking distortion on the performance of different adaptive filters in FXLMS algorithm with non-minimum phase secondary path is explored. The investigation is done for different adaptive algorithms (nLMS, APA and RLS), different weight stacking methods, and different number of subbands.

  4. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

    Science.gov (United States)

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-12-27

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

  5. Random Noise Monopulse Radar System for Covert Tracking of Targets

    Science.gov (United States)

    Narayanan, Ram M.

    2002-07-01

    The University of Nebraska is currently developing a unique monopulse radar concept based on the use of random noise signal for covert tracking applications. This project is funded by the Missile Defense Agency (MDA). The advantage of this system over conventional frequency-modulated continuous wave (FMCW) or short pulse systems is its covertness resulting from the random waveform's immunity from interception and jamming. The system integrates a novel heterodyne correlation receiver with conventional monopulse architecture. Based on the previous work such as random noise interferometry, a series of theoretical analysis and simulations were conducted to examine the potential performance of this monopulse system. Furthermore, a prototype system is under development to exploit practical design aspects of phase comparison angle measurement. It is revealed that random noise monopulse radar can provide the same function as traditional monopulse radar, i.e., implement range and angular estimation and tracking in real time. The bandwidth of random noise signal can be optimized to achieve the best range resolution as well as the angular accuracy.

  6. Effect of Filters on the Noise Generated by Continuous Positive Airway Pressure Delivered via a Helmet

    National Research Council Canada - National Science Library

    Ricardo Hernández-Molina; Francisco Fernández-Zacarías; Isabel Benavente-Fernández; Gema Jiménez-Gómez; Simón Lubián-López

    2017-01-01

    ...) via a helmet poses is the generation of noise. The objective of our study was to assess the effect that the use of filter has on sound pressure levels generated by the delivery of positive airway pressure at different gas flow...

  7. Tracking and convergence of multi-channel Kalman filters for active noise control

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; van Ophem, S.

    2013-01-01

    The feed-forward broadband active noise control problem can be formulated as a state estimation problem to achieve a faster rate of convergence than the filtered reference least mean squares algorithm and possibly also a better tracking performance. A multiple input/multiple output Kalman algorithm

  8. Effect of Filters on the Noise Generated by Continuous Positive Airway Pressure Delivered via a Helmet

    Directory of Open Access Journals (Sweden)

    Ricardo Hernández-Molina

    2017-01-01

    Full Text Available Introduction: One of the problems that the delivery of continuous positive airway pressure (CPAP via a helmet poses is the generation of noise. The objective of our study was to assess the effect that the use of filter has on sound pressure levels generated by the delivery of positive airway pressure at different gas flow rates. Materials and Methods: Sound pressure levels generated by neonatal helmet CPAP delivery were measured at different gas flows (20, 30, and 40 l/min with and without a breathing filter. Noise intensity was measured by installing microphones in the inner ear of dummy heads wearing helmets. Results: The sound pressure level increased by 38% at a gas flow of 40 l/min, as compared to a gas flow of 20 l/min {74 dBA [interquartile range (IQR 2,2] vs 52 dBA (IQR 5,9, respectively}. Using the breathing filter as a diffuser has a variety of effects on sound pressure levels according to the gas flow rate. Conclusion: The intensity of the noise generated by helmet delivery of positive airway pressure depends on the type of helmet used, gas flow, and use or not of a diffuser filter. Breathing filters with gas flows over 30 l/min might not be recommended since they would not attenuate but will rather amplify sound pressure.

  9. A low-noise widely tunable Gm-C filter with frequency calibration

    Science.gov (United States)

    Yu, Wang; Jing, Liu; Na, Yan; Hao, Min

    2016-09-01

    A fourth-order Gm-C Chebyshev low-pass filter is presented as channel selection filter for reconfigurable multi-mode wireless receivers. Low-noise technologies are proposed in optimizing the noise characteristics of both the Gm cells and the filter topology. A frequency tuning strategy is used by tuning both the transconductance of the Gm cells and the capacitance of the capacitor banks. To achieve accurate cut-off frequencies, an on-chip calibration circuit is presented to compensate for the frequency inaccuracy introduced by process variation. The filter is fabricated in a 0.13 μm CMOS process. It exhibits a wide programmable bandwidth from 322.5 kHz to 20 MHz. Measured results show that the filter has low input referred noise of 5.9 \\text{nV}/\\sqrt {\\text{Hz}} and high out-of-band IIP3 of 16.2 dBm. It consumes 4.2 and 9.5 mW from a 1 V power supply at its lowest and highest cut-off frequencies respectively. Project supported by the National Natural Science Foundation of China (No. 61574045).

  10. Sigma-Point Particle Filter for Parameter Estimation in a Multiplicative Noise Environment

    Directory of Open Access Journals (Sweden)

    Youmin Tang

    2011-12-01

    Full Text Available A pre-requisite for the “optimal estimate” by the ensemble-based Kalman filter (EnKF is the Gaussian assumption for background and observation errors, which is often violated when the errors are multiplicative, even for a linear system. This study first explores the challenge of the multiplicative noise to the current EnKF schemes. Then, a Sigma Point Kalman Filter based Particle Filter (SPPF is presented as an alternative to solve the issues associated with multiplicative noise. The classic Lorenz '63 model and a higher dimensional Lorenz '96 model are used as test beds for the data assimilation experiments. Performance of the SPPF algorithm is compared against a standard EnKF as well as an advanced square-root Sigma-Point Kalman Filters (SPKF. The results show that the SPPF outperforms the EnKF and the square-root SPKF in the presence of multiplicative noise. The super ensemble structure of the SPPF makes it computationally attractive compared to the standard Particle Filter (PF.

  11. A generalized model via random walks for information filtering

    Science.gov (United States)

    Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

    2016-08-01

    There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.

  12. A noise filtration technique for fabric defects image using curvelet transform domain filters

    Science.gov (United States)

    Luo, Jing; Ni, Jian-Yun; Lin, Shu-Zhong; Song, Li-Mei

    2010-08-01

    A noise filtration technique for fabric defects image using curvelet transform domain Filters is proposed in this paper. Firstly, we used FDCT_WARPING to decompose image into five scales curvelet coefficients. Secondly, the proposed algorithm distinguished major edges from noise background at the third scale. Thirdly, the possible lost edges in the procedure above were detected according to the decaying lever of the coefficients. Fourthly, the edges of the defect at the second scale were detected by four correlation coefficients in the two directions at the third scale. Fifthly, the curvelet coefficients at the fourth scale are filtered by the decaying lever. Sixthly, the curvelet coefficients at the fifth scale are filtered by hard threshing. Finally, the processed coefficients are reconstructed. The tests on the developed algorithms were performed with images from TILDA's Textile Texture Database, and suggest that the new approach outperforms wavelet methods in image denoising.

  13. Aplikasi Metode F-K Filter Untuk Mereduksi Linear Noise Pada Data Seismik di Daerah Batuan Vulkanik

    Directory of Open Access Journals (Sweden)

    Raden Bagus Fauzan Irshadibima

    2017-03-01

    Full Text Available Batuan beku yang menutupi batuan induk akan menyebabkan penjalaran gelombang seismic terganggu, efek ini terjadi karena sifat alami dari batuan beku yang memiliki sifat refraksi yang kuat. Efek ini akan mempengaruhi data seismik yang mengakibatkan hasil pengolahan data dari penampang seismik menjadi buram/tidak jelas. Oleh sebab itu, untuk mereduksi noise pada data seismik perlu dilakukannya filtering. Filter yang digunakan pada penelitian ini adalah f-k filter. Filter ini bertujuan untuk mengurangi noise linear yang hadir pada data seismik dengan cara mentransformasikan bilangan waktu-offset kedalam frequency-bilangan gelombang. Tahapan pengolahan data yang dilakukan adalah geometri, koreksi statik, muting, filter frekuensi, dekonvolusi lalu terakhir adalah filter f-k. Setelah dilakukan pengolahan data noise-noise ground roll dapat direduksi dengan baik namun event seismik pada daerah batuan beku vulkanik belum dapat dimunculkan.

  14. Random noise characterization on the carrying capacities of a ...

    African Journals Online (AJOL)

    We have utilised the technique of a numerical simulation to study the impact of environmental random noise on the carrying capacities of a mathematical model of ... some sort of a sustainable mitigation strategy that is capable of providing a long term solution to the impact of crude oil pollution on the Ogoni ecosystem.

  15. Generalized diffraction-stack migration and filtering of coherent noise

    KAUST Repository

    Zhan, Ge

    2014-01-27

    We reformulate the equation of reverse-time migration so that it can be interpreted as summing data along a series of hyperbola-like curves, each one representing a different type of event such as a reflection or multiple. This is a generalization of the familiar diffraction-stack migration algorithm where the migration image at a point is computed by the sum of trace amplitudes along an appropriate hyperbola-like curve. Instead of summing along the curve associated with the primary reflection, the sum is over all scattering events and so this method is named generalized diffraction-stack migration. This formulation leads to filters that can be applied to the generalized diffraction-stack migration operator to mitigate coherent migration artefacts due to, e.g., crosstalk and aliasing. Results with both synthetic and field data show that generalized diffraction-stack migration images have fewer artefacts than those computed by the standard reverse-time migration algorithm. The main drawback is that generalized diffraction-stack migration is much more memory intensive and I/O limited than the standard reverse-time migration method. © 2014 European Association of Geoscientists & Engineers.

  16. 3D filtering technique in presence of additive noise in color videos implemented on DSP

    Science.gov (United States)

    Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Palacios, Alfredo

    2014-05-01

    A filtering method for color videos contaminated by additive noise is presented. The proposed framework employs three filtering stages: spatial similarity filtering, neighboring frame denoising, and spatial post-processing smoothing. The difference with other state-of- the-art filtering methods, is that this approach, based on fuzzy logic, analyses basic and related gradient values between neighboring pixels into a 7 fi 7 sliding window in the vicinity of a central pixel in each of the RGB channels. Following, the similarity measures between the analogous pixels in the color bands are taken into account during the denoising. Next, two neighboring video frames are analyzed together estimating local motions between the frames using block matching procedure. In the final stage, the edges and smoothed areas are processed differently in a current frame during the post-processing filtering. Numerous simulations results confirm that this 3D fuzzy filter perform better than other state-of-the- art methods, such as: 3D-LLMMSE, WMVCE, RFMDAF, FDARTF G, VBM3D and NLM, in terms of objective criteria (PSNR, MAE, NCD and SSIM) as well as subjective perception via human vision system in the different color videos. An efficiency analysis of the designed and other mentioned filters have been performed on the DSPs TMS320 DM642 and TMS320DM648 by Texas Instruments through MATLAB and Simulink module showing that the novel 3D fuzzy filter can be used in real-time processing applications.

  17. Performance of a Y-Ba-Cu-O superconducting filter/GaAs low noise amplifier hybrid circuit

    Science.gov (United States)

    Bhasin, Kul B.; Toncich, S. S.; Chorey, C. M.; Bonetti, R. R.; Williams, A. E.

    1992-01-01

    A superconducting 7.3 GHz two-pole microstrip bandpass filter and a GaAs low noise amplifier (LNA) were combined into a hybrid circuit and characterized at liquid nitrogen temperatures. This superconducting/seismology circuit's performance was compared to a gold filter/GaAs LNA hybrid circuit. The superconducting filter/GaAs LNA hybrid circuit showed higher gain and lower noise figure than its gold counterpart.

  18. Modeling Random Telegraph Noise Under Switched Bias Conditions Using Cyclostationary RTS Noise

    NARCIS (Netherlands)

    van der Wel, A.P.; Klumperink, Eric A.M.; Vandamme, L.K.J.; Nauta, Bram

    In this paper, we present measurements and simulation of random telegraph signal (RTS) noise in n-channel MOSFETs under periodic large signal gate-source excitation (switched bias conditions). This is particularly relevant to analog CMOS circuit design where large signal swings occur and where LF

  19. Noise Reduction in Breath Sound Files Using Wavelet Transform Based Filter

    Science.gov (United States)

    Syahputra, M. F.; Situmeang, S. I. G.; Rahmat, R. F.; Budiarto, R.

    2017-04-01

    The development of science and technology in the field of healthcare increasingly provides convenience in diagnosing respiratory system problem. Recording the breath sounds is one example of these developments. Breath sounds are recorded using a digital stethoscope, and then stored in a file with sound format. This breath sounds will be analyzed by health practitioners to diagnose the symptoms of disease or illness. However, the breath sounds is not free from interference signals. Therefore, noise filter or signal interference reduction system is required so that breath sounds component which contains information signal can be clarified. In this study, we designed a filter called a wavelet transform based filter. The filter that is designed in this study is using Daubechies wavelet with four wavelet transform coefficients. Based on the testing of the ten types of breath sounds data, the data is obtained in the largest SNRdB bronchial for 74.3685 decibels.

  20. Open quantum random walk in terms of quantum Bernoulli noise

    Science.gov (United States)

    Wang, Caishi; Wang, Ce; Ren, Suling; Tang, Yuling

    2018-03-01

    In this paper, we introduce an open quantum random walk, which we call the QBN-based open walk, by means of quantum Bernoulli noise, and study its properties from a random walk point of view. We prove that, with the localized ground state as its initial state, the QBN-based open walk has the same limit probability distribution as the classical random walk. We also show that the probability distributions of the QBN-based open walk include those of the unitary quantum walk recently introduced by Wang and Ye (Quantum Inf Process 15:1897-1908, 2016) as a special case.

  1. A Stochastic Simulation Framework for the Prediction of Strategic Noise Mapping and Occupational Noise Exposure Using the Random Walk Approach

    Science.gov (United States)

    Haron, Zaiton; Bakar, Suhaimi Abu; Dimon, Mohamad Ngasri

    2015-01-01

    Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces. PMID:25875019

  2. Band-gap tunable dielectric elastomer filter for low frequency noise

    Science.gov (United States)

    Jia, Kun; Wang, Mian; Lu, Tongqing; Zhang, Jinhua; Wang, Tiejun

    2016-05-01

    In the last decades, diverse materials and technologies for sound insulation have been widely applied in engineering. However, suppressing the noise radiation at low frequency still remains a challenge. In this work, a novel membrane-type smart filter, consisting of a pre-stretched dielectric elastomer membrane with two compliant electrodes coated on the both sides, is presented to control the low frequency noise. Since the stiffness of membrane dominates its acoustic properties, sound transmission band-gap of the membrane filter can be tuned by adjusting the voltage applied to the membrane. The impedance tube experiments have been carried out to measure the sound transmission loss (STL) of the filters with different electrodes, membrane thickness and pre-stretch conditions. The experimental results show that the center frequency of sound transmission band-gap mainly depends on the stress in the dielectric elastomer, and a large band-gap shift (more than 60 Hz) can be achieved by tuning the voltage applied to the 85 mm diameter VHB4910 specimen with pre-stretch {λ }0=3. Based on the experimental results and the assumption that applied electric field is independent of the membrane behavior, 3D finite element analysis has also been conducted to calculate the membrane stress variation. The sound filter proposed herein may provide a promising facility to control low frequency noise source with tonal characteristics.

  3. Listening to the noise: random fluctuations reveal gene network parameters

    Energy Technology Data Exchange (ETDEWEB)

    Munsky, Brian [Los Alamos National Laboratory; Khammash, Mustafa [UCSB

    2009-01-01

    The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.

  4. Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

    Directory of Open Access Journals (Sweden)

    Sebastián Pantoja

    2009-08-01

    Full Text Available The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers’ outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called “baseline errors” associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver’s output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network.

  5. Calibration of correlation radiometers using pseudo-random noise signals.

    Science.gov (United States)

    Pérez, Isaac Ramos; Bosch-Lluis, Xavi; Camps, Adriano; Alvarez, Nereida Rodriguez; Hernandez, Juan Fernando Marchán; Domènech, Enric Valencia; Vernich, Carlos; de la Rosa, Sonia; Pantoja, Sebastián

    2009-01-01

    The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers' outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called "baseline errors" associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN) signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver's output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network.

  6. The Miniaturization of the AFIT Random Noise Radar

    Science.gov (United States)

    2013-03-01

    Gaussian , RI = σ2n. If k is chosen to be 1/σ2, the result is simply [30] H = X∗. (2.35) In other words, the ideal filter in the presence of white noise...Virtex-5. The HDL code for the correlation algorithm consists of a combination of Verilog , schematic- based coding , and Xilinx IP Cores. Verilog is an HDL...synthesizable. In addition to Verilog coding , the Xilinx ISE includes a graphical method for representing the register-transfer level circuits needed for

  7. Basilar-membrane responses to broadband noise modeled using linear filters with rational transfer functions.

    Science.gov (United States)

    Recio-Spinoso, Alberto; Fan, Yun-Hui; Ruggero, Mario A

    2011-05-01

    Basilar-membrane responses to white Gaussian noise were recorded using laser velocimetry at basal sites of the chinchilla cochlea with characteristic frequencies near 10 kHz and first-order Wiener kernels were computed by cross correlation of the stimuli and the responses. The presence or absence of minimum-phase behavior was explored by fitting the kernels with discrete linear filters with rational transfer functions. Excellent fits to the kernels were obtained with filters with transfer functions including zeroes located outside the unit circle, implying nonminimum-phase behavior. These filters accurately predicted basilar-membrane responses to other noise stimuli presented at the same level as the stimulus for the kernel computation. Fits with all-pole and other minimum-phase discrete filters were inferior to fits with nonminimum-phase filters. Minimum-phase functions predicted from the amplitude functions of the Wiener kernels by Hilbert transforms were different from the measured phase curves. These results, which suggest that basilar-membrane responses do not have the minimum-phase property, challenge the validity of models of cochlear processing, which incorporate minimum-phase behavior. © 2011 IEEE

  8. Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

    Science.gov (United States)

    Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bullard, B.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; De Geronimo, G.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; de Vries, J. Jan; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, S.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Radeka, V.; Rafique, A.; Rescia, S.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Thorn, C.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Yu, B.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-08-01

    The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.

  9. Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

    Energy Technology Data Exchange (ETDEWEB)

    Acciarri, R.; et al.

    2017-05-20

    The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.

  10. Novel Results for Induced l∞ Stability for Digital Filters with External Noise

    Science.gov (United States)

    Kokil, Priyanka; Arockiaraj, S. Xavier

    This paper establishes novel criteria for the induced l∞ stability to avoid overflow oscillations in fixed-point digital filters with generalized overflow non-linearities and external noise. The proposed linear matrix inequality (LMI)-based criteria ensure exponential stability as well as confirm reduction in the influence of external noise. The generalized overflow non-linearities which are considered for analysis commonly occur in practice, viz. saturation, zeroing, two's complement, and triangular. The presented approach unifies a string of existing results which are derived by considering saturation non-linearities and external interference. Simulation examples are shown to validate the usefulness of the proposed approach.

  11. LMI Design of Frequency Selective LMS Adaptive Filters and Its Application to Active Noise Control

    Science.gov (United States)

    Wakasa, Yuji; Izumi, Tatsuya; Yamamoto, Yutaka

    Recently, a frequency selective adaptive filter design method for active noise control has been proposed based on the so-called least mean square algorithm. However, this method does not sufficiently exploit the degree of freedom of the step parameter of the recursive rule in the case where a priori information on an uncertain plant is available. This paper proposes a design method of the step parameter such that noise cancellation is guaranteed against the plant uncertainty. The design problem of the step parameter is reduced to an optimization problem involving linear matrix inequalities and is efficiently solvable. Experimental results are provided to illustrate the effectiveness of the proposed method.

  12. Cat Swarm Optimization Based Functional Link Artificial Neural Network Filter for Gaussian Noise Removal from Computed Tomography Images

    Directory of Open Access Journals (Sweden)

    M. Kumar

    2016-01-01

    Full Text Available Gaussian noise is one of the dominant noises, which degrades the quality of acquired Computed Tomography (CT image data. It creates difficulties in pathological identification or diagnosis of any disease. Gaussian noise elimination is desirable to improve the clarity of a CT image for clinical, diagnostic, and postprocessing applications. This paper proposes an evolutionary nonlinear adaptive filter approach, using Cat Swarm Functional Link Artificial Neural Network (CS-FLANN to remove the unwanted noise. The structure of the proposed filter is based on the Functional Link Artificial Neural Network (FLANN and the Cat Swarm Optimization (CSO is utilized for the selection of optimum weight of the neural network filter. The applied filter has been compared with the existing linear filters, like the mean filter and the adaptive Wiener filter. The performance indices, such as peak signal to noise ratio (PSNR, have been computed for the quantitative analysis of the proposed filter. The experimental evaluation established the superiority of the proposed filtering technique over existing methods.

  13. Joint Conditional Random Field Filter for Multi-Object Tracking

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  14. Optimal Linear Filters. 2. Pulse Time Measurements in the Presence of Noise

    Energy Technology Data Exchange (ETDEWEB)

    Nygaard, K.

    1966-09-15

    The problem of calculating the maximum available timing information contained in nuclear pulses in the presence of noise is solved theoretically. Practical experiments show that the theoretical values can be obtained by very simple, but untraditional, means. An output pulse from a practical filter connected to a charge sensitive amplifier with a Ge(Li) detector showed a rise time of 30 ns and a noise level of less than 5 keV. The time jitter measured was inversely proportional to the pulse height and less than 30 ns for 10 keV pulses. With the timing filter shown solid state detectors can be classified somewhere between Nal scintillators and organic scintillators with respect to time resolution.

  15. Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise.

    Science.gov (United States)

    Cui, Bingbo; Chen, Xiyuan; Tang, Xihua; Huang, Haoqian; Liu, Xiao

    2017-10-10

    In order to improve the accuracy of GNSS/INS working in GNSS-denied environment, a robust cubature Kalman filter (RCKF) is developed by considering colored measurement noise and missing observations. First, an improved cubature Kalman filter (CKF) is derived by considering colored measurement noise, where the time-differencing approach is applied to yield new observations. Then, after analyzing the disadvantages of existing methods, the measurement augment in processing colored noise is translated into processing the uncertainties of CKF, and new sigma point update framework is utilized to account for the bounded model uncertainties. By reusing the diffused sigma points and approximation residual in the prediction stage of CKF, the RCKF is developed and its error performance is analyzed theoretically. Results of numerical experiment and field test reveal that RCKF is more robust than CKF and extended Kalman filter (EKF), and compared with EKF, the heading error of land vehicle is reduced by about 72.4%. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Effects of noise, nonlinear processing, and linear filtering on perceived music quality.

    Science.gov (United States)

    Arehart, Kathryn H; Kates, James M; Anderson, Melinda C

    2011-03-01

    The purpose of this study was to determine the relative impact of different forms of hearing aid signal processing on quality ratings of music. Music quality was assessed using a rating scale for three types of music: orchestral classical music, jazz instrumental, and a female vocalist. The music stimuli were subjected to a wide range of simulated hearing aid processing conditions including, (1) noise and nonlinear processing, (2) linear filtering, and (3) combinations of noise, nonlinear, and linear filtering. Quality ratings were measured in a group of 19 listeners with normal hearing and a group of 15 listeners with sensorineural hearing impairment. Quality ratings in both groups were generally comparable, were reliable across test sessions, were impacted more by noise and nonlinear signal processing than by linear filtering, and were significantly affected by the genre of music. The average quality ratings for music were reasonably well predicted by the hearing aid speech quality index (HASQI), but additional work is needed to optimize the index to the wide range of music genres and processing conditions included in this study.

  17. A biophysical model of adaptive noise filtering in the shark brain.

    Science.gov (United States)

    Bratby, Peter; Montgomery, John; Sneyd, James

    2014-02-01

    Sharks detect their prey using an extremely sensitive electrosensory system that is capable of distinguishing weak external stimuli from a relatively strong background noise generated by the animal itself. Experiments indicate that part of the shark's hindbrain, the dorsal octavolateralis nucleus (DON), is responsible for extracting the external stimulus using an adaptive filter mechanism to suppress signals correlated with the shark's breathing motion. The DON's principal neuron integrates input from afferents as well as many thousands of parallel fibres transmitting, inter alia, breathing-correlated motor command signals. There are a number of models in the literature, studying how this adaptive filtering mechanisms occurs, but most of them are based on a spike-train model approach.This paper presents a biophysically based computational simulation which demonstrates a mechanism for adaptive noise filtering in the DON. A spatial model of the neuron uses the Hodgkin-Huxley equations to simulate the propagation of action potentials along the dendrites. Synaptic inputs are modelled by applied currents at various positions along the dendrites, whose input conductances are varied according to a simple learning rule.Simulation results show that the model is able to demonstrate adaptive filtering in agreement with previous experimental and modelling studies. Furthermore, the spatial nature of the model does not greatly affect its learning properties, and in its present form is effectively equivalent to an isopotential model which does not incorporate a spatial element.

  18. Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

    Science.gov (United States)

    Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

    2016-08-01

    Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

  19. Teaching learning based optimization-functional link artificial neural network filter for mixed noise reduction from magnetic resonance image.

    Science.gov (United States)

    Kumar, M; Mishra, S K

    2017-01-01

    The clinical magnetic resonance imaging (MRI) images may get corrupted due to the presence of the mixture of different types of noises such as Rician, Gaussian, impulse, etc. Most of the available filtering algorithms are noise specific, linear, and non-adaptive. There is a need to develop a nonlinear adaptive filter that adapts itself according to the requirement and effectively applied for suppression of mixed noise from different MRI images. In view of this, a novel nonlinear neural network based adaptive filter i.e. functional link artificial neural network (FLANN) whose weights are trained by a recently developed derivative free meta-heuristic technique i.e. teaching learning based optimization (TLBO) is proposed and implemented. The performance of the proposed filter is compared with five other adaptive filters and analyzed by considering quantitative metrics and evaluating the nonparametric statistical test. The convergence curve and computational time are also included for investigating the efficiency of the proposed as well as competitive filters. The simulation outcomes of proposed filter outperform the other adaptive filters. The proposed filter can be hybridized with other evolutionary technique and utilized for removing different noise and artifacts from others medical images more competently.

  20. The Influence of Optical Filtering on the Noise Performance of Microwave Photonic Phase Shifters Based on SOAs

    DEFF Research Database (Denmark)

    Lloret, Juan; Ramos, Francisco; Xue, Weiqi

    2011-01-01

    Different optical filtering scenarios involving microwave photonic phase shifters based on semiconductor optical amplifiers are investigated numerically as well as experimentally with respect to noise performance. Investigations on the role of the modulation depth and number of elements in cascaded...... shifting stages are also carried out. Suppression of the noise level by more than 5 dB has been achieved in schemes based on band-pass optical filtering when three phase shifting stages are cascaded....

  1. Application of variational mode decomposition to seismic random noise reduction

    Science.gov (United States)

    Liu, Wei; Cao, Siyuan; Wang, Zhiming

    2017-08-01

    We have proposed a new denoising method for the simultaneous noise reduction and preservation of seismic signals based on variational mode decomposition (VMD). VMD is a recently developed adaptive signal decomposition method and an advance in non-stationary signal analysis. It solves the mode-mixing and non-optimal reconstruction performance problems of empirical mode decomposition that have existed for a long time. By using VMD, a multi-component signal can be non-recursively decomposed into a series of quasi-orthogonal intrinsic mode functions (IMFs), each of which has a relatively local frequency range. Meanwhile, the signal will focus on a smaller number of obtained IMFs after decomposition, and thus the denoised result is able to be obtained by reconstructing these signal-dominant IMFs. Synthetic examples are given to demonstrate the effectiveness of the proposed approach and comparison is made with the complete ensemble empirical mode decomposition, which demonstrates that the VMD algorithm has lower computational cost and better random noise elimination performance. The application of on field seismic data further illustrates the superior performance of our method in both random noise attenuation and the recovery of seismic events.

  2. Research on the Random Shock Vibration Test Based on the Filter-X LMS Adaptive Inverse Control Algorithm

    Directory of Open Access Journals (Sweden)

    Wang Wei

    2016-01-01

    Full Text Available The related theory and algorithm of adaptive inverse control were presented through the research which pointed out the adaptive inverse control strategy could effectively eliminate the noise influence on the system control. Proposed using a frequency domain filter-X LMS adaptive inverse control algorithm, and the control algorithm was applied to the two-exciter hydraulic vibration test system of random shock vibration control process and summarized the process of the adaptive inverse control strategies in the realization of the random shock vibration test. The self-closed-loop and field test show that using the frequency-domain filter-X LMS adaptive inverse control algorithm can realize high precision control of random shock vibration test.

  3. Seismic random noise attenuation using shearlet and total generalized variation

    Science.gov (United States)

    Kong, Dehui; Peng, Zhenming

    2015-12-01

    Seismic denoising from a corrupted observation is an important part of seismic data processing which improves the signal-to-noise ratio (SNR) and resolution. In this paper, we present an effective denoising method to attenuate seismic random noise. The method takes advantage of shearlet and total generalized variation (TGV) regularization. Different regularity levels of TGV improve the quality of the final result by suppressing Gibbs artifacts caused by the shearlet. The problem is formulated as mixed constraints in a convex optimization. A Bregman algorithm is proposed to solve the proposed model. Extensive experiments based on one synthetic datum and two post-stack field data are done to compare performance. The results demonstrate that the proposed method provides superior effectiveness and preserve the structure better.

  4. Derivation of an expression for the roundoff noise determinant det (KW)^{1/2} for digital filters

    DEFF Research Database (Denmark)

    Jørsboe, Helge

    1978-01-01

    The minimal roundoff noise in fixed point digital filters is determined by a certain determinant, generally denoted by det(KW)^{1/2}. This determinant may be expressed by the poles and zeros of the filter transfer function H(z). This paper presents a simple and direct derivation of this expression...

  5. Convergence analysis of the Filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible

    NARCIS (Netherlands)

    Fraanje, P.R.; Verhaegen, M.; Doelman, N.J.

    2003-01-01

    The Filtered-U LMS algorithm, proposed by Eriksson for active noise control applications, adapts the coefficients of an infinite-impulse response controller. Conditions for global convergence of the Filtered-U LMS algorithm were presented by Wang and Ren (Signal Processing, 73 (1999) 3) and Mosquera

  6. Optimization through Co-Simulation of Antenna, Bandpass Filter and Low-Noise Amplifier at 6-9 GHz

    OpenAIRE

    Khan, Abbas

    2012-01-01

    Ultra-wide band (UWB) 6-9 GHz antenna, band pass filter and low-noise amplifier (LNA) optimization using co-simulation of the RF front-end. At higher frequencies, carefully conducted design methodologies are required for RF front-end parameter optimization, such as power gain and low noise figure with low power consumption.

  7. Information Theoretically Secure, Enhanced Johnson Noise Based Key Distribution over the Smart Grid with Switched Filters

    Science.gov (United States)

    2013-01-01

    We introduce a protocol with a reconfigurable filter system to create non-overlapping single loops in the smart power grid for the realization of the Kirchhoff-Law-Johnson-(like)-Noise secure key distribution system. The protocol is valid for one-dimensional radial networks (chain-like power line) which are typical of the electricity distribution network between the utility and the customer. The speed of the protocol (the number of steps needed) versus grid size is analyzed. When properly generalized, such a system has the potential to achieve unconditionally secure key distribution over the smart power grid of arbitrary geometrical dimensions. PMID:23936164

  8. Information theoretically secure, enhanced Johnson noise based key distribution over the smart grid with switched filters.

    Directory of Open Access Journals (Sweden)

    Elias Gonzalez

    Full Text Available We introduce a protocol with a reconfigurable filter system to create non-overlapping single loops in the smart power grid for the realization of the Kirchhoff-Law-Johnson-(like-Noise secure key distribution system. The protocol is valid for one-dimensional radial networks (chain-like power line which are typical of the electricity distribution network between the utility and the customer. The speed of the protocol (the number of steps needed versus grid size is analyzed. When properly generalized, such a system has the potential to achieve unconditionally secure key distribution over the smart power grid of arbitrary geometrical dimensions.

  9. Information theoretically secure, enhanced Johnson noise based key distribution over the smart grid with switched filters.

    Science.gov (United States)

    Gonzalez, Elias; Kish, Laszlo B; Balog, Robert S; Enjeti, Prasad

    2013-01-01

    We introduce a protocol with a reconfigurable filter system to create non-overlapping single loops in the smart power grid for the realization of the Kirchhoff-Law-Johnson-(like)-Noise secure key distribution system. The protocol is valid for one-dimensional radial networks (chain-like power line) which are typical of the electricity distribution network between the utility and the customer. The speed of the protocol (the number of steps needed) versus grid size is analyzed. When properly generalized, such a system has the potential to achieve unconditionally secure key distribution over the smart power grid of arbitrary geometrical dimensions.

  10. CT urography in the urinary bladder: To compare excretory phase images using a low noise index and a high noise index with adaptive noise reduction filter

    Energy Technology Data Exchange (ETDEWEB)

    Takeyama, Nobuyuki; Hayashi, Takaki (Dept. of Radiology, Showa Univ. Fujigaoka Hospital, Yokohama (Japan)), email: momiji@mtc.biglobe.ne.jp; Ohgiya, Yoshimitsu (Dept. of Radiology, Showa Univ. School of Medicine, Tokyo (Japan)) (and others)

    2011-07-15

    Background: Although CT urography (CTU) is widely used for the evaluation of the entire urinary tract, the most important drawback is the radiation exposure. Purpose: To evaluate the effect of a noise reduction filter (NRF) using a phantom and to quantitatively and qualitatively compare excretory phase (EP) images using a low noise index (NI) with those using a high NI and postprocessing NRF (pNRF). Material and Methods: Each NI value was defined for a slice thickness of 5 mm, and reconstructed images with a slice thickness of 1.25 mm were assessed. Sixty patients who were at high risk of developing bladder tumors (BT) were divided into two groups according to whether their EP images were obtained using an NI of 9.88 (29 patients; group A) or an NI of 20 and pNRF (31 patients; group B). The CT dose index volume (CTDI{sub vol}) and the contrast-to-noise ratio (CNR) of the bladder with respect to the anterior pelvic fat were compared in both groups. Qualitative assessment of the urinary bladder for image noise, sharpness, streak artifacts, homogeneity, and the conspicuity of polypoid or sessile-shaped BTs with a short-axis diameter greater than 10 mm was performed using a 3-point scale. Results: The phantom study showed noise reduction of approximately 40% and 76% dose reduction between group A and group B. CTDI{sub vol} demonstrated a 73% reduction in group B (4.6 +- 1.1 mGy) compared with group A (16.9 +- 3.4 mGy). The CNR value was not significantly different (P = 0.60) between group A (16.1 +- 5.1) and group B (16.6 +- 7.6). Although group A was superior (P < 0.01) to group B with regard to image noise, other qualitative analyses did not show significant differences. Conclusion: EP images using a high NI and pNRF were quantitatively and qualitatively comparable to those using a low NI, except with regard to image noise

  11. CT urography in the urinary bladder: to compare excretory phase images using a low noise index and a high noise index with adaptive noise reduction filter.

    Science.gov (United States)

    Takeyama, Nobuyuki; Ohgiya, Yoshimitsu; Hayashi, Takaki; Takahashi, Toshiyuki; Yoshiaki, Suzuki; Takasu, Daisuke; Nakashima, Junya; Kato, Kyoichi; Kinebuchi, Yuko; Hashimoto, Toshi; Gokan, Takehiko

    2011-07-01

    Although CT urography (CTU) is widely used for the evaluation of the entire urinary tract, the most important drawback is the radiation exposure. To evaluate the effect of a noise reduction filter (NRF) using a phantom and to quantitatively and qualitatively compare excretory phase (EP) images using a low noise index (NI) with those using a high NI and postprocessing NRF (pNRF). Each NI value was defined for a slice thickness of 5 mm, and reconstructed images with a slice thickness of 1.25 mm were assessed. Sixty patients who were at high risk of developing bladder tumors (BT) were divided into two groups according to whether their EP images were obtained using an NI of 9.88 (29 patients; group A) or an NI of 20 and pNRF (31 patients; group B). The CT dose index volume (CTDI(vol)) and the contrast-to-noise ratio (CNR) of the bladder with respect to the anterior pelvic fat were compared in both groups. Qualitative assessment of the urinary bladder for image noise, sharpness, streak artifacts, homogeneity, and the conspicuity of polypoid or sessile-shaped BTs with a short-axis diameter greater than 10 mm was performed using a 3-point scale. The phantom study showed noise reduction of approximately 40% and 76% dose reduction between group A and group B. CTDI(vol) demonstrated a 73% reduction in group B (4.6 ± 1.1 mGy) compared with group A (16.9 ± 3.4 mGy). The CNR value was not significantly different (P = 0.60) between group A (16.1 ± 5.1) and group B (16.6 ± 7.6). Although group A was superior (P < 0.01) to group B with regard to image noise, other qualitative analyses did not show significant differences. EP images using a high NI and pNRF were quantitatively and qualitatively comparable to those using a low NI, except with regard to image noise.

  12. Compressively Characterizing High-Dimensional Entangled States with Complementary, Random Filtering

    Science.gov (United States)

    2016-06-30

    the same photons. Remarkably, the measure- ment disturbance introduced by the momentum filtering manifests as a small amount of additive noise in the...quantum state; it maps a small amount of momentum information onto the total intensity passing the filter. The measurement disturb- ance of...andR ports of each filter and are connected to a coincidence circuit . The total number of coincident detection events between signal and idler channels

  13. SVD-based optimal filtering for noise reduction in dual microphone hearing aids: a real time implementation and perceptual evaluation.

    Science.gov (United States)

    Maj, Jean-Baptiste; Royackers, Liesbeth; Moonen, Marc; Wouters, Jan

    2005-09-01

    In this paper, the first real-time implementation and perceptual evaluation of a singular value decomposition (SVD)-based optimal filtering technique for noise reduction in a dual microphone behind-the-ear (BTE) hearing aid is presented. This evaluation was carried out for a speech weighted noise and multitalker babble, for single and multiple jammer sound source scenarios. Two basic microphone configurations in the hearing aid were used. The SVD-based optimal filtering technique was compared against an adaptive beamformer, which is known to give significant improvements in speech intelligibility in noisy environment. The optimal filtering technique works without assumptions about a speaker position, unlike the two-stage adaptive beamformer. However this strategy needs a robust voice activity detector (VAD). A method to improve the performance of the VAD was presented and evaluated physically. By connecting the VAD to the output of the noise reduction algorithms, a good discrimination between the speech-and-noise periods and the noise-only periods of the signals was obtained. The perceptual experiments demonstrated that the SVD-based optimal filtering technique could perform as well as the adaptive beamformer in a single noise source scenario, i.e., the ideal scenario for the latter technique, and could outperform the adaptive beamformer in multiple noise source scenarios.

  14. The effect of sampling noise in ensemble-based Kalman filters

    Science.gov (United States)

    Sacher, William

    Ensemble-based Kalman filters have drawn a lot of attention in the atmospheric and ocean scientific community because of their potential to be used as a data assimilation tool for numerical prediction in a strongly nonlinear context at an affordable cost. However, many studies have noted practical problems in their implementation. Indeed, being Monte-Carlo methods, the useful parameters are estimated from a sample of limited size of independent realizations of the process. As a consequence, the unavoidable sampling noise impacts the quality of the analysis. An idealized perfect model context is considered in which the analytical expression for the analysis accuracy and reliability as a function of the ensemble size is established, from a second-order moment perspective. It is proved that one can analytically explain the general tendency for ensemble-based Kalman filters to underestimate, on average, the analysis variance and therefore the likeliness for these filters to diverge. Performance of alternative methods, designed to reduce or eliminate sampling error effects, such as the double ensemble Kalman filter or covariance inflation are also analytically explored. For methods using perturbed observations, it is shown that the covariance inflation is the easiest and least expensive method to obtain the most accurate and reliable analysis. These analytical results agreed well with means over a large number of experiments using a perfect, low-resolution, and quasi-geostrophic barotropic model, in a series of observation system simulation experiments of single analysis cycles as well as in a simulated forecast system. In one-analysis cycle experiments with rank histograms, non-perturbed-observation methods show a lack of reliability regardless of the number of members. For small ensemble sizes, sampling error effects are dominant but have a smaller impact than in the perturbed observation method, making non-perturbed-observation method filters much less subject to

  15. Estimation of time varying system parameters from ambient response using improved Particle-Kalman filter with correlated noise

    Science.gov (United States)

    Sen, Subhamoy; Crinière, Antoine; Mevel, Laurent; Cerou, Frederic; Dumoulin, Jean

    2017-04-01

    Keywords: Parameter estimation; Kalman filter; Particle filter; Particle-Kalman filter; Correlated noise Although Kalman filter (KF) was originally proposed for system control i.e. steering a system as desired by monitoring the system states, its application for parameter estimation problems is widespread because of the excellent similarity between these two apparently different problem types in state space description. In standard Kalman filter, system dynamics is described through the dynamics of certain internal variable, termed as states, evolving over time as defined by an assumed process model, while a measurement model maps these states to measurements. In some parameter estimation problems, the system is replaced by a state space formulation of the dynamic model with parameters appended in the unobserved states and collectively observed through the response measurements. Filtering based parameter estimation problems are thus inherently nonlinear due to the required nonlinear mapping of parameters to the corresponding observations. Being a linear estimator, Kalman Filter (KF) cannot be employed for such nonlinear system estimation and alternative filtering algorithms (eg. Particle filter) are therefore generally used. However, being model based, these filters optimally estimate the parameters of a quasi-static model of the real dynamic system. Consequently, any time variation in the system dynamics may completely diverge the estimation yielding a false or infeasible solution. By decoupling the estimation of system states and parameters, and applying concurrent filtering strategy that attempts conditional estimation of states based on parameters and vice versa, time varying systems can be estimated. This article attempts to combine KF with Particle filter (PF) and apply them for estimation of states and system parameters respectively on a system with correlated noise in process and measurement. The idea is to nest a bank of linear KFs for state estimation

  16. Performance analysis of a low power low noise tunable band pass filter for multiband RF front end

    Science.gov (United States)

    Manjula, J.; Malarvizhi, S.

    2014-03-01

    This paper presents a low power tunable active inductor and RF band pass filter suitable for multiband RF front end circuits. The active inductor circuit uses the PMOS cascode structure as the negative transconductor of a gyrator to reduce the noise voltage. Also, this structure provides possible negative resistance to reduce the inductor loss with wide inductive bandwidth and high resonance frequency. The RF band pass filter is realized using the proposed active inductor with suitable input and output buffer stages. The tuning of the center frequency for multiband operation is achieved through the controllable current source. The designed active inductor and RF band pass filter are simulated in 180 nm and 45 nm CMOS process using the Synopsys HSPICE simulation tool and their performances are compared. The parameters, such as resonance frequency, tuning capability, noise and power dissipation, are analyzed for these CMOS technologies and discussed. The design of a third order band pass filter using an active inductor is also presented.

  17. Error Bounds Due to Random Noise in Cylindrical Near-Field Measurements

    OpenAIRE

    Romeu Robert, Jordi; Jofre Roca, Lluís

    1991-01-01

    The far field errors due to near field random noise are statistically bounded when performing cylindrical near to far field transform. In this communication, the far field noise variance it is expressed as a function of the measurement parameters and the near field noise variance. Peer Reviewed

  18. Multi-filter transport of intensity equation solver with equalized noise sensitivity.

    Science.gov (United States)

    Martinez-Carranza, J; Falaggis, K; Kozacki, T

    2015-09-07

    Phase retrieval based on the Transport of Intensity Equation (TIE) has shown to be a powerful tool to obtain the phase of complex fields. Recently, it has been proven that the performance of TIE techniques can be improved when using unequally spaced measurement planes. In this paper, an algorithm is presented that recovers accurately the phase of a complex objects from a set of intensity measurements obtained at unequal plane separations. This technique employs multiple band-pass filters in the frequency domain of the axial derivative and uses these specific frequency bands for the calculation of the final phase. This provides highest accuracy for TIE based phase recovery giving minimal phase error for a given set of measurement planes. Moreover, because each of these band-pass filters has a distinct sensitivity to noise, a new plane selection strategy is derived that equalizes the error contribution of all frequency bands. It is shown that this new separation strategy allows controlling the final error of the retrieved phase without using a priori information of the object. This is an advantage compared to previous optimum phase retrieval techniques. In order to show the stability and robustness of this new technique, we present the numerical simulations.

  19. Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise

    Science.gov (United States)

    Burge, Johannes

    2017-01-01

    Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA’s compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA’s unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and

  20. MicroRNA filters Hox temporal transcription noise to confer boundary formation in the spinal cord

    Science.gov (United States)

    Li, Chung-Jung; Hong, Tian; Tung, Ying-Tsen; Yen, Ya-Ping; Hsu, Ho-Chiang; Lu, Ya-Lin; Chang, Mien; Nie, Qing; Chen, Jun-An

    2017-03-01

    The initial rostrocaudal patterning of the neural tube leads to differential expression of Hox genes that contribute to the specification of motor neuron (MN) subtype identity. Although several 3' Hox mRNAs are expressed in progenitors in a noisy manner, these Hox proteins are not expressed in the progenitors and only become detectable in postmitotic MNs. MicroRNA biogenesis impairment leads to precocious expression and propagates the noise of Hoxa5 at the protein level, resulting in an imprecise Hoxa5-Hoxc8 boundary. Here we uncover, using in silico simulation, two feed-forward Hox-miRNA loops accounting for the precocious and noisy Hoxa5 expression, as well as an ill-defined boundary phenotype in Dicer mutants. Finally, we identify mir-27 as a major regulator coordinating the temporal delay and spatial boundary of Hox protein expression. Our results provide a novel trans Hox-miRNA circuit filtering transcription noise and controlling the timing of protein expression to confer robust individual MN identity.

  1. Separating precipitation and evapotranspiration from noise – a new filter routine for high-resolution lysimeter data

    Directory of Open Access Journals (Sweden)

    A. Peters

    2014-03-01

    Full Text Available Weighing lysimeters yield the most precise and realistic measures for evapotranspiration (ET and precipitation (P, which are of great importance for many questions regarding soil and atmospheric sciences. An increase or a decrease of the system mass (lysimeter plus seepage indicates P or ET. These real mass changes of the lysimeter system have to be separated from measurement noise (e.g., caused by wind. A promising approach to filter noisy lysimeter data is (i to introduce a smoothing routine, like a moving average with a certain averaging window, w, and then (ii to apply a certain threshold value, δ, accounting for measurement accuracy, separating significant from insignificant weight changes. Thus, two filter parameters are used, namely w and δ. In particular, the time-variable noise due to wind as well as strong signals due to heavy precipitation pose challenges for such noise-reduction algorithms. If w is too small, data noise might be interpreted as real system changes. If w is too wide, small weight changes in short time intervals might be disregarded. The same applies to too small or too large values for δ. Application of constant w and δ leads either to unnecessary losses of accuracy or to faulty data due to noise. The aim of this paper is to solve this problem with a new filter routine that is appropriate for any event, ranging from smooth evaporation to strong wind and heavy precipitation. Therefore, the new routine uses adaptive w and δ in dependence on signal strength and noise (AWAT – adaptive window and adaptive threshold filter. The AWAT filter, a moving-average filter and the Savitzky–Golay filter with constant w and δ were applied to real lysimeter data comprising the above-mentioned events. The AWAT filter was the only filter that could handle the data of all events very well. A sensitivity study shows that the magnitude of the maximum threshold value has practically no influence on the results; thus only the maximum

  2. Random wavelet transforms, algebraic geometric coding, and their applications in signal compression and de-noising

    Energy Technology Data Exchange (ETDEWEB)

    Bieleck, T.; Song, L.M.; Yau, S.S.T. [Univ. of Illinois, Chicago, IL (United States); Kwong, M.K. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    The concepts of random wavelet transforms and discrete random wavelet transforms are introduced. It is shown that these transforms can lead to simultaneous compression and de-noising of signals that have been corrupted with fractional noises. Potential applications of algebraic geometric coding theory to encode the ensuing data are also discussed.

  3. An analysis of noise reduction in variable reluctance motors using pulse position randomization

    Science.gov (United States)

    Smoot, Melissa C.

    1994-05-01

    The design and implementation of a control system to introduce randomization into the control of a variable reluctance motor (VRM) is presented. The goal is to reduce noise generated by radial vibrations of the stator. Motor phase commutation angles are dithered by 1 or 2 mechanical degrees to investigate the effect of randomization on acoustic noise. VRM commutation points are varied using a uniform probability density function and a 4 state Markov chain among other methods. The theory of VRM and inverter operation and a derivation of the major source of acoustic noise are developed. The experimental results show the effects of randomization. Uniform dithering and Markov chain dithering both tend to spread the noise spectrum, reducing peak noise components. No clear evidence is found to determine which is the optimum randomization scheme. The benefit of commutation angle randomization in reducing VRM loudness as perceived by humans is found to be questionable.

  4. Real-time Kalman filter implementation for active feedforward control of time-varying broadband noise and vibrations

    NARCIS (Netherlands)

    van Ophem, S.; Berkhoff, Arthur P.; Sas, P; Jonckheere, S.; Moens, D.

    2012-01-01

    Tracking behavior and the rate of convergence are critical properties in active noise control applications with time-varying disturbance spectra. As compared to the standard filtered-reference Least Mean Square (LMS) algorithm, improved convergence can be obtained with schemes based on

  5. Common-mode noise analysis, modeling and filter design for a phase-shifted full-bridge forward converter

    DEFF Research Database (Denmark)

    Makda, Ishtiyaq Ahmed; Nymand, Morten

    2015-01-01

    This paper presents the common-mode noise analysis and modeling of a phase-shifted full-bridge forward converter. The common-mode noise source due to a transformer inter-winding capacitance is considered for the case of study. The generated common-mode noise voltage-source in a converter is analy......This paper presents the common-mode noise analysis and modeling of a phase-shifted full-bridge forward converter. The common-mode noise source due to a transformer inter-winding capacitance is considered for the case of study. The generated common-mode noise voltage-source in a converter...... is analytically determined, which then leads to a common-mode noise modeling of a phase-shifted converter. Using a proposed model, common-mode noise-current harmonics are calculated and a fully analytical filter design procedure is presented to comply with the CISPR-11 standard. Finally, a prototype phase-shifted...... forward converter is built to verify the theoretical analysis. This study shows that the primary-to-secondary transformer winding capacitance creates a very significant amount of common-mode noise current in a phase-shifted forward converter....

  6. Slepian simulation of plastic displacement distributions for shear frame excited by filtered Gaussian white noise ground motion

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager; Lazarov, Boyan Stefanov

    2003-01-01

    Application of the Slepian model process concept to obtain approximate plastic displacement distributions of elasto-plastic shear frame oscillators of one or more degrees of freedom has in previous works been for white noise force excitation acting directly on the first floor mass of the shear...... frame. A suitable number of the lower floors has been considered to represent the soil both as a filter of a white noise base rock excitation and as a simplified model for soil structure interaction. In the present paper the Slepian model is applied to obtain plastic displacement distributions...... for a single story shear frame excited by stationary Gaussian ground motion defined by the output of a Clough-Penzien filter with Gaussian white noise input. This is equivalent to considering an artificial three story elasto-plastic shear frame with possible yielding solely in the third column connection...

  7. Diffusion MRI noise mapping using random matrix theory

    Science.gov (United States)

    Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S.

    2016-01-01

    Purpose To estimate the spatially varying noise map using a redundant magnitude MR series. Methods We exploit redundancy in non-Gaussian multi-directional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices. The bulk of PCA eigenvalues, arising due to noise, is described by the universal Marchenko-Pastur distribution, parameterized by the noise level. This allows us to estimate noise level in a local neighborhood based on the singular value decomposition of a matrix combining neighborhood voxels and diffusion directions. Results We present a model-independent local noise mapping method capable of estimating noise level down to about 1% error. In contrast to current state-of-the art techniques, the resultant noise maps do not show artifactual anatomical features that often reflect physiological noise, the presence of sharp edges, or a lack of adequate a priori knowledge of the expected form of MR signal. Conclusions Simulations and experiments show that typical diffusion MRI data exhibit sufficient redundancy that enables accurate, precise, and robust estimation of the local noise level by interpreting the PCA eigenspectrum in terms of the Marchenko-Pastur distribution. PMID:26599599

  8. Low-dose MDCT urography: feasibility study of low-tube-voltage technique and adaptive noise reduction filter.

    Science.gov (United States)

    Yanaga, Yumi; Awai, Kazuo; Funama, Yoshinori; Nakaura, Takeshi; Hirai, Toshinori; Roux, Sebastien; Yamashita, Yasuyuki

    2009-09-01

    The purpose of this study was to investigate the feasibility of performance of MDCT urography with low tube voltage and an adaptive noise reduction filter. Thirty-one patients underwent excretory phase (300 seconds after administration of 100 mL of iopamidol) 40-MDCT of the urinary tract at 120 and 80 kVp. The 80-kVp images were postprocessed with an adaptive noise reduction filter. Using a 3-point scale for homogeneity of the urinary tract and sharpness of contour, streak artifacts, and overall image quality, two radiologists evaluated coronal multiplanar reconstruction images generated from 120-kVp, unfiltered 80-kVp, and filtered 80-kVp images. Attenuation values of the abdominal aorta, renal pelvis, renal cortex, psoas muscle, vertebral body, and retroperitoneal fat and image noise of the psoas muscle were measured. The effective radiation dose was estimated for each patient. At visual evaluation of images of the upper urinary tract, the quality of filtered 80-kVp images was comparable with that of 120-kVp images. At evaluation of images of the lower urinary tract, however, filtered 80-kVp images were of inferior quality. Except for those of fat tissue, attenuation values were significantly higher on 80-kVp than on 120-kVp images (paired Student's t test, p urography is feasible with a low-tube-voltage technique and an adaptive noise reduction filter. The technique allows reduction in radiation dose without marked degradation of image quality and can be used in clinical assessment of the renal collecting system and upper ureter. For evaluation of the pelvic ureter and urinary bladder, however, image quality is not sufficient, and a compensatory increase in tube current may be necessary.

  9. Comparison of edge detection techniques for M7 subtype Leukemic cell in terms of noise filters and threshold value

    Directory of Open Access Journals (Sweden)

    Abdul Salam Afifah Salmi

    2017-01-01

    Full Text Available This paper will focus on the study and identifying various threshold values for two commonly used edge detection techniques, which are Sobel and Canny Edge detection. The idea is to determine which values are apt in giving accurate results in identifying a particular leukemic cell. In addition, evaluating suitability of edge detectors are also essential as feature extraction of the cell depends greatly on image segmentation (edge detection. Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML is chosen due to its diagnosing which were found lacking. Next, for an enhancement in image quality, noise filters are applied. Hence, by comparing images with no filter, median and average filter, useful information can be acquired. Each threshold value is fixed with value 0, 0.25 and 0.5. From the investigation found, without any filter, Canny with a threshold value of 0.5 yields the best result.

  10. Filtering out the noise: evaluating the impact of noise and sound reduction strategies on sleep quality for ICU patients

    Science.gov (United States)

    Bosma, Karen J; Ranieri, V Marco

    2009-01-01

    The review article by Xie and colleagues examines the impact of noise and noise reduction strategies on sleep quality for critically ill patients. Evaluating the impact of noise on sleep quality is challenging, as it must be measured relative to other factors that may be more or less disruptive to patients' sleep. Such factors may be difficult for patients, observers, and polysomnogram interpreters to identify, due to our limited understanding of the causes of sleep disruption in the critically ill, as well as the challenges in recording and quantifying sleep stages and sleep fragmentation in the intensive care unit. Furthermore, most research in this field has focused on noise level, whereas acousticians typically evaluate additional parameters such as noise spectrum and reverberation time. The authors highlight the disparate results and limitations of existing studies, including the lack of attention to other acoustic parameters besides sound level, and the combined effects of different sleep disturbing factors. PMID:19519943

  11. Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

    Science.gov (United States)

    Abrecht, David G.; Schwantes, Jon M.; Kukkadapu, Ravi K.; McDonald, Benjamin S.; Eiden, Gregory C.; Sweet, Lucas E.

    2015-02-01

    Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mössbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the Mössbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.

  12. Diffusion MRI noise mapping using random matrix theory

    National Research Council Canada - National Science Library

    Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S

    2016-01-01

    .... Methods We exploit redundancy in non-Gaussian distributed multidirectional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices...

  13. Fluorescence microscopy image noise reduction using a stochastically-connected random field model.

    Science.gov (United States)

    Haider, S A; Cameron, A; Siva, P; Lui, D; Shafiee, M J; Boroomand, A; Haider, N; Wong, A

    2016-02-17

    Fluorescence microscopy is an essential part of a biologist's toolkit, allowing assaying of many parameters like subcellular localization of proteins, changes in cytoskeletal dynamics, protein-protein interactions, and the concentration of specific cellular ions. A fundamental challenge with using fluorescence microscopy is the presence of noise. This study introduces a novel approach to reducing noise in fluorescence microscopy images. The noise reduction problem is posed as a Maximum A Posteriori estimation problem, and solved using a novel random field model called stochastically-connected random field (SRF), which combines random graph and field theory. Experimental results using synthetic and real fluorescence microscopy data show the proposed approach achieving strong noise reduction performance when compared to several other noise reduction algorithms, using quantitative metrics. The proposed SRF approach was able to achieve strong performance in terms of signal-to-noise ratio in the synthetic results, high signal to noise ratio and contrast to noise ratio in the real fluorescence microscopy data results, and was able to maintain cell structure and subtle details while reducing background and intra-cellular noise.

  14. Large Signal Excitation Measurement Techniques for Random Telegraph Signal Noise in MOSFETs

    NARCIS (Netherlands)

    Hoekstra, E.

    2005-01-01

    This paper introduces large signal excitation measurement techniques to analyze random telegraph signal (RTS) noise originating from oxide-traps in MOSFETs. The paper concentrates on the trap-occupancy, which relates directly to the generated noise. The proposed measurement technique makes

  15. Large Signal Excitation Measurement Techniques for Random Telegraph Signal Noise in MOSFETs

    NARCIS (Netherlands)

    Hoekstra, E.; Kolhatkar, J.S.; van der Wel, A.P.; Salm, Cora; Klumperink, Eric A.M.

    2005-01-01

    This paper introduces large signal excitation measurement techniques to analyze Random Telegraph Signal (RTS) noise originating from oxide-traps in MOSFETs. The paper concentrates on the trap-occupancy, which relates directly to the generated noise. The proposed measurement technique makes

  16. Random-Resistor-Random-Temperature Kirchhoff-Law-Johnson-Noise (RRRT-KLJN Key Exchange

    Directory of Open Access Journals (Sweden)

    Kish Laszlo B.

    2016-03-01

    Full Text Available We introduce two new Kirchhoff-law-Johnson-noise (KLJN secure key distribution schemes which are generalizations of the original KLJN scheme. The first of these, the Random-Resistor (RR- KLJN scheme, uses random resistors with values chosen from a quasi-continuum set. It is well-known since the creation of the KLJN concept that such a system could work in cryptography, because Alice and Bob can calculate the unknown resistance value from measurements, but the RR-KLJN system has not been addressed in prior publications since it was considered impractical. The reason for discussing it now is the second scheme, the Random Resistor Random Temperature (RRRT- KLJN key exchange, inspired by a recent paper of Vadai, Mingesz and Gingl, wherein security was shown to be maintained at non-zero power flow. In the RRRT-KLJN secure key exchange scheme, both the resistances and their temperatures are continuum random variables. We prove that the security of the RRRT-KLJN scheme can prevail at a non-zero power flow, and thus the physical law guaranteeing security is not the Second Law of Thermodynamics but the Fluctuation-Dissipation Theorem. Alice and Bob know their own resistances and temperatures and can calculate the resistance and temperature values at the other end of the communication channel from measured voltage, current and power-flow data in the wire. However, Eve cannot determine these values because, for her, there are four unknown quantities while she can set up only three equations. The RRRT-KLJN scheme has several advantages and makes all former attacks on the KLJN scheme invalid or incomplete.

  17. Evaluation of the effectiveness of Gaussian filtering in distinguishing punctate synaptic signals from background noise during image analysis.

    Science.gov (United States)

    Iwabuchi, Sadahiro; Kakazu, Yasuhiro; Koh, Jin-Young; Harata, N Charles

    2014-02-15

    Images in biomedical imaging research are often affected by non-specific background noise. This poses a serious problem when the noise overlaps with specific signals to be quantified, e.g. for their number and intensity. A simple and effective means of removing background noise is to prepare a filtered image that closely reflects background noise and to subtract it from the original unfiltered image. This approach is in common use, but its effectiveness in identifying and quantifying synaptic puncta has not been characterized in detail. We report on our assessment of the effectiveness of isolating punctate signals from diffusely distributed background noise using one variant of this approach, "Difference of Gaussian(s) (DoG)" which is based on a Gaussian filter. We evaluated immunocytochemically stained, cultured mouse hippocampal neurons as an example, and provided the rationale for choosing specific parameter values for individual steps in detecting glutamatergic nerve terminals. The intensity and width of the detected puncta were proportional to those obtained by manual fitting of two-dimensional Gaussian functions to the local information in the original image. DoG was compared with the rolling-ball method, using biological data and numerical simulations. Both methods removed background noise, but differed slightly with respect to their efficiency in discriminating neighboring peaks, as well as their susceptibility to high-frequency noise and variability in object size. DoG will be useful in detecting punctate signals, once its characteristics are examined quantitatively by experimenters. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Quasi-Coherent Noise Jamming to LFM Radar Based on Pseudo-random Sequence Phase-modulation

    Directory of Open Access Journals (Sweden)

    N. Tai

    2015-12-01

    Full Text Available A novel quasi-coherent noise jamming method is proposed against linear frequency modulation (LFM signal and pulse compression radar. Based on the structure of digital radio frequency memory (DRFM, the jamming signal is acquired by the pseudo-random sequence phase-modulation of sampled radar signal. The characteristic of jamming signal in time domain and frequency domain is analyzed in detail. Results of ambiguity function indicate that the blanket jamming effect along the range direction will be formed when jamming signal passes through the matched filter. By flexible controlling the parameters of interrupted-sampling pulse and pseudo-random sequence, different covering distances and jamming effects will be achieved. When the jamming power is equivalent, this jamming obtains higher process gain compared with non-coherent jamming. The jamming signal enhances the detection threshold and the real target avoids being detected. Simulation results and circuit engineering implementation validate that the jamming signal covers real target effectively.

  19. 3D noise power spectrum applied on clinical MDCT scanners: effects of reconstruction algorithms and reconstruction filters

    Science.gov (United States)

    Miéville, Frédéric A.; Bolard, Gregory; Benkreira, Mohamed; Ayestaran, Paul; Gudinchet, François; Bochud, François; Verdun, Francis R.

    2011-03-01

    The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters. A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed. In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements. The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

  20. Analogies between colored Lévy noise and random channel approach to disordered kinetics

    Science.gov (United States)

    Vlad, Marcel O.; Velarde, Manuel G.; Ross, John

    2004-02-01

    We point out some interesting analogies between colored Lévy noise and the random channel approach to disordered kinetics. These analogies are due to the fact that the probability density of the Lévy noise source plays a similar role as the probability density of rate coefficients in disordered kinetics. Although the equations for the two approaches are not identical, the analogies can be used for deriving new, useful results for both problems. The random channel approach makes it possible to generalize the fractional Uhlenbeck-Ornstein processes (FUO) for space- and time-dependent colored noise. We describe the properties of colored noise in terms of characteristic functionals, which are evaluated by using a generalization of Huber's approach to complex relaxation [Phys. Rev. B 31, 6070 (1985)]. We start out by investigating the properties of symmetrical white noise and then define the Lévy colored noise in terms of a Langevin equation with a Lévy white noise source. We derive exact analytical expressions for the various characteristic functionals, which characterize the noise, and a functional fractional Fokker-Planck equation for the probability density functional of the noise at a given moment in time. Second, by making an analogy between the theory of colored noise and the random channel approach to disordered kinetics, we derive fractional equations for the evolution of the probability densities of the random rate coefficients in disordered kinetics. These equations serve as a basis for developing methods for the evaluation of the statistical properties of the random rate coefficients from experimental data. Special attention is paid to the analysis of systems for which the observed kinetic curves can be described by linear or nonlinear stretched exponential kinetics.

  1. On the nice behavior of the Gaussian projection filter with small observation noise

    NARCIS (Netherlands)

    Brigo, D.

    1995-01-01

    When projecting on the manifold of Gaussian densities, the projection filter has been shown to be equal to a McShane-Fisk-Stratonovich (MFS) derivation of the Gaussian assumed density filter. Starting from this point, we study the asymptotic behaviour of the Gaussian projection filter when the

  2. A multi-resolution filtered-x LMS algorithm based on discrete wavelet transform for active noise control

    Science.gov (United States)

    Qiu, Z.; Lee, C.-M.; Xu, Z. H.; Sui, L. N.

    2016-01-01

    We have developed a new active control algorithm based on discrete wavelet transform (DWT) for both stationary and non-stationary noise control. First, the Mallat pyramidal algorithm is introduced to implement the DWT, which can decompose the reference signal into several sub-bands with multi-resolution and provides a perfect reconstruction (PR) procedure. To reduce the extra computational complexity introduced by DWT, an efficient strategy is proposed that updates the adaptive filter coefficients in the frequency domainDeepthi B.B using a fast Fourier transform (FFT). Based on the reference noise source, a 'Haar' wavelet is employed and by decomposing the noise signal into two sub-band (3-band), the proposed DWT-FFT-based FXLMS (DWT-FFT-FXLMS) algorithm has greatly reduced complexity and a better convergence performance compared to a time domain filtered-x least mean square (TD-FXLMS) algorithm. As a result of the outstanding time-frequency characteristics of wavelet analysis, the proposed DWT-FFT-FXLMS algorithm can effectively cancel both stationary and non-stationary noise, whereas the frequency domain FXLMS (FD-FXLMS) algorithm cannot approach this point.

  3. Garner Valley Vibroseis Data Processing Using Time-Frequency Filtering Techniques to Remove Unwanted Harmonics and External Noise

    Science.gov (United States)

    Lord, N. E.; Wang, H. F.; Fratta, D.; Lancelle, C.; Chalari, A.

    2015-12-01

    Time-frequency filtering techniques can greatly improve data quality when combined with frequency swept seismic sources (vibroseis) recorded by seismic arrays by removing unwanted source harmonics or external noise sources (e.g., cultural or ambient noise). A source synchronous filter (SSF) is a time-frequency filter which only passes a specified width frequency band centered on the time varying frequency of the seismic source. A source delay filter (SDF) is a time-frequency filter which only passes those frequencies from the source within a specified delay time range. Both of these time-frequency filters operate on the uncorrelated vibroseis data and allow separate analysis of the source fundamental frequency and each harmonic. In either technique, the time-frequency function of the source can be captured from the source encoder or specified using two or more time-frequency points. SSF and SDF were both used in the processing of the vibroseis data collected in the September 2013 seismic experiment conducted at the NEES@UCSB Garner Valley field site. Three vibroseis sources were used: a 45 kN shear shaker, a 450 N portable mass shaker, and a 26 kN vibroseis truck. Seismic signals from these sources were recorded by two lines of 1 and 3 component accelerometers and geophones, and the Silixa Ltd's intelligent Distributed Acoustic Sensing (iDASTM ) system connected to 762 m of trenched fiber optical cable in a larger rectangular area. SSF and SDF improved vibroseis data quality, simplified data interpretation, and allowed new analysis techniques. This research is part of the larger DOE's PoroTomo project (URL: http://geoscience.wisc.edu/feigl/porotomo).

  4. Research on adaptive filtering method for electrostatic signals

    Science.gov (United States)

    Xu, Hongke; Pang, Yue; Yi, Yingmin

    2017-05-01

    The signal will be inevitably mixed with various types of noise in the process of transmission, which causes the distortion of information in different degree, in order to obtain accurate information, it's an important work to suppress random noise in the digital signal processing system. This paper mainly studies the adaptive filtering method, using LMS algorithm in adaptive filter (Least mean square LMS algorithm), when the filter starts reading the electrostatic signal, it also can estimate the statistical characteristics of electrostatic signal, adaptive adjust its filter parameters, filtering the electrostatic signal on time, attain the maximum noise suppression, to avoid distortion of information, and to achieve optimal filtering.

  5. Median filters as a tool to determine dark noise thresholds in high resolution smartphone image sensors for scientific imaging

    Science.gov (United States)

    Igoe, Damien P.; Parisi, Alfio V.; Amar, Abdurazaq; Rummenie, Katherine J.

    2018-01-01

    An evaluation of the use of median filters in the reduction of dark noise in smartphone high resolution image sensors is presented. The Sony Xperia Z1 employed has a maximum image sensor resolution of 20.7 Mpixels, with each pixel having a side length of just over 1 μm. Due to the large number of photosites, this provides an image sensor with very high sensitivity but also makes them prone to noise effects such as hot-pixels. Similar to earlier research with older models of smartphone, no appreciable temperature effects were observed in the overall average pixel values for images taken in ambient temperatures between 5 °C and 25 °C. In this research, hot-pixels are defined as pixels with intensities above a specific threshold. The threshold is determined using the distribution of pixel values of a set of images with uniform statistical properties associated with the application of median-filters of increasing size. An image with uniform statistics was employed as a training set from 124 dark images, and the threshold was determined to be 9 digital numbers (DN). The threshold remained constant for multiple resolutions and did not appreciably change even after a year of extensive field use and exposure to solar ultraviolet radiation. Although the temperature effects' uniformity masked an increase in hot-pixel occurrences, the total number of occurrences represented less than 0.1% of the total image. Hot-pixels were removed by applying a median filter, with an optimum filter size of 7 × 7; similar trends were observed for four additional smartphone image sensors used for validation. Hot-pixels were also reduced by decreasing image resolution. The method outlined in this research provides a methodology to characterise the dark noise behavior of high resolution image sensors for use in scientific investigations, especially as pixel sizes decrease.

  6. Reduction of randomness in seismic noise as a short-term precursor to a volcanic eruption.

    Science.gov (United States)

    Glynn, C C; Konstantinou, K I

    2016-11-24

    Ambient seismic noise is characterized by randomness incurred by the random position and strength of the noise sources as well as the heterogeneous properties of the medium through which it propagates. Here we use ambient noise data recorded prior to the 1996 Gjálp eruption in Iceland in order to show that a reduction of noise randomness can be a clear short-term precursor to volcanic activity. The eruption was preceded on 29 September 1996 by a Mw ~5.6 earthquake that occurred in the caldera rim of the Bárdarbunga volcano. A significant reduction of randomness started occurring 8 days before the earthquake and 10 days before the onset of the eruption. This reduction was observed even at stations more than 100 km away from the eruption site. Randomness increased to its previous levels 160 minutes after the Bárdarbunga earthquake, during which time aftershocks migrated from the Bárdarbunga caldera to a site near the Gjálp eruption fissure. We attribute this precursory reduction of randomness to the lack of higher frequencies (>1 Hz) in the noise wavefield caused by high absorption losses as hot magma ascended in the upper crust.

  7. Random telegraphic voltage noise due to thermal bi-stability in a superconducting weak link

    Science.gov (United States)

    Biswas, Sourav; Kumar, Nikhil; Winkelmann, C. B.; Courtois, Herve; Gupta, Anjan K.

    2016-05-01

    We investigated the random telegraphic voltage noise signal in the hysteretic bi-stable state of a superconducting weak link device. Fluctuation induced random switching between zero voltage state and non-zero-voltage state gives rise to a random telegraphic voltage signal in time domain. This telegraphic noise is used to find the mean lifetime of each of the two states. The mean life time in the zero voltage state is found to decrease with increasing bias current while that of resistive state increases and thus the two cross at certain bias current. We qualitatively discuss this observed switching behavior as arising from the bi-stable nature.

  8. Information Encoding on a Pseudo Random Noise Radar Waveform

    Science.gov (United States)

    2013-03-01

    antenna under test AWG arbitrary waveform generator AWGN additive white Gaussian noise BPSK binary phase shift keying CDMA code division multiple...focused on the orthogonal frequency-division multiplexing (OFDM) and code division multiple access ( CDMA ) waveforms. The Ohio State University has...components into a single unit allows for a more mobile compact platform. The plan is diagrammed in Figure 3.5. Figure 3.5: Planned modifications to

  9. Identification and Filtering of Uncharacteristic Noise in the CMS Hadron Calorimeter

    CERN Document Server

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D'Enterria, D; Everaerts, P; Gomez Ceballos, G; Hahn, K A; Harris, P; Jaditz, S; Kim, Y; Klute, M; Lee, Y J; Li, W; Loizides, C; Ma, T; Miller, M; Nahn, S; Paus, C; Roland, C; Roland, G; Rudolph, M; Stephans, G; Sumorok, K; Sung, K; Vaurynovich, S; Wenger, E A; Wyslouch, B; Xie, S; Yilmaz, Y; Yoon, A S; Bailleux, D; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dolgopolov, A; Dudero, P R; Egeland, R; Franzoni, G; Haupt, J; Inyakin, A; Klapoetke, K; Kubota, Y; Mans, J; Mirman, N; Petyt, D; Rekovic, V; Rusack, R; Schroeder, M; Singovsky, A; Zhang, J; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Sonnek, P; Summers, D; Bloom, K; Bockelman, B; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Lundstedt, C; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Iashvili, I; Kharchilava, A; Kumar, A; Smith, K; Strang, M; Alverson, G; Barberis, E; Boeriu, O; Eulisse, G; Govi, G; McCauley, T; Musienko, Y; Muzaffar, S; Osborne, I; Paul, T; Reucroft, S; Swain, J; Taylor, L; Tuura, L; Anastassov, A; Gobbi, B; Kubik, A; Ofierzynski, R A; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolberg, T; Lannon, K; Lynch, S; Marinelli, N; Morse, D M; Ruchti, R; Slaunwhite, J; Warchol, J; Wayne, M; Bylsma, B; Durkin, L S; Gilmore, J; Gu, J; Killewald, P; Ling, T Y; Williams, G; Adam, N; Berry, E; Elmer, P; Garmash, A; Gerbaudo, D; Halyo, V; Hunt, A; Jones, J; Laird, E; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Stickland, D; Tully, C; Werner, J S; Wildish, T; Xie, Z; Zuranski, A; Acosta, J G; Bonnett Del Alamo, M; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Ramirez Vargas, J E; Santacruz, N; Zatzerklyany, A; Alagoz, E; Antillon, E; Barnes, V E; Bolla, G; Bortoletto, D; Everett, A; Garfinkel, A F; Gecse, Z; Gutay, L; Ippolito, N; Jones, M; Koybasi, O; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Sedov, A; Shipsey, I; Yoo, H D; Zheng, Y; Jindal, P; Parashar, N; Cuplov, V; Ecklund, K M; Geurts, F J M; Liu, J H; Maronde, D; Matveev, M; Padley, B P; Redjimi, R; Roberts, J; Sabbatini, L; Tumanov, A; Betchart, B; Bodek, A; Budd, H; Chung, Y S; de Barbaro, P; Demina, R; Flacher, H; Gotra, Y; Harel, A; Korjenevski, S; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Demortier, L; Goulianos, K; Hatakeyama, K; Lungu, G; Mesropian, C; Yan, M; Atramentov, O; Bartz, E; Gershtein, Y; Halkiadakis, E; Hits, D; Lath, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Watts, T L; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Aurisano, A; Eusebi, R; Golyash, A; Gurrola, A; Kamon, T; Nguyen, C N; Pivarski, J; Safonov, A; Sengupta, S; Toback, D; Weinberger, M; Akchurin, N; Berntzon, L; Gumus, K; Jeong, C; Kim, H; Lee, S W; Popescu, S; Roh, Y; Sill, A; Volobouev, I; Washington, E; Wigmans, R; Yazgan, E; Engh, D; Florez, C; Johns, W; Pathak, S; Sheldon, P; Andelin, D; Arenton, M W; Balazs, M; Boutle, S; Buehler, M; Conetti, S; Cox, B; Hirosky, R; Ledovskoy, A; Neu, C; Phillips II, D; Ronquest, M; Yohay, R; Gollapinni, S; Gunthoti, K; Harr, R; Karchin, P E; Mattson, M; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Crotty, I; Dasu, S; Dutta, S; Efron, J; Feyzi, F; Flood, K; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Jaworski, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Loveless, R; Magrans de Abril, M; Mohapatra, A; Ott, G; Polese, G; Reeder, D; Savin, A; Smith, W H; Sourkov, A; Swanson, J; Weinberg, M; Wenman, D; Wensveen, M; White, A

    2010-01-01

    Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation.

  10. A method for total noise removal in digital holography based on enhanced grouping and sparsity enhancement filtering

    Science.gov (United States)

    Bianco, Vittorio; Memmolo, Pasquale; Paturzo, Melania; Finizio, Andrea; Ferraro, Pietro

    2017-06-01

    In digital holography (DH), the coherent nature of the employed light sources severely degrades the holographic reconstructions due to a mixture of speckle and incoherent additive noise. These can affect both the visual quality in holographic imaging and display, and the accuracy of quantitative phase-contrast reconstructions. Typically, the noise problem is tackled by reducing the illumination coherence, thus the most intuitive way involves the recording of multiple uncorrelated holograms to be incoherently combined. This framework is known as Multi-Look DH (MLDH). However, single shot recordings are highly desirable in DH, and numerical methods are required to go beyond the improvement bound of ML techniques. Among the existing image processing methods, the 3D Block Matching filtering (BM3D) has shown the best performance. Here we present the MLDH-BM3D, a method specifically suitable to filter DH images that combines the two aforementioned strategies to overcome their respective limitations. We demonstrate the effectiveness of this framework in three different experimental situations, i.e. reconstructions of single wavelength holograms and color holograms in the visible region and the challenging case of the Infrared Radiation Digital Holography (IRDH) reconstructions, where a very severe noise degradation occurs.

  11. Detectability and image quality metrics based on robust statistics: following non-linear, noise-reduction filters

    Science.gov (United States)

    Tkaczyk, J. Eric; Haneda, Eri; Palma, Giovanni; Iordache, Razvan; Klausz, Remy; Garayt, Mathieu; Carton, Ann-Katherine

    2014-03-01

    Non-linear image processing and reconstruction algorithms that reduced noise while preserving edge detail are currently being evaluated in medical imaging research literature. We have implemented a robust statistics analysis of four widely utilized methods. This work demonstrates consistent trends in filter impact by which such non-linear algorithms can be evaluated. We calculate observer model test statistics and propose metrics based on measured non-Gaussian distributions that can serve as image quality measures analogous to SDNR and detectability. The filter algorithms that vary significantly in their approach to noise reduction include median (MD), bilateral (BL), anisotropic diffusion (AD) and total-variance regularization (TV). It is shown that the detectability of objects limited by Poisson noise is not significantly improved after filtration. There is no benefit to the fraction of correct responses in repeated n-alternate forced choice experiments, for n=2-25. Nonetheless, multi-pixel objects with contrast above the detectability threshold appear visually to benefit from non-linear processing algorithms. In such cases, calculations on highly repeated trials show increased separation of the object-level histogram from the background-level distribution. Increased conspicuity is objectively characterized by robust statistical measures of distribution separation.

  12. Noise

    Science.gov (United States)

    Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...

  13. A Flexible Speech Distortion Weighted Multi-Channel Wiener Filter for Noise Reduction in Hearing Aids

    DEFF Research Database (Denmark)

    Ngo, K.; Moonen, M.; Jensen, Søren Holdt

    2011-01-01

    -only and a speech+noise state, a solution is introduced that allows for a more flexible trade-off between noise reduction and speech distortion. Experimental results with hearing aid scenarios demonstrate that the proposed SDW-MWF incorporating the flexible weighting factor improves the signal...

  14. Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error.

    Science.gov (United States)

    Kiani, M A; Sim, K S; Nia, M E; Tso, C P

    2015-05-01

    A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

  15. Noise Filter Studies for CMS Forward Hadron Calorimeter (HF) Between Old and New PMT's Using Data in 2012

    CERN Document Server

    Dumanoglu, Isa; Gurpinar, Emine; Kunori, Shuichi; Lezki, Samet; Tali, Bayram

    2016-01-01

    During the data taking before 2012 some abnormal events which have higher signals than expected were observed. Most of these were due to muons. When a muon hits the PMT glass window it creates a huge signal. To eliminate this kind of events 24 old HF PMTs (Hamamatsu R7525) in HF Minus at iphi 43 (corresponds to one sector) were replaced with new multi anode PMTs (Hamamatsu multi anode R7600) which have thin glass windows. These new PMTs were installed and tested in H2 test beam area in 2009 [1]. To check whether these new PMTs perform better than the old ones data taken in 2012 were analyzed using various predefined noise filters. Noisy rechits percentage was found to be around 6-7 \\% for the new PMTs while it varies between 29-66 \\% for the old PMTs for various trigger selections and for HFLongShortFilter after an energy cut of 500GeV [2].

  16. Emergence of deterministic Green's functions from noise generated by finite random sources.

    Science.gov (United States)

    Godin, Oleg A

    2009-12-01

    Two-point correlation functions of sufficiently diffuse wave fields generated by uncorrelated random sources are known to approximate deterministic Green's functions between the two points. This property is utilized increasingly for passive imaging and remote sensing of the environment. Here we show that the relation between the Green's functions and the noise cross-correlation function holds under much less restrictive conditions than previously thought. It can even hold when ambient noise sources have correlation ranges large compared to the wavelength. Admissible correlation ranges are limited from above by the size of the Fresnel zone at wave propagation between the points where noise cross correlation is evaluated.

  17. Adaptive spatial filtering improves speech reception in noise while preserving binaural cues.

    Science.gov (United States)

    Bissmeyer, Susan R S; Goldsworthy, Raymond L

    2017-09-01

    Hearing loss greatly reduces an individual's ability to comprehend speech in the presence of background noise. Over the past decades, numerous signal-processing algorithms have been developed to improve speech reception in these situations for cochlear implant and hearing aid users. One challenge is to reduce background noise while not introducing interaural distortion that would degrade binaural hearing. The present study evaluates a noise reduction algorithm, referred to as binaural Fennec, that was designed to improve speech reception in background noise while preserving binaural cues. Speech reception thresholds were measured for normal-hearing listeners in a simulated environment with target speech generated in front of the listener and background noise originating 90° to the right of the listener. Lateralization thresholds were also measured in the presence of background noise. These measures were conducted in anechoic and reverberant environments. Results indicate that the algorithm improved speech reception thresholds, even in highly reverberant environments. Results indicate that the algorithm also improved lateralization thresholds for the anechoic environment while not affecting lateralization thresholds for the reverberant environments. These results provide clear evidence that this algorithm can improve speech reception in background noise while preserving binaural cues used to lateralize sound.

  18. Detection of random signals in dependent Gaussian noise

    CERN Document Server

    Gualtierotti, Antonio F

    2015-01-01

    The book presents the necessary mathematical basis to obtain and rigorously use likelihoods for detection problems with Gaussian noise. To facilitate comprehension the text is divided into three broad areas –  reproducing kernel Hilbert spaces, Cramér-Hida representations and stochastic calculus – for which a somewhat different approach was used than in their usual stand-alone context. One main applicable result of the book involves arriving at a general solution to the canonical detection problem for active sonar in a reverberation-limited environment. Nonetheless, the general problems dealt with in the text also provide a useful framework for discussing other current research areas, such as wavelet decompositions, neural networks, and higher order spectral analysis. The structure of the book, with the exposition presenting as many details as necessary, was chosen to serve both those readers who are chiefly interested in the results and those who want to learn the material from scratch. Hence, the text...

  19. Pathological Brain Detection Using Weiner Filtering, 2D-Discrete Wavelet Transform, Probabilistic PCA, and Random Subspace Ensemble Classifier

    Directory of Open Access Journals (Sweden)

    Debesh Jha

    2017-01-01

    Full Text Available Accurate diagnosis of pathological brain images is important for patient care, particularly in the early phase of the disease. Although numerous studies have used machine-learning techniques for the computer-aided diagnosis (CAD of pathological brain, previous methods encountered challenges in terms of the diagnostic efficiency owing to deficiencies in the choice of proper filtering techniques, neuroimaging biomarkers, and limited learning models. Magnetic resonance imaging (MRI is capable of providing enhanced information regarding the soft tissues, and therefore MR images are included in the proposed approach. In this study, we propose a new model that includes Wiener filtering for noise reduction, 2D-discrete wavelet transform (2D-DWT for feature extraction, probabilistic principal component analysis (PPCA for dimensionality reduction, and a random subspace ensemble (RSE classifier along with the K-nearest neighbors (KNN algorithm as a base classifier to classify brain images as pathological or normal ones. The proposed methods provide a significant improvement in classification results when compared to other studies. Based on 5×5 cross-validation (CV, the proposed method outperforms 21 state-of-the-art algorithms in terms of classification accuracy, sensitivity, and specificity for all four datasets used in the study.

  20. An LCMV Filter for Single-Channel Noise Cancellation and Reduction in the Time Domain

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

    2013-01-01

    In this paper, we consider a recent class of optimal rectangular fil- tering matrices for single-channel speech enhancement. This class of filters exploits the fact that the dimension of the signal subspace is lower than that of the full space. Then, extra degrees of freedom in the filters...... signal-to-interference ratio. This is showed for both synthetic and real speech signals....

  1. Removing Spikes While Preserving Data and Noise using Wavelet Filter Banks

    Data.gov (United States)

    National Aeronautics and Space Administration — Many diagnostic datasets suffer from the adverse effects of spikes that are embedded in data and noise. For example, this is true for electrical power system data...

  2. Random Access for Machine-Type Communication based on Bloom Filtering

    DEFF Research Database (Denmark)

    Pratas, Nuno; Stefanovic, Cedomir; Madueño, Germán Corrales

    2016-01-01

    We present a random access method inspired on Bloom filters that is suited for Machine-Type Communications (MTC). Each accessing device sends a signature during the contention process. A signature is constructed using the Bloom filtering method and contains information on the device identity...... utilizes the system resources more efficiently and achieves similar or lower latency of connection establishment in case of synchronous arrivals, compared to the variant of the LTE-A access protocol that is optimized for MTC traffic. A dividend of the proposed method is that allows the base station (BS...

  3. Kalman Filtering with Real-Time Applications

    CERN Document Server

    Chui, Charles K

    2009-01-01

    Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering.

  4. A First Approach to Design Mobility Function and Noise Filter in VLC System Utilizing Low-cost Analog Circuits

    Directory of Open Access Journals (Sweden)

    Syifaul Fuada

    2017-07-01

    Full Text Available Visible Light Communication (VLC as one of wireless technology must be able to offer a good capability as mobile communication system. The signal will be faded when the distance and angle of LED to photo-detector become higher at a certain distance. Other problem at VLC system is light interference noise which is caused by flicker effect from other light sources such as incandescent, fluorescent, DC-lamp (i.e. flashlight and the sunlight. Each of lights have specific carried signal characteristics and it can influences the VLC system. In this paper we offer design of mobile VLC system based on analog domain. We use Automatic Gain Controller (AGC circuit using commercially available IC and it will be placed at analog front-end receiver side. AGC can self-adjust its gain according to the input signal amplitude.  We also design analog filter to eliminate all interferences noise spectrum which is existed under 50 KHz. We design both circuits, analog filter and AGC in VLC receiver system with low-cost. The test data are obtained through the simulation and achieved good results in ideal condition.

  5. Wireless rake-receiver using adaptive filter with a family of partial update algorithms in noise cancellation applications

    Science.gov (United States)

    Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Aldhaibani, Jaafar A.; Salman, M. K.; Abdullah, Farah Salwani

    2015-05-01

    For high data rate propagation in wireless ultra-wideband (UWB) communication systems, the inter-symbol interference (ISI), multiple-access interference (MAI), and multiple-users interference (MUI) are influencing the performance of the wireless systems. In this paper, the rake-receiver was presented with the spread signal by direct sequence spread spectrum (DS-SS) technique. The adaptive rake-receiver structure was shown with adjusting the receiver tap weights using least mean squares (LMS), normalized least mean squares (NLMS), and affine projection algorithms (APA) to support the weak signals by noise cancellation and mitigate the interferences. To minimize the data convergence speed and to reduce the computational complexity by the previous algorithms, a well-known approach of partial-updates (PU) adaptive filters were employed with algorithms, such as sequential-partial, periodic-partial, M-max-partial, and selective-partial updates (SPU) in the proposed system. The simulation results of bit error rate (BER) versus signal-to-noise ratio (SNR) are illustrated to show the performance of partial-update algorithms that have nearly comparable performance with the full update adaptive filters. Furthermore, the SPU-partial has closed performance to the full-NLMS and full-APA while the M-max-partial has closed performance to the full-LMS updates algorithms.

  6. Integrated WiFi/PDR/Smartphone Using an Adaptive System Noise Extended Kalman Filter Algorithm for Indoor Localization

    Directory of Open Access Journals (Sweden)

    Xin Li

    2016-02-01

    Full Text Available Wireless signal strength is susceptible to the phenomena of interference, jumping, and instability, which often appear in the positioning results based on Wi-Fi field strength fingerprint database technology for indoor positioning. Therefore, a Wi-Fi and PDR (pedestrian dead reckoning real-time fusion scheme is proposed in this paper to perform fusing calculation by adaptively determining the dynamic noise of a filtering system according to pedestrian movement (straight or turning, which can effectively restrain the jumping or accumulation phenomena of wireless positioning and the PDR error accumulation problem. Wi-Fi fingerprint matching typically requires a quite high computational burden: To reduce the computational complexity of this step, the affinity propagation clustering algorithm is adopted to cluster the fingerprint database and integrate the information of the position domain and signal domain of respective points. An experiment performed in a fourth-floor corridor at the School of Environment and Spatial Informatics, China University of Mining and Technology, shows that the traverse points of the clustered positioning system decrease by 65%–80%, which greatly improves the time efficiency. In terms of positioning accuracy, the average error is 4.09 m through the Wi-Fi positioning method. However, the positioning error can be reduced to 2.32 m after integration of the PDR algorithm with the adaptive noise extended Kalman filter (EKF.

  7. Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter

    Directory of Open Access Journals (Sweden)

    Álvaro Moreno

    2014-08-01

    Full Text Available Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted local regression filter (LOESS and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG, smoothing spline (SSP, Interpolation for Data Reconstruction (IDR and adaptive Savitzky-Golay (ASG. This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| < 8%; rRMSE < 20% reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal

  8. Co-design method for dual-band low-noise amplifier and band-pass filter

    Science.gov (United States)

    Ma, Runbo; Zhang, Wenmei; Han, Guorui; Li, Li; Chen, Xinwei; Han, Liping

    2012-04-01

    A co-design method for the dual-band low-noise amplifier (LNA) and band-pass filter (BPF) is presented in this study. The dual-band BPF and LNA are designed separately by the traditional method first. In order to reduce the circuit, the dual-band matching networks (MNs) of the LNA and BPF are combined into the dual-band matching-filter. The validity is verified by a sample of 1.57/2.4 GHz LNA-filter after the co-design. The measured S21, NF and BW3 dB are 18.6 dB, 1.98 dB and 0.22 GHz at 1.57 GHz, and 15.2 dB, 1.95 dB and 0.3 GHz at 2.31 GHz, respectively. The results indicate that the co-design and cascade versions have same performance, but the co-design version cuts down the number of the passive components by nearly half.

  9. Design optimisation of powers-of-two FIR filter using self-organising random immigrants GA

    Science.gov (United States)

    Chandra, Abhijit; Chattopadhyay, Sudipta

    2015-01-01

    In this communication, we propose a novel design strategy of multiplier-less low-pass finite impulse response (FIR) filter with the aid of a recent evolutionary optimisation technique, known as the self-organising random immigrants genetic algorithm. Individual impulse response coefficients of the proposed filter have been encoded as sum of signed powers-of-two. During the formulation of the cost function for the optimisation algorithm, both the frequency response characteristic and the hardware cost of the discrete coefficient FIR filter have been considered. The role of crossover probability of the optimisation technique has been evaluated on the overall performance of the proposed strategy. For this purpose, the convergence characteristic of the optimisation technique has been included in the simulation results. In our analysis, two design examples of different specifications have been taken into account. In order to substantiate the efficiency of our proposed structure, a number of state-of-the-art design strategies of multiplier-less FIR filter have also been included in this article for the purpose of comparison. Critical analysis of the result unambiguously establishes the usefulness of our proposed approach for the hardware efficient design of digital filter.

  10. Evaluation of a Cubature Kalman Filtering-Based Phase Unwrapping Method for Differential Interferograms with High Noise in Coal Mining Areas.

    Science.gov (United States)

    Liu, Wanli; Bian, Zhengfu; Liu, Zhenguo; Zhang, Qiuzhao

    2015-07-06

    Differential interferometric synthetic aperture radar has been shown to be effective for monitoring subsidence in coal mining areas. Phase unwrapping can have a dramatic influence on the monitoring result. In this paper, a filtering-based phase unwrapping algorithm in combination with path-following is introduced to unwrap differential interferograms with high noise in mining areas. It can perform simultaneous noise filtering and phase unwrapping so that the pre-filtering steps can be omitted, thus usually retaining more details and improving the detectable deformation. For the method, the nonlinear measurement model of phase unwrapping is processed using a simplified Cubature Kalman filtering, which is an effective and efficient tool used in many nonlinear fields. Three case studies are designed to evaluate the performance of the method. In Case 1, two tests are designed to evaluate the performance of the method under different factors including the number of multi-looks and path-guiding indexes. The result demonstrates that the unwrapped results are sensitive to the number of multi-looks and that the Fisher Distance is the most suitable path-guiding index for our study. Two case studies are then designed to evaluate the feasibility of the proposed phase unwrapping method based on Cubature Kalman filtering. The results indicate that, compared with the popular Minimum Cost Flow method, the Cubature Kalman filtering-based phase unwrapping can achieve promising results without pre-filtering and is an appropriate method for coal mining areas with high noise.

  11. Evaluation of a Cubature Kalman Filtering-Based Phase Unwrapping Method for Differential Interferograms with High Noise in Coal Mining Areas

    Directory of Open Access Journals (Sweden)

    Wanli Liu

    2015-07-01

    Full Text Available Differential interferometric synthetic aperture radar has been shown to be effective for monitoring subsidence in coal mining areas. Phase unwrapping can have a dramatic influence on the monitoring result. In this paper, a filtering-based phase unwrapping algorithm in combination with path-following is introduced to unwrap differential interferograms with high noise in mining areas. It can perform simultaneous noise filtering and phase unwrapping so that the pre-filtering steps can be omitted, thus usually retaining more details and improving the detectable deformation. For the method, the nonlinear measurement model of phase unwrapping is processed using a simplified Cubature Kalman filtering, which is an effective and efficient tool used in many nonlinear fields. Three case studies are designed to evaluate the performance of the method. In Case 1, two tests are designed to evaluate the performance of the method under different factors including the number of multi-looks and path-guiding indexes. The result demonstrates that the unwrapped results are sensitive to the number of multi-looks and that the Fisher Distance is the most suitable path-guiding index for our study. Two case studies are then designed to evaluate the feasibility of the proposed phase unwrapping method based on Cubature Kalman filtering. The results indicate that, compared with the popular Minimum Cost Flow method, the Cubature Kalman filtering-based phase unwrapping can achieve promising results without pre-filtering and is an appropriate method for coal mining areas with high noise.

  12. A rapidly converging filtered-error algorithm for multichannel active noise control

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; Nijsse, G.

    2006-01-01

    In this paper, a multichannel adaptive control algorithm is described which has good convergence properties while having relatively small computational complexity. This complexity is similar to that of the filtered-error algorithm. In order to obtain these properties, the algorithm is based on a

  13. Utilização de filtro de transformada de fourier para a minimização de ruídos em sinais analíticos Utilization of fourier transform filter for noise minimization in analytical signals

    Directory of Open Access Journals (Sweden)

    Eduardo O. Cerqueira

    2000-10-01

    Full Text Available Instrumental data always present some noise. The analytical data information and instrumental noise generally has different frequencies. Thus is possible to remove the noise using a digital filter based on Fourier transform and inverse Fourier transform. This procedure enhance the signal/noise ratio and consecutively increase the detection limits on instrumental analysis. The basic principle of Fourier transform filter with modifications implemented to improve its performance is presented. A numerical example, as well as a real voltammetric example are showed to demonstrate the Fourier transform filter implementation. The programs to perform the Fourier transform filter, in Matlab and Visual Basic languages, are included as appendices

  14. An automatic approach towards modal parameter estimation for high-rise buildings of multicomponent signals under ambient excitations via filter-free Random Decrement Technique

    Science.gov (United States)

    Nasser, Fatima; Li, Zhongyang; Martin, Nadine; Gueguen, Philippe

    2016-03-01

    This paper proposes an automatic modal analysis approach for signals of high-rise buildings recorded under real-world ambient excitations. The fact of working over such type of signals is faced with several challenges: the time-domain convolution between the system impulse response and the seismic noise, the existence of several components, the presence of closely-spaced frequency modes, with high additive noises, and low, exponential and damped amplitudes. The proposed approach handles these challenges simultaneously without the need for a user intervention. It is based on a filter-free Random Decrement Technique to estimate the free-decay response, followed by a spectral-based method for a rough modal estimate and finalized by a Maximum-Likelihood Estimation process to refine the modal estimates. Each of these processes is responsible to tackle one or more of the aforementioned challenges in the aim to provide an automatic and moreover a reliable modal analysis of the studied signals.

  15. Fractional White-Noise Limit and Paraxial Approximation for Waves in Random Media

    Science.gov (United States)

    Gomez, Christophe; Pinaud, Olivier

    2017-12-01

    This work is devoted to the asymptotic analysis of high frequency wave propagation in random media with long-range dependence. We are interested in two asymptotic regimes, that we investigate simultaneously: the paraxial approximation, where the wave is collimated and propagates along a privileged direction of propagation, and the white-noise limit, where random fluctuations in the background are well approximated in a statistical sense by a fractional white noise. The fractional nature of the fluctuations is reminiscent of the long-range correlations in the underlying random medium. A typical physical setting is laser beam propagation in turbulent atmosphere. Starting from the high frequency wave equation with fast non-Gaussian random oscillations in the velocity field, we derive the fractional Itô-Schrödinger equation, that is, a Schrödinger equation with potential equal to a fractional white noise. The proof involves a fine analysis of the backscattering and of the coupling between the propagating and evanescent modes. Because of the long-range dependence, classical diffusion-approximation theorems for equations with random coefficients do not apply, and we therefore use moment techniques to study the convergence.

  16. Fractional White-Noise Limit and Paraxial Approximation for Waves in Random Media

    Science.gov (United States)

    Gomez, Christophe; Pinaud, Olivier

    2017-07-01

    This work is devoted to the asymptotic analysis of high frequency wave propagation in random media with long-range dependence. We are interested in two asymptotic regimes, that we investigate simultaneously: the paraxial approximation, where the wave is collimated and propagates along a privileged direction of propagation, and the white-noise limit, where random fluctuations in the background are well approximated in a statistical sense by a fractional white noise. The fractional nature of the fluctuations is reminiscent of the long-range correlations in the underlying random medium. A typical physical setting is laser beam propagation in turbulent atmosphere. Starting from the high frequency wave equation with fast non-Gaussian random oscillations in the velocity field, we derive the fractional Itô-Schrödinger equation, that is, a Schrödinger equation with potential equal to a fractional white noise. The proof involves a fine analysis of the backscattering and of the coupling between the propagating and evanescent modes. Because of the long-range dependence, classical diffusion-approximation theorems for equations with random coefficients do not apply, and we therefore use moment techniques to study the convergence.

  17. Random telegraph noise analysis in AlOx/WOy resistive switching memories

    Science.gov (United States)

    Zhang, Ye; Wu, Huaqiang; Wu, Minghao; Deng, Ning; Yu, Zhiping; Zhang, Jinyu; Qian, He

    2014-03-01

    In this Letter, the origins of current fluctuations of Al/AlOx/WOy/W bilayer resistive random access memory (RRAM) devices are investigated through detailed noise analysis. Random telegraph noise (RTN) measurements were performed on RRAMs with three different resistance states. An obvious RTN signal with 40.7% amplitude difference was found at high resistance state, and the trapping/de-trapping process leading to the RTN signal was studied in detail by extracting the trap energy from energy diagram. For median and low resistance states, the resistance fluctuations were 34.0% and 0.3%, respectively. To further study the RTN characteristics, the normalized power spectral density (PSD) was analyzed. It is found that, for one dominant-trap caused RTN phenomena, the normalized noise PSD behaves as 1/f 2 on the high resistance state; while for median and low resistance states, the noise follows 1/f rule, suggesting that the current fluctuations are associated with the envelop of multiple RTNs caused by traps located near/in the conductive filament. Based on the noise analyses in time and frequency domains, a conduction mechanism is proposed to describe the trap effects on the current fluctuations of different resistance states.

  18. DS/LPI autocorrelation detection in noise plus random-tone interference

    Science.gov (United States)

    Hinedi, Sami; Polydoros, Andreas

    1990-01-01

    An analysis is presented of a frequency-noncoherent, two-lag autocorrelation statistic for the wideband detection of random binary phase-shift keying (BPSK) signals in noise plus random multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values contrary to an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. The purpose of the paper is to promote the real-time autocorrelation domain and its samples (lags) as a viable approach for detecting random signals in dense environments.

  19. Composite correlation filter for O-ring detection in stationary colored noise

    Science.gov (United States)

    Hassebrook, Laurence G.

    2009-04-01

    O-rings are regularly replaced in aircraft and if they are not replaced or if they are installed improperly, they can result in catastrophic failure of the aircraft. It is critical that the o-rings be packaged correctly to avoid mistakes made by technicians during routine maintenance. For this reason, fines may be imposed on the o-ring manufacturer if the o-rings are packaged incorrectly. That is, a single o-ring must be packaged and labeled properly. No o-rings or more than one o-ring per package is not acceptable. We present an industrial inspection system based on real-time composite correlation filtering that has successfully solved this problem in spite of opaque paper o-ring packages. We present the system design including the composite filter design.

  20. R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.

    Science.gov (United States)

    Yang, Jing; Jin, Qi-Yu; Zhang, Biao; Shen, Hong-Bin

    2016-08-15

    Inter-residue contacts in proteins dictate the topology of protein structures. They are crucial for protein folding and structural stability. Accurate prediction of residue contacts especially for long-range contacts is important to the quality of ab inito structure modeling since they can enforce strong restraints to structure assembly. In this paper, we present a new Residue-Residue Contact predictor called R2C that combines machine learning-based and correlated mutation analysis-based methods, together with a two-dimensional Gaussian noise filter to enhance the long-range residue contact prediction. Our results show that the outputs from the machine learning-based method are concentrated with better performance on short-range contacts; while for correlated mutation analysis-based approach, the predictions are widespread with higher accuracy on long-range contacts. An effective query-driven dynamic fusion strategy proposed here takes full advantages of the two different methods, resulting in an impressive overall accuracy improvement. We also show that the contact map directly from the prediction model contains the interesting Gaussian noise, which has not been discovered before. Different from recent studies that tried to further enhance the quality of contact map by removing its transitive noise, we designed a new two-dimensional Gaussian noise filter, which was especially helpful for reinforcing the long-range residue contact prediction. Tested on recent CASP10/11 datasets, the overall top L/5 accuracy of our final R2C predictor is 17.6%/15.5% higher than the pure machine learning-based method and 7.8%/8.3% higher than the correlated mutation analysis-based approach for the long-range residue contact prediction. http://www.csbio.sjtu.edu.cn/bioinf/R2C/Contact:hbshen@sjtu.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Tracking random walk of individual domain walls in cylindrical nanomagnets with resistance noise.

    Science.gov (United States)

    Singh, Amrita; Mukhopadhyay, Soumik; Ghosh, Arindam

    2010-08-06

    The stochasticity of domain-wall (DW) motion in magnetic nanowires has been probed by measuring slow fluctuations, or noise, in electrical resistance at small magnetic fields. By controlled injection of DWs into isolated cylindrical nanowires of nickel, we have been able to track the motion of the DWs between the electrical leads by discrete steps in the resistance. Closer inspection of the time dependence of noise reveals a diffusive random walk of the DWs with a universal kinetic exponent. Our experiments outline a method with which electrical resistance is able to detect the kinetic state of the DWs inside the nanowires, which can be useful in DW-based memory designs.

  2. Kalman filtering with real-time applications

    CERN Document Server

    Chui, Charles K

    2017-01-01

    This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help de...

  3. Random Number Simulations Reveal How Random Noise Affects the Measurements and Graphical Portrayals of Self-Assessed Competency

    Directory of Open Access Journals (Sweden)

    Edward Nuhfer

    2016-01-01

    Full Text Available Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x vs. (x scatterplots; (y minus x vs. (x column graphs aggregated as quantiles; line charts that display data aggregated as quantiles; and some histograms. Graphical conventions that generate minimal artifacts include scatterplots with a best-fit line that depict (y vs. (x measures (self-assessed competence vs. measured competence plotted by individual participant scores, and (y vs. (x scatterplots of collective average measures of all participants plotted item-by-item. This last graphic convention attenuates noise and improves the definition of the signal. To provide relevant comparisons across varied graphical conventions, we use a single dataset derived from paired measures of 1154 participants' self-assessed competence and demonstrated competence in science literacy. Our results show that different numerical approaches employed in investigating and describing self-assessment accuracy are not equally valid. By modeling this dataset with random numbers, we show how recognizing the varied expressions of randomness in self-assessment data can improve the validity of numeracy-based descriptions of self-assessment.

  4. Identification of optimal mask size parameter for noise filtering in 99mTc-methylene diphosphonate bone scintigraphy images.

    Science.gov (United States)

    Pandey, Anil K; Bisht, Chandan S; Sharma, Param D; ArunRaj, Sreedharan Thankarajan; Taywade, Sameer; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

    2017-11-01

    Tc-methylene diphosphonate (Tc-MDP) bone scintigraphy images have limited number of counts per pixel. A noise filtering method based on local statistics of the image produces better results than a linear filter. However, the mask size has a significant effect on image quality. In this study, we have identified the optimal mask size that yields a good smooth bone scan image. Forty four bone scan images were processed using mask sizes 3, 5, 7, 9, 11, 13, and 15 pixels. The input and processed images were reviewed in two steps. In the first step, the images were inspected and the mask sizes that produced images with significant loss of clinical details in comparison with the input image were excluded. In the second step, the image quality of the 40 sets of images (each set had input image, and its corresponding three processed images with 3, 5, and 7-pixel masks) was assessed by two nuclear medicine physicians. They selected one good smooth image from each set of images. The image quality was also assessed quantitatively with a line profile. Fisher's exact test was used to find statistically significant differences in image quality processed with 5 and 7-pixel mask at a 5% cut-off. A statistically significant difference was found between the image quality processed with 5 and 7-pixel mask at P=0.00528. The identified optimal mask size to produce a good smooth image was found to be 7 pixels. The best mask size for the John-Sen Lee filter was found to be 7×7 pixels, which yielded Tc-methylene diphosphonate bone scan images with the highest acceptable smoothness.

  5. Effect of Acute Noise Exposure on Salivary Cortisol: A Randomized Controlled Trial.

    Science.gov (United States)

    Pouryaghoub, Gholamreza; Mehrdad, Ramin; Valipouri, Alireza

    2016-10-01

    Cardiovascular adverse effects are interesting aspects of occupational noise exposure. One possible mechanism of these effects is an alternation in hypothalamic-pituitary-adrenal axis. Our aim was to measure salivary cortisol response to relatively high-intensity noise exposure in a controlled randomized trial study. We exposed 50 male volunteers to 90 dBA noise for 20 minutes and compared their level of salivary cortisol with 50 non-exposed controls. Salivary samples obtained before and after exposure. Before intervention means (SD) salivary cortisol level were 3.24 (0.47)ng/ml and 3.25 (0.41)ng/ml for exposed and non-exposed groups respectively. Mean salivary cortisol level increased to 4.17 ng/mlafter intervention in exposure group. This increment was statistically significant (P=0.00). Mean salivary cortisol level of the non-exposed group had statistically non-significant decrement after this period (0.2 ng/ml). The difference between salivary cortisol level of non-exposed and exposed groups after the intervention was statistically significant. Noise exposure may affect the hypothalamic-pituitary-adrenal axis activity, and this may be one of the mechanisms of noise exposure cardiovascular effects.

  6. Ambient awareness: From random noise to digital closeness in online social networks

    OpenAIRE

    Levordashka, Ana; Utz, Sonja

    2016-01-01

    Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empiricall...

  7. A method for noninvasive on-line secondary path modeling for the filtered-X LMS algorithm for active control of periodic noise

    Science.gov (United States)

    Kim, Benjamin Jung

    A novel method for noninvasive on-line secondary path modeling for the filtered-X LMS algorithm is proposed for the active control of periodic noise. Previous noninvasive algorithms have utilized iterative search methods that have proven unsuccessful in delivering sufficiently accurate secondary path models for use by the filtered-X LMS-based control system, especially in time-varying systems, resulting in poor performance and instability. The proposed method, based in the frequency domain, uses the concept of linear independence of two equations/two unknowns to arrive at the secondary path estimate. Linear independence of the two equations is achieved by adjusting the control filter output via the filter coefficients prior to the acquisition of the second set of data corresponding to the second equation. The proposed method is tested on a unique "sound-free" system designed and built specifically for the validation of active noise control algorithms. A summing junction circuit simulates the interference between the primary and secondary disturbances while a computer housing a manually adjustable filter provides a time-varying secondary path; signal generators provide the reference signal. Sinusoidal and dual-frequency signals are used to validate the proposed method. In order to demonstrate the ability of the proposed secondary path modeler to track system changes, tests are conducted where the frequencies are shifted and also where the secondary path is evolving. The secondary path estimates are then compared to the correct estimates ascertained using an LMS-based adaptive filter. The results reflect a simple and elegant secondary path modeling algorithm that provides estimates of unprecedented accuracy for time-varying systems. This accuracy in turn allows for stable operation of the filtered-X LMS-based control filter and thus reliable noise cancellation performance.

  8. Observation of phase noise reduction in photonically synthesized sub-THz signals using a passively mode-locked laser diode and highly selective optical filtering

    DEFF Research Database (Denmark)

    Criado, A. R.; Acedo, P.; Carpintero, G.

    2012-01-01

    A Continuous Wave (CW) sub-THz photonic synthesis setup based on a single Passively Mode-Locked Laser Diode (PMLLD) acting as a monolithic Optical Frequency Comb Generator (OFCG) and highly selective optical filtering has been implemented to evaluate the phase noise performance of the generated sub...

  9. Active random noise control using adaptive learning rate neural networks with an immune feedback law

    Science.gov (United States)

    Sasaki, Minoru; Kuribayashi, Takumi; Ito, Satoshi

    2005-12-01

    In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. In the proposed method, because of the immune feedback law change a learning rate of the neural networks individually and adaptively, it is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks with the immune feedback law. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

  10. Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method

    Directory of Open Access Journals (Sweden)

    Katagiri Fumiaki

    2008-11-01

    Full Text Available Abstract Background Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC analysis has been used for this purpose, but it tends to remove small features as well as random noise. Results We interpreted the PCs as a mere signal-rich coordinate system and sorted the squared PC-coordinates of each row in descending order. The sorted squared PC-coordinates were compared with the distribution of the ordered squared random noise, and PC-coordinates for insignificant contributions were treated as random noise and nullified. The processed data were transformed back to the initial coordinates as noise-reduced data. To increase the sensitivity of signal capture and reduce the effects of stochastic noise, this procedure was applied to multiple small subsets of rows randomly sampled from a large data set, and the results corresponding to each row of the data set from multiple subsets were averaged. We call this procedure Row-specific, Sorted PRincipal component-guided Noise Reduction (RSPR-NR. Robust performance of RSPR-NR, measured by noise reduction and retention of small features, was demonstrated using simulated data sets. Furthermore, when applied to an actual expression profile data set, RSPR-NR preferentially increased the correlations between genes that share the same Gene Ontology terms, strongly suggesting reduction of random noise in the data set. Conclusion RSPR-NR is a robust random noise reduction method that retains small features well. It should be useful in improving the quality of large biological data sets.

  11. Bayesian filtering in spiking neural networks: noise, adaptation, and multisensory integration.

    Science.gov (United States)

    Bobrowski, Omer; Meir, Ron; Eldar, Yonina C

    2009-05-01

    A key requirement facing organisms acting in uncertain dynamic environments is the real-time estimation and prediction of environmental states, based on which effective actions can be selected. While it is becoming evident that organisms employ exact or approximate Bayesian statistical calculations for these purposes, it is far less clear how these putative computations are implemented by neural networks in a strictly dynamic setting. In this work, we make use of rigorous mathematical results from the theory of continuous time point process filtering and show how optimal real-time state estimation and prediction may be implemented in a general setting using simple recurrent neural networks. The framework is applicable to many situations of common interest, including noisy observations, non-Poisson spike trains (incorporating adaptation), multisensory integration, and state prediction. The optimal network properties are shown to relate to the statistical structure of the environment, and the benefits of adaptation are studied and explicitly demonstrated. Finally, we recover several existing results as appropriate limits of our general setting.

  12. Steering quantum-memory-assisted entropic uncertainty under unital and nonunital noises via filtering operations

    Science.gov (United States)

    Huang, Ai-Jun; Shi, Jia-Dong; Wang, Dong; Ye, Liu

    2017-02-01

    In this work, we investigate the dynamic features of the entropic uncertainty for two incompatible measurements under local unital and nonunital channels. Herein, we choose Pauli operators σ _x and σ _z as a pair of observables of interest measuring on particle A, and the uncertainty can be predicted when particle A is entangled with quantum memory B. We explore the dynamics of the uncertainty for the measurement under local unitary (phase-damping) and nonunitary (amplitude-damping) channels, respectively. Remarkably, we derive the entropic uncertainty relation under three different kinds of measurements of Pauli-observable pair under various realistic noisy environments; it has been found that the entropic uncertainty has the same tendency of its evolution during the AD and PD channel when we choose σ _x and σ _y measurement. Besides, we find out that the entropic uncertainty will have an optimal value if one chooses σ _x and σ _z as the measurement incompatibility, comparing with others. Furthermore, in order to reduce the entropic uncertainty in noisy environment, we propose an effective strategy to steer the amount by means of implementing a filtering operation on the particle under the two types of channels, respectively. It turns out that this operation can greatly reduce the entropic uncertainty by modulation of the operation strength. Thus, our investigations might offer an insight into the dynamics and steering of the entropic uncertainty in an open system.

  13. Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform

    Directory of Open Access Journals (Sweden)

    Biao Hu

    2017-04-01

    Full Text Available While most filtering approaches based on random finite sets have focused on improving performance, in this paper, we argue that computation times are very important in order to enable real-time applications such as pedestrian detection. Towards this goal, this paper investigates the use of OpenCL to accelerate the computation of random finite set-based Bayesian filtering in a heterogeneous system. In detail, we developed an efficient and fully-functional pedestrian-tracking system implementation, which can run under real-time constraints, meanwhile offering decent tracking accuracy. An extensive evaluation analysis was carried out to ensure the fulfillment of sufficient accuracy requirements. This was followed by extensive profiling analysis to spot the potential bottlenecks in terms of execution performance, which were then targeted to come up with an OpenCL accelerated application. Video-throughput improvements from roughly 15 fps to 100 fps (6× were observed on average while processing typical MOT benchmark videos. Moreover, the worst-case frame processing yielded an 18× advantage from nearly 2 fps to 36 fps, thereby comfortably meeting the real-time constraints. Our implementation is released as open-source code.

  14. Effects of a leukocyte depleting arterial line filter on perioperative morbidity in patients undergoing cardiac surgery: a controlled randomized trial.

    Science.gov (United States)

    Leal-Noval, Santiago R; Amaya, Rosario; Herruzo, Angel; Hernández, Ana; Ordóñez, Antonio; Marín-Niebla, Ana; Camacho, Pedro

    2005-10-01

    Activated leukocytes may increase morbidity in cardiac surgery. The objective of this study is to investigate the influence on morbidity of leukocyte-depleting blood filters placed into the arterial line of cardiopulmonary bypass circuits. Simple, blind, prospective, randomized and controlled clinical trial carried out in a cardiac surgery ICU at a university center. We included 159 consecutive low-risk patients (ie, Parsonnet score < 10) undergoing cardiac surgery who were initially stratified in three risk levels according to the Parsonnet score at admission into the hospital (ie, low, < 4; middle, 4 to 7; and high, 8 to 10). Once stratified, all patients were randomized to undergo cardiopulmonary bypass either with a conventional blood filter or with a leukocyte filter (randomization ratio, 2:1). The outcome variable was morbidity. Patients were considered to have a high morbidity if any of the following clinical situations were present (ie, pulmonary dysfunction, cardiac dysfunction, perioperative infections, postoperative hyperthermia, and hyperdynamic states). The leukocyte filter was used in 52 patients and the conventional filter in 107 patients. The morbidity rate was similar in both groups, but patients with leukocyte filter had a lower incidence of perioperative infections, fever, and hyperdynamic states as compared with patients with the conventional filter. Leukocyte filtration in patients undergoing cardiac surgery with extracorporeal perfusion showed no measurable effects on postoperative morbidity. However, although not statistically significant, a decrease was observed in the rates of perioperative infection, fever, and hyperdynamic states.

  15. Impacts of regular and random noise on the behaviour, growth and development of larval Atlantic cod (Gadus morhua).

    Science.gov (United States)

    Nedelec, Sophie L; Simpson, Stephen D; Morley, Erica L; Nedelec, Brendan; Radford, Andrew N

    2015-10-22

    Anthropogenic noise impacts behaviour and physiology in many species, but responses could change with repeat exposures. As repeat exposures can vary in regularity, identifying regimes with less impact is important for regulation. We use a 16-day split-brood experiment to compare effects of regular and random acoustic noise (playbacks of recordings of ships), relative to ambient-noise controls, on behaviour, growth and development of larval Atlantic cod (Gadus morhua). Short-term noise caused startle responses in newly hatched fish, irrespective of rearing noise. Two days of both regular and random noise regimes reduced growth, while regular noise led to faster yolk sac use. After 16 days, growth in all three sound treatments converged, although fish exposed to regular noise had lower body width-length ratios. Larvae with lower body width-length ratios were easier to catch in a predator-avoidance experiment. Our results demonstrate that the timing of acoustic disturbances can impact survival-related measures during development. Much current work focuses on sound levels, but future studies should consider the role of noise regularity and its importance for noise management and mitigation measures. © 2015 The Authors.

  16. Phenomenological analysis of random telegraph noise in amorphous TiOx-based bipolar resistive switching random access memory devices.

    Science.gov (United States)

    Lee, Jung-Kyu; Lee, Ju-Wan; Bae, Jong-Ho; Park, Jinwon; Chung, Sung-Woong; Roh, Jae Sung; Hong, Sung-Joo; Lee, Jong-Ho

    2012-07-01

    As dimensions of resistive random access memories (RRAMs) devices continue to shrink, the low-frequency noise of nanoscale devices has become increasingly important in evaluating the device reliability. Thus, we investigated random telegraph noise (RTN) caused by capture and emission of an electron at traps. We physically analyzed capture and emission processes through systematic measurements of amorphous TiOx (alpha-TiOx)-based bipolar RRAMs. RTNs were observed during high-resistance state (HRS) in most devices. However, discrete switching behavior was scarcely observed in low-resistance state (LRS) as most of traps in the alpha-TiOx were filled with mobile ions such as O2- in LRS. The capture and emission processes of an electron at traps are largely divided into two groups: (1) both capture and emission processes are mainly affected by electric field; and (2) one of the capture and emission processes is only influenced by the thermal process. This paper provides fundamental physics required to understand the mechanism of RTNs in alpha-TiOx-based bipolar RRAMs.

  17. Compressively Characterizing High-Dimensional Entangled States with Complementary, Random Filtering

    Directory of Open Access Journals (Sweden)

    Gregory A. Howland

    2016-05-01

    Full Text Available The resources needed to conventionally characterize a quantum system are overwhelmingly large for high-dimensional systems. This obstacle may be overcome by abandoning traditional cornerstones of quantum measurement, such as general quantum states, strong projective measurement, and assumption-free characterization. Following this reasoning, we demonstrate an efficient technique for characterizing high-dimensional, spatial entanglement with one set of measurements. We recover sharp distributions with local, random filtering of the same ensemble in momentum followed by position—something the uncertainty principle forbids for projective measurements. Exploiting the expectation that entangled signals are highly correlated, we use fewer than 5000 measurements to characterize a 65,536-dimensional state. Finally, we use entropic inequalities to witness entanglement without a density matrix. Our method represents the sea change unfolding in quantum measurement, where methods influenced by the information theory and signal-processing communities replace unscalable, brute-force techniques—a progression previously followed by classical sensing.

  18. Low-noise and high-gain Brillouin optical amplifier for narrowband active optical filtering based on a pump-to-signal optoelectronic tracking.

    Science.gov (United States)

    Souidi, Yahia; Taleb, Fethallah; Zheng, Junbo; Lee, Min Won; Du Burck, Frédéric; Roncin, Vincent

    2016-01-10

    We implement and characterize an optical narrowband amplifier based on stimulated Brillouin scattering with pump-to-signal relative frequency fluctuations overcome thanks to an active pump tracking. We achieve a precise characterization of this amplifier in terms of gain and noise degradation (noise figure). The performances of this stable selective amplification are compared to those of a conventional erbium-doped fiber amplifier in order to highlight the interest of the Brillouin amplification solution for active narrow optical filtering with a bandpass of 10 MHz. Thanks to the simple optoelectronic pump-to-signal tracking, the Brillouin active filter appears as a stable and reliable solution for narrowband optical processing in the coherent optical communication context and optical sensor applications.

  19. Statistical analysis of random telegraph noise in HfO2-based RRAM devices in LRS

    Science.gov (United States)

    Puglisi, Francesco Maria; Pavan, Paolo; Larcher, Luca; Padovani, Andrea

    2015-11-01

    In this work, we present a thorough statistical characterization of Random Telegraph Noise (RTN) in HfO2-based Resistive Random Access Memory (RRAM) cells in Low Resistive State (LRS). Devices are tested under a variety of operational conditions. A Factorial Hidden Markov Model (FHMM) analysis is exploited to extrapolate the properties of the traps causing multi-level RTN in LRS. The trapping and de-trapping of charge carriers into/out of defects located in the proximity of the conductive filament results in a shielding effect on a portion of the conductive filament, leading to the observed RTN current fluctuations. It is found that both oxygen vacancies and oxygen ions defects may be responsible for the observed RTN. The variations of the current observed at subsequent set/reset cycles are instead attributed to the stochastic variations in the filament due to oxidation/reduction processes during reset and set operations, respectively.

  20. Transcranial Random Noise Stimulation Does Not Enhance the Effects of Working Memory Training.

    Science.gov (United States)

    Holmes, Joni; Byrne, Elizabeth M; Gathercole, Susan E; Ewbank, Michael P

    2016-10-01

    Transcranial random noise stimulation (tRNS), a noninvasive brain stimulation technique, enhances the generalization and sustainability of gains following mathematical training. Here it is combined for the first time with working memory training in a double-blind randomized controlled trial. Adults completed 10 sessions of Cogmed Working Memory Training with either active tRNS or sham stimulation applied bilaterally to dorsolateral pFC. Training was associated with gains on both the training tasks and on untrained tests of working memory that shared overlapping processes with the training tasks, but not with improvements on working memory tasks with distinct processing demands or tests of other cognitive abilities (e.g., IQ, maths). There was no evidence that tRNS increased the magnitude or transfer of these gains. Thus, combining tRNS with Cogmed Working Memory Training provides no additional therapeutic value.

  1. Random exponential attractor for cocycle and application to non-autonomous stochastic lattice systems with multiplicative white noise

    Science.gov (United States)

    Zhou, Shengfan

    2017-08-01

    We first establish some sufficient conditions for constructing a random exponential attractor for a continuous cocycle on a separable Banach space and weighted spaces of infinite sequences. Then we apply our abstract result to study the existence of random exponential attractors for non-autonomous first order dissipative lattice dynamical systems with multiplicative white noise.

  2. Random telegraph noise and resistance switching analysis of oxide based resistive memory.

    Science.gov (United States)

    Choi, Shinhyun; Yang, Yuchao; Lu, Wei

    2014-01-07

    Resistive random access memory (RRAM) devices (e.g."memristors") are widely believed to be a promising candidate for future memory and logic applications. Although excellent performance has been reported, the nature of resistance switching is still under extensive debate. In this study, we perform systematic investigation of the resistance switching mechanism in a TaOx based RRAM through detailed noise analysis, and show that the resistance switching from high-resistance to low-resistance is accompanied by a semiconductor-to-metal transition mediated by the accumulation of oxygen-vacancies in the conduction path. Specifically, pronounced random-telegraph noise (RTN) with values up to 25% was observed in the device high-resistance state (HRS) but not in the low-resistance state (LRS). Through time-domain and temperature dependent analysis, we show that the RTN effect shares the same origin as the resistive switching effects, and both can be traced to the (re)distribution of oxygen vacancies (VOs). From noise and transport analysis we further obtained the density of states and average distance of the VOs at different resistance states, and developed a unified model to explain the conduction in both the HRS and the LRS and account for the resistance switching effects in these devices. Significantly, it was found that even though the conduction channel area is larger in the HRS, during resistive switching a localized region gains significantly higher VO and dominates the conduction process. These findings reveal the complex dynamics involved during resistive switching and will help guide continued optimization in the design and operation of this important emerging device class.

  3. Design and Implementation of Digital Chebyshev Type II Filter using XSG for Noise Reduction in ECG Signal

    OpenAIRE

    Kaustubh Gaikwad; Mahesh Chavan

    2016-01-01

    ASIC Chips and Digital Signal Processors are generally used for implementing digital filters. Now days the advanced technologies lead to use of field programmable Gate Array (FPGA) for the implementation of Digital Filters.The present paper deals with Design and Implementation of Digital IIR Chebyshev type II filter using Xilinx System Generator. The Quantization and Overflow are main crucial parameters while designing the filter on FPGA and that need to be consider for getting th...

  4. 2D stochastic-integral models for characterizing random grain noise in titanium alloys

    Energy Technology Data Exchange (ETDEWEB)

    Sabbagh, Harold A.; Murphy, R. Kim; Sabbagh, Elias H. [Victor Technologies, LLC, PO Box 7706, Bloomington, IN 47407-7706 (United States); Cherry, Matthew [University of Dayton Research Institute, 300 College Park Dr., Dayton, OH 45410 (United States); Pilchak, Adam; Knopp, Jeremy S.; Blodgett, Mark P. [Air Force Research Laboratory (AFRL/RXC), Wright Patterson AFB OH 45433-7817 (United States)

    2014-02-18

    We extend our previous work, in which we applied high-dimensional model representation (HDMR) and analysis of variance (ANOVA) concepts to the characterization of a metallic surface that has undergone a shot-peening treatment to reduce residual stresses, and has, therefore, become a random conductivity field. That example was treated as a onedimensional problem, because those were the only data available. In this study, we develop a more rigorous two-dimensional model for characterizing random, anisotropic grain noise in titanium alloys. Such a model is necessary if we are to accurately capture the 'clumping' of crystallites into long chains that appear during the processing of the metal into a finished product. The mathematical model starts with an application of the Karhunen-Loève (K-L) expansion for the random Euler angles, θ and φ, that characterize the orientation of each crystallite in the sample. The random orientation of each crystallite then defines the stochastic nature of the electrical conductivity tensor of the metal. We study two possible covariances, Gaussian and double-exponential, which are the kernel of the K-L integral equation, and find that the double-exponential appears to satisfy measurements more closely of the two. Results based on data from a Ti-7Al sample will be given, and further applications of HDMR and ANOVA will be discussed.

  5. Robust non-local median filter

    Science.gov (United States)

    Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

    2017-04-01

    This paper describes a novel image filter with superior performance on detail-preserving removal of random-valued impulse noise superimposed on natural gray-scale images. The non-local means filter is in the limelight as a way of Gaussian noise removal with superior performance on detail preservation. By referring the fundamental concept of the non-local means, we had proposed a non-local median filter as a specialized way for random-valued impulse noise removal so far. In the non-local processing, the output of a filter is calculated from pixels in blocks which are similar to the block centered at a pixel of interest. As a result, aggressive noise removal is conducted without destroying the detailed structures in an original image. However, the performance of non-local processing decreases enormously in the case of high noise occurrence probability. A cause of this problem is that the superimposed noise disturbs accurate calculation of the similarity between the blocks. To cope with this problem, we propose an improved non-local median filter which is robust to the high level of corruption by introducing a new similarity measure considering possibility of being the original signal. The effectiveness and validity of the proposed method are verified in a series of experiments using natural gray-scale images.

  6. Iterative dip-steering median filter

    Science.gov (United States)

    Huo, Shoudong; Zhu, Weihong; Shi, Taikun

    2017-09-01

    Seismic data are always contaminated with high noise components, which present processing challenges especially for signal preservation and its true amplitude response. This paper deals with an extension of the conventional median filter, which is widely used in random noise attenuation. It is known that the standard median filter works well with laterally aligned coherent events but cannot handle steep events, especially events with conflicting dips. In this paper, an iterative dip-steering median filter is proposed for the attenuation of random noise in the presence of multiple dips. The filter first identifies the dominant dips inside an optimized processing window by a Fourier-radial transform in the frequency-wavenumber domain. The optimum size of the processing window depends on the intensity of random noise that needs to be attenuated and the amount of signal to be preserved. It then applies median filter along the dominant dip and retains the signals. Iterations are adopted to process the residual signals along the remaining dominant dips in a descending sequence, until all signals have been retained. The method is tested by both synthetic and field data gathers and also compared with the commonly used f-k least squares de-noising and f-x deconvolution.

  7. Respiratory Filter Reduces the Cardiovascular Effects Associated With Diesel Exhaust Exposure: A Randomized, Prospective, Double-Blind, Controlled Study of Heart Failure: The FILTER-HF Trial.

    Science.gov (United States)

    Vieira, Jefferson L; Guimaraes, Guilherme V; de Andre, Paulo A; Cruz, Fátima D; Saldiva, Paulo H Nascimento; Bocchi, Edimar A

    2016-01-01

    The goal of this study was to test the effects of a respiratory filter intervention (filter) during controlled pollution exposure. Air pollution is considered a risk factor for heart failure (HF) decompensation and mortality. This study was a double-blind, randomized to order, controlled, 3-way crossover, single-center clinical trial. It enrolled 26 patients with HF and 15 control volunteers. Participants were exposed in 3 separate sessions to clean air, unfiltered diesel exhaust exposure (DE), or filtered DE. Endpoints were endothelial function assessed by using the reactive hyperemia index (RHi), arterial stiffness, serum biomarkers, 6-min walking distance, and heart rate variability. In patients with HF, DE was associated with a worsening in RHi from 2.17 (interquartile range [IQR]: 1.8 to 2.5) to 1.72 (IQR: 1.5 to 2.2; p = 0.002) and an increase in B-type natriuretic peptide (BNP) from 47.0 pg/ml (IQR: 17.3 to 118.0 pg/ml) to 66.5 pg/ml (IQR: 26.5 to 155.5 pg/ml; p = 0.004). Filtration reduced the particulate concentration (325 ± 31 μg/m(3) vs. 25 ± 6 μg/m(3); p HF, filter was associated with an improvement in RHi from 1.72 (IQR: 1.5 to 2.2) to 2.06 (IQR: 1.5 to 2.6; p = 0.019) and a decrease in BNP from 66.5 pg/ml (IQR: 26.5 to 155.5 pg/ml) to 44.0 pg/ml (IQR: 20.0 to 110.0 pg/ml; p = 0.015) compared with DE. In both groups, DE decreased the 6-min walking distance and arterial stiffness, although filter did not change these responses. DE had no effect on heart rate variability or exercise testing. To our knowledge, this trial is the first to show that a filter can reduce both endothelial dysfunction and BNP increases in patients with HF during DE. Given these potential benefits, the widespread use of filters in patients with HF exposed to traffic-derived air pollution may have beneficial public health effects and reduce the burden of HF. (Effects of Air Pollution Exposure Reduction by Filter Mask on Heart Failure; NCT01960920). Copyright © 2016

  8. Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.

    Science.gov (United States)

    Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B

    2013-03-01

    Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.

  9. Novel evidence that attributing affectively salient signal to random noise is associated with psychosis.

    Science.gov (United States)

    Catalan, Ana; Simons, Claudia J P; Bustamante, Sonia; Drukker, Marjan; Madrazo, Aranzazu; de Artaza, Maider Gonzalez; Gorostiza, Iñigo; van Os, Jim; Gonzalez-Torres, Miguel A

    2014-01-01

    We wished to replicate evidence that an experimental paradigm of speech illusions is associated with psychotic experiences. Fifty-four patients with a first episode of psychosis (FEP) and 150 healthy subjects were examined in an experimental paradigm assessing the presence of speech illusion in neutral white noise. Socio-demographic, cognitive function and family history data were collected. The Positive and Negative Syndrome Scale (PANSS) was administered in the patient group and the Structured Interview for Schizotypy-Revised (SIS-R), and the Community Assessment of Psychic Experiences (CAPE) in the control group. Patients had a much higher rate of speech illusions (33.3% versus 8.7%, ORadjusted: 5.1, 95% CI: 2.3-11.5), which was only partly explained by differences in IQ (ORadjusted: 3.4, 95% CI: 1.4-8.3). Differences were particularly marked for signals in random noise that were perceived as affectively salient (ORadjusted: 9.7, 95% CI: 1.8-53.9). Speech illusion tended to be associated with positive symptoms in patients (ORadjusted: 3.3, 95% CI: 0.9-11.6), particularly affectively salient illusions (ORadjusted: 8.3, 95% CI: 0.7-100.3). In controls, speech illusions were not associated with positive schizotypy (ORadjusted: 1.1, 95% CI: 0.3-3.4) or self-reported psychotic experiences (ORadjusted: 1.4, 95% CI: 0.4-4.6). Experimental paradigms indexing the tendency to detect affectively salient signals in noise may be used to identify liability to psychosis.

  10. Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

    Science.gov (United States)

    Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.

    2017-01-01

    Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561

  11. Discrete stochastic processes and optimal filtering

    CERN Document Server

    Bertein, Jean-Claude

    2012-01-01

    Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar

  12. Errors due to random noise in velocity measurement using incoherent-scatter radar

    Directory of Open Access Journals (Sweden)

    P. J. S. Williams

    Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.

  13. Errors due to random noise in velocity measurement using incoherent-scatter radar

    Directory of Open Access Journals (Sweden)

    P. J. S. Williams

    1996-12-01

    Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.

  14. Improvement of the seismic noise attenuation performance of the Monolithic Geometric Anti-Spring filters for gravitational wave interferometric detectors

    Energy Technology Data Exchange (ETDEWEB)

    Stochino, Alberto [Dipartimento di Fisica, Universita di Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa (Italy); California Institute of Technology, MS 18-34, 91125 Pasadena, CA (United States)], E-mail: stochino@ligo.caltech.edu; DeSalvo, Riccardo [California Institute of Technology, MS 18-34, 91125 Pasadena, CA (United States); Huang Yumei [Department of Astronomy, Beijing Normal University, 100875 Beijing (China); California Institute of Technology, MS 18-34, 91125 Pasadena, CA (United States); Sannibale, Virginio [California Institute of Technology, MS 18-34, 91125 Pasadena, CA (United States)

    2007-10-11

    The Monolithic Geometric Anti-Spring (GAS) filter is one of the most efficient vertical seismic isolation devices for Gravitational Wave (GW) interferometers. However, the attenuation of this filter was previously limited to around 60 dB due to the high frequency saturation associated with the filter's distributed mass-a problem typical of passive mechanical filters. We show that it is possible to circumvent this limit using a compensation wand based on the Center Of Percussion (COP) effect. When this device is mounted in parallel with the blade springs of a GAS filter, attenuation improves to 80 dB in the region above 10 Hz. Using this device it is therefore possible to design simpler attenuation chains consisting of fewer stages.

  15. OPTIMAL LINEAR COMBINED FILTERING OF RANDOM SEQUENCES BASED ON THE RECURSIVE LEAST SQUARES METHOD

    Directory of Open Access Journals (Sweden)

    V. M. Artemiev

    2015-01-01

    Full Text Available The problem of the synthesis of linear combined filter for the criterion of minimizing current losses on the basis of the recursive least squares method is being solved. This approach does not requirea priori knowledge of the statistical characteristics of impacts that is an advantage compared with the Kalman filter. A comparative evaluation of the filters’ accuracy is provided using the values of variances of the filtering errors.

  16. Bilateral Filtering using Modified Fuzzy Clustering for Image Denoising

    OpenAIRE

    G.Vijaya,; Dr.V.Vasudevan

    2011-01-01

    This paper presents a novel bilateral filtering using weighed fcm algorithm based on Gaussian kernel unction for image manipulations such as segmentation and denoising . Our proposed bilateral filteringconsists of the standard bilateral filter and the original Euclidean distance is replaced by a kernel – induced distance in the algorithm. We have applied the proposed filtering for image denoising with both the impulse and Gaussian random noise, which achieves better results than the bilateral...

  17. A New Switching-Based Median Filtering Scheme and Algorithm for Removal of High-Density Salt and Pepper Noise in Images

    Directory of Open Access Journals (Sweden)

    Jayaraj V

    2010-01-01

    Full Text Available A new switching-based median filtering scheme for restoration of images that are highly corrupted by salt and pepper noise is proposed. An algorithm based on the scheme is developed. The new scheme introduces the concept of substitution of noisy pixels by linear prediction prior to estimation. A novel simplified linear predictor is developed for this purpose. The objective of the scheme and algorithm is the removal of high-density salt and pepper noise in images. The new algorithm shows significantly better image quality with good PSNR, reduced MSE, good edge preservation, and reduced streaking. The good performance is achieved with reduced computational complexity. A comparison of the performance is made with several existing algorithms in terms of visual and quantitative results. The performance of the proposed scheme and algorithm is demonstrated.

  18. Reduction of timing jitter and intensity noise in normal-dispersion passively mode-locked fiber lasers by narrow band-pass filtering.

    Science.gov (United States)

    Qin, Peng; Song, Youjian; Kim, Hyoji; Shin, Junho; Kwon, Dohyeon; Hu, Minglie; Wang, Chingyue; Kim, Jungwon

    2014-11-17

    Fiber lasers mode-locked with normal cavity dispersion have recently attracted great attention due to large output pulse energy and femtosecond pulse duration. Here we accurately characterized the timing jitter of normal-dispersion fiber lasers using a balanced cross-correlation method. The timing jitter characterization experiments show that the timing jitter of normal-dispersion mode-locked fiber lasers can be significantly reduced by using narrow band-pass filtering (e.g., 7-nm bandwidth filtering in this work). We further identify that the timing jitter of the fiber laser is confined in a limited range, which is almost independent of cavity dispersion map due to the amplifier-similariton formation by insertion of the narrow bandpass filter. The lowest observed timing jitter reaches 0.57 fs (rms) integrated from 10 kHz to 10 MHz Fourier frequency. The rms relative intensity noise (RIN) is also reduced from 0.37% to 0.02% (integrated from 1 kHz to 5 MHz Fourier frequency) by the insertion of narrow band-pass filter.

  19. Transcranial Random Noise Stimulation (tRNS Shapes the Processing of Rapidly Changing Auditory Information

    Directory of Open Access Journals (Sweden)

    Katharina S. Rufener

    2017-06-01

    Full Text Available Neural oscillations in the gamma range are the dominant rhythmic activation pattern in the human auditory cortex. These gamma oscillations are functionally relevant for the processing of rapidly changing acoustic information in both speech and non-speech sounds. Accordingly, there is a tight link between the temporal resolution ability of the auditory system and inherent neural gamma oscillations. Transcranial random noise stimulation (tRNS has been demonstrated to specifically increase gamma oscillation in the human auditory cortex. However, neither the physiological mechanisms of tRNS nor the behavioral consequences of this intervention are completely understood. In the present study we stimulated the human auditory cortex bilaterally with tRNS while EEG was continuously measured. Modulations in the participants’ temporal and spectral resolution ability were investigated by means of a gap detection task and a pitch discrimination task. Compared to sham, auditory tRNS increased the detection rate for near-threshold stimuli in the temporal domain only, while no such effect was present for the discrimination of spectral features. Behavioral findings were paralleled by reduced peak latencies of the P50 and N1 component of the auditory event-related potentials (ERP indicating an impact on early sensory processing. The facilitating effect of tRNS was limited to the processing of near-threshold stimuli while stimuli clearly below and above the individual perception threshold were not affected by tRNS. This non-linear relationship between the signal-to-noise level of the presented stimuli and the effect of stimulation further qualifies stochastic resonance (SR as the underlying mechanism of tRNS on auditory processing. Our results demonstrate a tRNS related improvement in acoustic perception of time critical auditory information and, thus, provide further indices that auditory tRNS can amplify the resonance frequency of the auditory system.

  20. Study of combined filter based on wavelet transform to denoise stripe images of electronic speckle shearography pattern interferometry

    Science.gov (United States)

    Liu, Zhongling; Jing, Chao; Zhang, Yimo

    2011-11-01

    Stripe images of electronic speckle shearography pattern interferometry, in which stripe distribution are correlated with vertical micro distortion or micro vibration of objects, are severely disturbed by noises, and so denoising stripe images of electronic speckle shearography pattern interferometry is necessary to extract useful stripe distribution information. Denoising methods and flow for stripe images of electronic speckle shearography pattern interferometry are analyzed in this paper to get the stripe distribution correlated with vertical micro distortion or micro vibration of objects. The noises in the stripe images of electronic speckle shearography pattern interferometry are comprised of speckle noise and other random noises induced by environmental disturb and instrumental performance, so it's difficult to use familiar filters, such as mean-value filter, medium-value filter and adaptive filter, etc, to remove all noises in the stripe images. The combined filter composed of mean-value filter and wavelet filter is designed to denoise stripe images. The aim of mean-value filter is to remove random noises induced by environmental disturb and instrumental performance, and then the wavelet filter, in which the Meyer wavelet is adopted, is designed to remove speckle noise in the stripe images. The final stripe distribution images after denoising and binarization are listed to prove the denoising validity of combined filter based on wavelet transform.

  1. A combination of spatial and recursive temporal filtering for noise reduction when using region of interest (ROI) fluoroscopy for patient dose reduction in image guided vascular interventions with significant anatomical motion

    Science.gov (United States)

    Setlur Nagesh, S. V.; Khobragade, P.; Ionita, C.; Bednarek, D. R.; Rudin, S.

    2015-03-01

    Because x-ray based image-guided vascular interventions are minimally invasive they are currently the most preferred method of treating disorders such as stroke, arterial stenosis, and aneurysms; however, the x-ray exposure to the patient during long image-guided interventional procedures could cause harmful effects such as cancer in the long run and even tissue damage in the short term. ROI fluoroscopy reduces patient dose by differentially attenuating the incident x-rays outside the region-of-interest. To reduce the noise in the dose-reduced regions previously recursive temporal filtering was successfully demonstrated for neurovascular interventions. However, in cardiac interventions, anatomical motion is significant and excessive recursive filtering could cause blur. In this work the effects of three noise-reduction schemes, including recursive temporal filtering, spatial mean filtering, and a combination of spatial and recursive temporal filtering, were investigated in a simulated ROI dose-reduced cardiac intervention. First a model to simulate the aortic arch and its movement was built. A coronary stent was used to simulate a bioprosthetic valve used in TAVR procedures and was deployed under dose-reduced ROI fluoroscopy during the simulated heart motion. The images were then retrospectively processed for noise reduction in the periphery, using recursive temporal filtering, spatial filtering and a combination of both. Quantitative metrics for all three noise reduction schemes are calculated and are presented as results. From these it can be concluded that with significant anatomical motion, a combination of spatial and recursive temporal filtering scheme is best suited for reducing the excess quantum noise in the periphery. This new noise-reduction technique in combination with ROI fluoroscopy has the potential for substantial patient-dose savings in cardiac interventions.

  2. DS/LPI autocorrelation detection in noise plus random-tone interference. [Direct Sequence Low-Probabilty of Intercept

    Science.gov (United States)

    Hinedi, S.; Polydoros, A.

    1988-01-01

    The authors present and analyze a frequency-noncoherent two-lag autocorrelation statistic for the wideband detection of random BPSK signals in noise-plus-random-multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values, contrary to the case of an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. It is concluded that the real-time autocorrelation domain and its samples (lags) are a viable approach for detecting random signals in dense environments.

  3. Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing

    OpenAIRE

    Zhongke Jiao; Bo Liu; Enhai Liu; Yongjian Yue

    2015-01-01

    In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for l...

  4. Mittag-Leffler noise induced stochastic resonance in a generalized Langevin equation with random inherent frequency

    Science.gov (United States)

    He, Guitian; Guo, Dali; Tian, Yan; Li, Tiejun; Luo, Maokang

    2017-10-01

    The generalized stochastic resonance (GSR) and the bona fide stochastic resonance (SR) in a generalized Langevin equation driven by a periodic signal, multiplicative noise and Mittag-Leffler noise are extensively investigated. The expression of the frequency spectrum of the Mittag-Leffler noise is studied. Using the Shapiro-Loginov formula and Laplace transformation technique, the exact expressions of the output amplitude gain and the signal-to-noise ratio are obtained. The simulation results turn out that the output amplitude gain and the signal-to-noise ratio are non-monotonic functions of the characteristics of noise parameters and system parameters. Especially, the influence of the memory exponent and memory time of Mittag-Leffler noise could induce the GSR phenomenon. The influence of the driving frequency could induce the bona fide stochastic resonance. It is found that the system with fractional memory exponent could be more easily induced SR phenomenon than the system with integer memory exponent.

  5. A two-stage noise source identification technique based on a farfield random parametric array.

    Science.gov (United States)

    Bai, Mingsian R; Chen, You Siang; Lo, Yi-Yang

    2017-05-01

    A farfield random array is implemented for noise source identification. Microphone positions are optimized, with the aid of the simulated annealing method. A two-stage localization and separation algorithm is devised on the basis of the equivalent source method (ESM). In the localization stage, the active source regions are located by using the delay-and-sum method, followed by a parametric localization procedure, stochastic maximum likelihood algorithm. Multidimensional nonlinear optimization is exploited in the bearing estimation process. In the separation stage, source amplitudes are extracted by formulating an inverse problem based on the preceding source bearings identified. The number of equivalent sources is selected to be less than that of microphones to render an overdetermined problem which can be readily solved by using the Tikhonov regularization. Alternatively, the separation problem can be augmented into an underdetermined problem which can be solved by using the compressive sensing technique. Traditionally, farfield arrays only give a relative distribution of source field. However, by using the proposed method, the acoustic variables including sound pressure, particle velocity, sound intensity, and sound power can be calculated based on ESM. Numerical and experimental results of several objective and subjective tests are presented.

  6. Noise-induced hearing loss in randomly selected New York dairy farmers.

    Science.gov (United States)

    May, J J; Marvel, M; Regan, M; Marvel, L H; Pratt, D S

    1990-01-01

    To understand better the effects of noise levels associated with dairy farming, we randomly selected 49 full-time dairy farmers from an established cohort. Medical and occupational histories were taken and standard audiometric testing was done. Forty-six males (94%) and three females (6%) with a mean age of 43.5 (+/- 13) years and an average of 29.4 (+/- 14) years in farming were tested. Pure Tone Average thresholds (PTA4) at 0.5, 1.0, 2.0, and 3.0 kHz plus High Frequency Average thresholds (HFA3) at 3.0, 4.0, and 6.0 kHz were calculated. Subjects with a loss of greater than or equal to 20 db in either ear were considered abnormal. Eighteen subjects (37%) had abnormal PTA4S and 32 (65%) abnormal HFA3S. The left ear was more severely affected in both groups (p less than or equal to .05, t-test). Significant associations were found between hearing loss and years worked (odds ratio 4.1, r = .53) and age (odds ratio 4.1, r = .59). No association could be found between hearing loss and measles; mumps; previous ear infections; or use of power tools, guns, motorcycles, snowmobiles, or stereo headphones. Our data suggest that among farmers, substantial hearing loss occurs especially in the high-frequency ranges. Presbycusis is an important confounding variable.

  7. Ambient awareness: From random noise to digital closeness in online social networks.

    Science.gov (United States)

    Levordashka, Ana; Utz, Sonja

    2016-07-01

    Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empirically. We provide evidence for the occurrence of ambient awareness and examine key questions related to its content and functions. A diverse sample of participants reported experiencing awareness, both as a general feeling towards their network as a whole, and as knowledge of individual members of the network, whom they had not met in real life. Our results indicate that ambient awareness can develop peripherally, from fragmented information and in the relative absence of extensive one-to-one communication. We report the effects of demographics, media use, and network variables and discuss the implications of ambient awareness for relational and informational processes online.

  8. Influence of Bandstructure Effects on the Single-Charge-Induced Random Telegraphic Noise in Nanoscale FETs

    Science.gov (United States)

    Islam, Sharnali; Ahmed, Shaikh

    2010-03-01

    Numerical simulations have been carried out to study the single-charge-induced random telegraphic noise in nanoscale field-effect transistors. A three-dimensional Monte Carlo device simulator has been developed and used in this work. Quantum effects have been accounted for via a parameter-free effective potential scheme that is based on a perturbation theory around thermodynamic equilibrium where the size of the electron depends upon its energy. For better accuracy, bandstructure parameters (bandgap, effective masses, and density of states) have been computed via a 20-band sp3d5s* tight-binding scheme. To treat full Coulomb interactions properly, two real-space molecular dynamics schemes have been implemented. Also, necessary event-biasing algorithms have been used that, while enhancing the statistics, results in a faster convergence in the channel current. The study confirms that, due to the presence of single channel charges, both the electrostatics (carrier density) and dynamics (mobility) get perturbed and, therefore, play important roles in determining the magnitude of the current fluctuations. The relative impact depends on an intricate interplay of device size, geometry, crystal direction, gate bias, temperature, and energetic and spatial location of the trap.

  9. Physical-layer security analysis of PSK quantum-noise randomized cipher in optically amplified links

    Science.gov (United States)

    Jiao, Haisong; Pu, Tao; Xiang, Peng; Zheng, Jilin; Fang, Tao; Zhu, Huatao

    2017-08-01

    The quantitative security of quantum-noise randomized cipher (QNRC) in optically amplified links is analyzed from the perspective of physical-layer advantage. Establishing the wire-tap channel models for both key and data, we derive the general expressions of secrecy capacities for the key against ciphertext-only attack and known-plaintext attack, and that for the data, which serve as the basic performance metrics. Further, the maximal achievable secrecy rate of the system is proposed, under which secrecy of both the key and data is guaranteed. Based on the same framework, the secrecy capacities of various cases can be assessed and compared. The results indicate perfect secrecy is potentially achievable for data transmission, and an elementary principle of setting proper number of photons and bases is given to ensure the maximal data secrecy capacity. But the key security is asymptotically perfect, which tends to be the main constraint of systemic maximal secrecy rate. Moreover, by adopting cascaded optical amplification, QNRC can realize long-haul transmission with secure rate up to Gb/s, which is orders of magnitude higher than the perfect secrecy rates of other encryption systems.

  10. Dynamical decoupling of local transverse random telegraph noise in a two-qubit gate

    Science.gov (United States)

    D'Arrigo, A.; Falci, G.; Paladino, E.

    2015-10-01

    Achieving high-fidelity universal two-qubit gates is a central requisite of any implementation of quantum information processing. The presence of spurious fluctuators of various physical origin represents a limiting factor for superconducting nanodevices. Operating qubits at optimal points, where the qubit-fluctuator interaction is transverse with respect to the single qubit Hamiltonian, considerably improved single qubit gates. Further enhancement has been achieved by dynamical decoupling (DD). In this article we investigate DD of transverse random telegraph noise acting locally on each of the qubits forming an entangling gate. Our analysis is based on the exact numerical solution of the stochastic Schrödinger equation. We evaluate the gate error under local periodic, Carr-Purcell and Uhrig DD sequences. We find that a threshold value of the number, n, of pulses exists above which the gate error decreases with a sequence-specific power-law dependence on n. Below threshold, DD may even increase the error with respect to the unconditioned evolution, a behaviour reminiscent of the anti-Zeno effect.

  11. Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise.

    Directory of Open Access Journals (Sweden)

    Reva E Johnson

    Full Text Available The objective of this study was to understand how people adapt to errors when using a myoelectric control interface. We compared adaptation across 1 non-amputee subjects using joint angle, joint torque, and myoelectric control interfaces, and 2 amputee subjects using myoelectric control interfaces with residual and intact limbs (five total control interface conditions. We measured trial-by-trial adaptation to self-generated errors and random perturbations during a virtual, single degree-of-freedom task with two levels of feedback uncertainty, and evaluated adaptation by fitting a hierarchical Kalman filter model. We have two main results. First, adaptation to random perturbations was similar across all control interfaces, whereas adaptation to self-generated errors differed. These patterns matched predictions of our model, which was fit to each control interface by changing the process noise parameter that represented system variability. Second, in amputee subjects, we found similar adaptation rates and error levels between residual and intact limbs. These results link prosthesis control to broader areas of motor learning and adaptation and provide a useful model of adaptation with myoelectric control. The model of adaptation will help us understand and solve prosthesis control challenges, such as providing additional sensory feedback.

  12. Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise.

    Science.gov (United States)

    Johnson, Reva E; Kording, Konrad P; Hargrove, Levi J; Sensinger, Jonathon W

    2017-01-01

    The objective of this study was to understand how people adapt to errors when using a myoelectric control interface. We compared adaptation across 1) non-amputee subjects using joint angle, joint torque, and myoelectric control interfaces, and 2) amputee subjects using myoelectric control interfaces with residual and intact limbs (five total control interface conditions). We measured trial-by-trial adaptation to self-generated errors and random perturbations during a virtual, single degree-of-freedom task with two levels of feedback uncertainty, and evaluated adaptation by fitting a hierarchical Kalman filter model. We have two main results. First, adaptation to random perturbations was similar across all control interfaces, whereas adaptation to self-generated errors differed. These patterns matched predictions of our model, which was fit to each control interface by changing the process noise parameter that represented system variability. Second, in amputee subjects, we found similar adaptation rates and error levels between residual and intact limbs. These results link prosthesis control to broader areas of motor learning and adaptation and provide a useful model of adaptation with myoelectric control. The model of adaptation will help us understand and solve prosthesis control challenges, such as providing additional sensory feedback.

  13. Hydrogen-dependent low frequency noise and its physical mechanism of HfO2 resistance change random access memory

    Science.gov (United States)

    Chen, Y. Q.; Liu, X.; Liu, Y.; Peng, C.; Fang, W. X.; En, Y. F.; Huang, Y.

    2017-12-01

    The effect of hydrogen on low frequency noise characteristics of HfO2 resistance change random access memories (RRAMs) was investigated in this paper. The experimental results show that HfO2 RRAMs after hydrogen treatment take on the better uniformity of switch characteristics and the conduction enhancement behavior. Furthermore, it was found that the low frequency noise characteristics of the HfO2 RRAMs was significantly impacted by the hydrogen treatment, and at three kinds of typical resistance states, the low frequency noises of the HfO2 RRAMs after hydrogen treatment are larger than those of the fresh HfO2 RRAMs. The mechanism could be attributed to H induced oxygen vacancies, which serve as the additional traps for conduction due to the trap-assisted tunneling process. This will result in more random trap/detrap processes in the conducting filament, which gives rise to the larger low frequency noise in the HfO2 RRAMs. The results of this study may be useful in the design and application of HfO2 RRAMs.

  14. Nonlinear bayesian state filtering with missing measurements and bounded noise and its application to vehicle position estimation

    Czech Academy of Sciences Publication Activity Database

    Pavelková, Lenka

    2011-01-01

    Roč. 47, č. 3 (2011), s. 370-384 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : non-linear state space model * bounded uncertainty * missing measurements * state filtering * vehicle position estimation Subject RIV: BC - Control Systems Theory Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/pavelkova-0360239.pdf

  15. Scaling characteristics of one-dimensional fractional diffusion processes in the presence of power-law distributed random noise

    Science.gov (United States)

    Nezhadhaghighi, Mohsen Ghasemi

    2017-08-01

    Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ -stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α . We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ -stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.

  16. Noise-correlation-time-mediated localization in random nonlinear dynamical systems

    CERN Document Server

    Cabrera, J L; De la Rubia, F J; Cabrera, Juan L.

    1999-01-01

    We investigate the behavior of the residence times density function for different nonlinear dynamical systems with limit cycle behavior and perturbed parametrically with a colored noise. We present evidence that underlying the stochastic resonancelike behavior with the noise correlation time, there is an effect of optimal localization of the system trajectories in the phase space. This phenomenon is observed in systems with different nonlinearities, suggesting a degree of universality.

  17. Transcranial random noise stimulation mitigates increased difficulty in an arithmetic learning task.

    Science.gov (United States)

    Popescu, Tudor; Krause, Beatrix; Terhune, Devin B; Twose, Olivia; Page, Thomas; Humphreys, Glyn; Cohen Kadosh, Roi

    2016-01-29

    Proficiency in arithmetic learning can be achieved by using a multitude of strategies, the most salient of which are procedural learning (applying a certain set of computations) and rote learning (direct retrieval from long-term memory). Here we investigated the effect of transcranial random noise stimulation (tRNS), a non-invasive brain stimulation method previously shown to enhance cognitive training, on both types of learning in a 5-day sham-controlled training study, under two conditions of task difficulty, defined in terms of item repetition. On the basis of previous research implicating the prefrontal and posterior parietal cortex in early and late stages of arithmetic learning, respectively, sham-controlled tRNS was applied to bilateral prefrontal cortex for the first 3 days and to the posterior parietal cortex for the last 2 days of a 5-day training phase. The training involved learning to solve arithmetic problems by applying a calculation algorithm; both trained and untrained problems were used in a brief testing phase at the end of the training phase. Task difficulty was manipulated between subjects by using either a large ("easy" condition) or a small ("difficult" condition) number of repetition of problems during training. Measures of attention and working memory were acquired before and after the training phase. As compared to sham, participants in the tRNS condition displayed faster reaction times and increased learning rate during the training phase; as well as faster reaction times for both trained and untrained (new) problems, which indicated a transfer effect after the end of training. All stimulation effects reached significance only in the "difficult" condition when number of repetition was lower. There were no transfer effects of tRNS on attention or working memory. The results support the view that tRNS can produce specific facilitative effects on numerical cognition--specifically, on arithmetic learning. They also highlight the importance of

  18. 1/f Noise and multifractality from bristlecone pine growth explained by the statistical convergence of random data

    Science.gov (United States)

    Kendal, Wayne S.

    2017-02-01

    Tree-ring growth records from bristlecone pines reveal an irregular pattern of fluctuations that have been linked to climatic change but otherwise have remained poorly understood. We find within these records evidence for a temporally related variance to mean power law, 1/f noise and multifractality that empirically resembles a fractal stochastic process and could be attributed to self-organized criticality. These growth records, however, also conformed to a non-Gaussian statistical distribution (the Tweedie compound Poisson distribution) characterized by an inherent variance to mean power law, that by itself implies 1/f noise. This distribution has a fundamental role in statistical theory as a focus of convergence for many types of random data, much like the Gaussian distribution has with the central limit theorem. The growth records were also multifractal, with the dimensional exponent of the Tweedie distribution critically balanced near the transition point between fractal stochastic processes and gamma distributed data, possibly consequent to a related convergence effect. Non-Gaussian random systems, like those related to bristlecone pine tree growth, may express 1/f noise and multifractality through mathematical convergence effects alone, without the dynamical assumptions of self-organized criticality.

  19. The clinical and biomechanical effects of subthreshold random noise on the plantar surface of the foot in diabetic patients and elder people: A systematic review.

    Science.gov (United States)

    Bagherzadeh Cham, Masumeh; Mohseni-Bandpei, Mohammad Ali; Bahramizadeh, Mahmood; Kalbasi, Saeed; Biglarian, Akbar

    2016-12-01

    Central nervous system receives information from foot mechanoreceptors in order to control balance and perform movement tasks. Subthreshold random noise seems to improve sensitivity of the cutaneous mechanoreceptor. The purpose of this study was to systematically review published evidence conducted to evaluate the clinical and biomechanical effects of subthreshold random noise on the plantar surface of the foot in diabetic patients and elder people. Systematic review. A literature search was performed in PubMed, Scopus, ScienceDirect, Web of Knowledge, CINAHL, and EMBASE databases based on population, intervention, comparison, outcomes, and study method. Quality of studies was assessed using the methodological quality assessment tool, using Physiotherapy Evidence Database scale. In all, 11 studies were selected for final evaluation based on inclusion criteria. Five studies evaluated the effects of subthreshold random noise in diabetic patients and six in elder people. In seven studies, biomechanical (balance and gait parameters) effects and in four studies clinical (pressure and vibration sensations) effects of subthreshold random noise were investigated. All reviewed studies were scored fair (2) to good (9) quality in terms of methodological quality assessment using Physiotherapy Evidence Database scale. The results indicated that subthreshold random noise improves balance and sensation in diabetic patients and elder people. Also gait variables can be improved in elder people with subthreshold random noise. However, further well-designed studies are needed. The previous studies reported that subthreshold random noise may improve gait, balance, and sensation, but more studies are needed to evaluate the long-term effect of subthreshold random noise in shoe or insole for daily living tasks in diabetic patients and elder people. © The International Society for Prosthetics and Orthotics 2016.

  20. Generalized randomly amplified linear system driven by gaussian noises: extreme heavy tail and algebraic correlation decay in plasma turbulence.

    Science.gov (United States)

    Steinbrecher, György; Weyssow, B

    2004-03-26

    The extreme heavy tail and the power-law decay of the turbulent flux correlation observed in hot magnetically confined plasmas are modeled by a system of coupled Langevin equations describing a continuous time linear randomly amplified stochastic process where the amplification factor is driven by a superposition of colored noises which, in a suitable limit, generate a fractional Brownian motion. An exact analytical formula for the power-law tail exponent beta is derived. The extremely small value of the heavy tail exponent and the power-law distribution of laminar times also found experimentally are obtained, in a robust manner, for a wide range of input values, as a consequence of the (asymptotic) self-similarity property of the noise spectrum. As a by-product, a new representation of the persistent fractional Brownian motion is obtained.

  1. Adaptively Blocked Particle Filtering with Spatial Smoothing in Large Scale Dynamic Random Fields

    Science.gov (United States)

    2014-07-01

    References [1] B.D.O. Anderson and J.B. Moore. Optimal Filtering. Prentice Hall, Englewood Cliffs, N.J., 1979. [2] A. Beskos, D. Crisan , and A. Jasra. On the... Crisan , A. Jasra, and N. Whiteley. Error bounds and normalising constants for sequential Monte Carlo samplers in high dimensions. Advances in Applied...Statistics, 2008. [5] O. Cappé, E. Moulines, and T. Rydén. Inference in Hidden MarkovModels. Springer, New York, N.Y., 2005. [6] D. Crisan and A. Doucet

  2. Time and direction of arrival detection and filtering for imaging in strongly scattering random media

    CERN Document Server

    Borcea, Liliana; Tsogka, Chrysoula

    2016-01-01

    We study detection and imaging of small reflectors in heavy clutter, using an array of transducers that emits and receives sound waves. Heavy clutter means that multiple scattering of the waves in the heterogeneous host medium is strong and overwhelms the arrivals from the small reflectors. Building on the adaptive time-frequency filter of [1], we propose a robust method for detecting the direction of arrival of the direct echoes from the small reflectors, and suppressing the unwanted clutter backscatter. This improves the resolution of imaging. We illustrate the performance of the method with realistic numerical simulations in a non-destructive testing setup.

  3. Bias aware Kalman filters

    DEFF Research Database (Denmark)

    Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

    2006-01-01

    This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model sta...

  4. Effect of signal-temporal uncertainty in children and adults: tone detection in noise or a random-frequency masker.

    Science.gov (United States)

    Bonino, Angela Yarnell; Leibold, Lori J; Buss, Emily

    2013-12-01

    A cue indicating when in time to listen can improve adults' tone detection thresholds, particularly for conditions that produce substantial informational masking. The purpose of this study was to determine if 5- to 13-yr-old children likewise benefit from a light cue indicating when in time to listen for a masked pure-tone signal. Each listener was tested in one of two continuous maskers: Broadband noise (low informational masking) or a random-frequency, two-tone masker (high informational masking). Using a single-interval method of constant stimuli, detection thresholds were measured for two temporal conditions: (1) Temporally-defined, with the listening interval defined by a light cue, and (2) temporally-uncertain, with no light cue. Thresholds estimated from psychometric functions fitted to the data indicated that children and adults benefited to the same degree from the visual cue. Across listeners, the average benefit of a defined listening interval was 1.8 dB in the broadband noise and 8.6 dB in the random-frequency, two-tone masker. Thus, the benefit of knowing when in time to listen was more robust for conditions believed to be dominated by informational masking. An unexpected finding of this study was that children's thresholds were comparable to adults' in the random-frequency, two-tone masker.

  5. Data Assimilation by Conditioning of Driving Noise on Future Observations

    KAUST Repository

    Lee, Wonjung

    2014-08-01

    Conventional recursive filtering approaches, designed for quantifying the state of an evolving stochastic dynamical system with intermittent observations, use a sequence of i) an uncertainty propagation step followed by ii) a step where the associated data is assimilated using Bayes\\' rule. Alternatively, the order of the steps can be switched to i) one step ahead data assimilation followed by ii) uncertainty propagation. In this paper, we apply this smoothing-based sequential filter to systems driven by random noise, however with the conditioning on future observation not only to the system variable but to the driving noise. Our research reveals that, for the nonlinear filtering problem, the conditioned driving noise is biased by a nonzero mean and in turn pushes forward the filtering solution in time closer to the true state when it drives the system. As a result our proposed method can yield a more accurate approximate solution for the state estimation problem. © 1991-2012 IEEE.

  6. Validation of the k-filtering technique for a signal composed of random-phase plane waves and non-random coherent structures

    Directory of Open Access Journals (Sweden)

    O. W. Roberts

    2014-12-01

    Full Text Available Recent observations of astrophysical magnetic fields have shown the presence of fluctuations being wave-like (propagating in the plasma frame and those described as being structure-like (advected by the plasma bulk velocity. Typically with single-spacecraft missions it is impossible to differentiate between these two fluctuations, due to the inherent spatio-temporal ambiguity associated with a single point measurement. However missions such as Cluster which contain multiple spacecraft have allowed for temporal and spatial changes to be resolved, using techniques such as k filtering. While this technique does not assume Taylor's hypothesis it requires both weak stationarity of the time series and that the fluctuations can be described by a superposition of plane waves with random phases. In this paper we test whether the method can cope with a synthetic signal which is composed of a combination of non-random-phase coherent structures with a mean radius d and a mean separation λ, as well as plane waves with random phase.

  7. Simultaneous Range-Velocity Processing and SNR Analysis of AFIT’s Random Noise Radar

    Science.gov (United States)

    2012-03-22

    First, and above all else, I give thanks and praise to the one from whom all blessings are given. Thank you, God , for continually giving generously to...target’s radial velocity is constant over the measurement window Ttx. Lievsay [18] created a bank of reference signals, analogous to Doppler filter...where ⌈⋅⌉ represents the integer ceiling of the computed value. Velocity resolution is directly tied to the highest frequency of the signal, fℎ and

  8. Combined influence of CT random noise and HU-RSP calibration curve nonlinearities on proton range systematic errors

    Science.gov (United States)

    Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.

    2017-11-01

    Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.

  9. Information processing at a central synapse suggests a noise filter in the auditory pathway of the noctuid moth.

    Science.gov (United States)

    Boyan, G S; Fullard, J H

    1988-12-01

    1. The central projections of the A1 afferent were confirmed via intracellular recording and staining with Lucifer Yellow in the pterothoracic ganglion of the noctuid moths, Agrotis infusa and Apamea amputatrix (Fig. 1). Simultaneous recordings of the A1 afferent in the tympanal nerve (extracellularly) and in the pterothoracic ganglion (intracellularly) confirm the identity of the stained receptor as being the A1 cell. 2. The major postsynaptic arborizations of interneurone 501 in the pterothoracic ganglion were also demonstrated via intracellular recording and staining (Fig. 2). Simultaneous recordings of the A1 afferent (extracellularly) and neurone 501 (intracellularly) revealed that each A1 spike evokes a constant short latency EPSP in the interneurone (Fig. 2Bi). Neurone 501 receives only monaural input from the A1 afferent on its soma side as demonstrated by electrical stimulation of each afferent nerve (Fig. 2Bii). EPSPs evoked in neurone 501 by high frequency (100 Hz) electrical stimulation of the afferent nerve did not decrement (Fig. 2Biii). These data are consistent with a monosynaptic input to neurone 501 from the A1 afferent. 3. The response of neurone 501 to a sound stimulus presented at an intensity near the upper limit of its linear response range (30 ms, 16 kHz, 80 dB SPL) was a plateau-like depolarization, with tonic spiking activity which continued beyond the end of the tone. The instantaneous spike frequency of the response was as high as 800 Hz, and was maintained at above 600 Hz for the duration of the tone (Fig. 3). 4. The relationship between the instantaneous spike frequency in the A1 afferent and that recorded simultaneously in neurone 501 is linear over the entire range of A1 spike frequencies evoked by white noise sound stimuli (Fig. 4). Similarly, the relationship between instantaneous spike frequency in the A1 afferent and the mean depolarization evoked in neurone 501 is also linear for all A1 spike frequencies tested (Fig. 5). No

  10. Cooperation of deterministic dynamics and random noise in production of complex syntactical avian song sequences: a neural network model

    Directory of Open Access Journals (Sweden)

    Yuichi eYamashita

    2011-04-01

    Full Text Available How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC, a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf-HVC interaction.

  11. Training in using earplugs or using earplugs with a higher than necessary noise reduction rating? A randomized clinical trial.

    Science.gov (United States)

    Salmani Nodoushan, M; Mehrparvar, A H; Torab Jahromi, M; Safaei, S; Mollasadeghi, A

    2014-10-01

    Noise-induced hearing loss (NIHL) is one of the most common occupational diseases and the second most common cause of workers' claims for occupational injuries. Due to high prevalence of NIHL and several reports of improper use of hearing protective devices (HPDs), we conducted this study to compare the effect of face-to-face training in effective use of earplugs with appropriate NRR to overprotection of workers by using earplugs with higher than necessary noise reduction rating (NRR). In a randomized clinical trial, 150 workers referred to occupational medicine clinic were randomly allocated to three arms---a group wearing earplugs with an NRR of 25 with no training in appropriate use of the device; a group wearing earplugs with an NRR of 25 with training; another group wearing earplugs with an NRR of 30, with no training. Hearing threshold was measured in the study groups by real ear attenuation at threshold (REAT) method. This trial is registered with Australian New Zealand clinical trials Registry, number ACTRN00363175. The mean ± SD age of the participants was 28 ± 5 (range: 19-39) years. 42% of participants were female. The mean noise attenuation in the group with training was 13.88 dB, significantly higher than those observed in other groups. The highest attenuation was observed in high frequencies (4, 6, and 8 kHz) in the group with training. Training in appropriate use of earplugs significantly affects the efficacy of earplugs---even more than using an earplug with higher NRR.

  12. Training in Using Earplugs or Using Earplugs with a Higher than Necessary Noise Reduction Rating? A Randomized Clinical Trial

    Directory of Open Access Journals (Sweden)

    M Salmani Nodoushan

    2014-09-01

    Full Text Available Background: Noise-induced hearing loss (NIHL is one of the most common occupational diseases and the second most common cause of workers' claims for occupational injuries. Objective: Due to high prevalence of NIHL and several reports of improper use of hearing protective devices (HPDs, we conducted this study to compare the effect of face-to-face training in effective use of earplugs with appropriate NRR to overprotection of workers by using earplugs with higher than necessary noise reduction rating (NRR. Methods: In a randomized clinical trial, 150 workers referred to occupational medicine clinic were randomly allocated to three arms—a group wearing earplugs with an NRR of 25 with no training in appropriate use of the device; a group wearing earplugs with an NRR of 25 with training; another group wearing earplugs with an NRR of 30, with no training. Hearing threshold was measured in the study groups by real ear attenuation at threshold (REAT method. This trial is registered with Australian New Zealand clinical trials Registry, number ACTRN00363175. Results: The mean±SD age of the participants was 28±5 (range: 19–39 years. 42% of participants were female. The mean noise attenuation in the group with training was 13.88 dB, significantly higher than those observed in other groups. The highest attenuation was observed in high frequencies (4, 6, and 8 kHz in the group with training. Conclusion: Training in appropriate use of earplugs significantly affects the efficacy of earplugs—even more than using an earplug with higher NRR.

  13. A Tool for Kalman Filter Tuning

    DEFF Research Database (Denmark)

    Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

    2007-01-01

    The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. A method for estimating noise covariances from process data has been investigated. The method gives a least-squares estimate of the noise covariances......, which can be used to compute the Kalman filter gain....

  14. Neuropathic pain: transcranial electric motor cortex stimulation using high frequency random noise. Case report of a novel treatment

    Directory of Open Access Journals (Sweden)

    Alm PA

    2013-06-01

    Full Text Available Per A Alm, Karolina DreimanisDepartment of Neuroscience, Uppsala University, Uppsala, SwedenObjectives: Electric motor cortex stimulation has been reported to be effective for many cases of neuropathic pain, in the form of epidural stimulation or transcranial direct current stimulation (tDCS. A novel technique is transcranial random noise stimulation (tRNS, which increases the cortical excitability irrespective of the orientation of the current. The aim of this study was to investigate the effect of tRNS on neuropathic pain in a small number of subjects, and in a case study explore the effects of different stimulation parameters and the long-term stability of treatment effects.Methods: The study was divided into three phases: (1 a double-blind 100–600 Hz, varying from 0.5 to 10 minutes and from 50 to 1500 µA, at intervals ranging from daily to fortnightly.crossover study, with four subjects; (2 a double-blind extended case study with one responder; and (3 open continued treatment. The motor cortex stimulation consisted of alternating current random noise (100–600 Hz, varying from 0.5 to 10 minutes and from 50 to 1500 μA, at intervals ranging from daily to fortnightly.Results: One out of four participants showed a strong positive effect (also compared with direct-current-sham, P = 0.006. Unexpectedly, this effect was shown to occur also for very weak (100 µA, P = 0.048 and brief (0.5 minutes, P = 0.028 stimulation. The effect was largest during the first month, but remained at a highly motivating level for the patient after 6 months.Discussion: The study suggests that tRNS may be an effective treatment for some cases of neuropathic pain. An important result was the indication that even low levels of stimulation may have substantial effects.Keywords: neuropathic pain, central pain, transcranial direct current stimulation, motor cortex stimulation, random noise stimulation

  15. Image pre-filtering for measurement error reduction in digital image correlation

    Science.gov (United States)

    Zhou, Yihao; Sun, Chen; Song, Yuntao; Chen, Jubing

    2015-02-01

    In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random

  16. Unsteady Fast Random Particle Mesh method for efficient prediction of tonal and broadband noises of a centrifugal fan unit

    Directory of Open Access Journals (Sweden)

    Seung Heo

    2015-09-01

    Full Text Available In this study, efficient numerical method is proposed for predicting tonal and broadband noises of a centrifugal fan unit. The proposed method is based on Hybrid Computational Aero-Acoustic (H-CAA techniques combined with Unsteady Fast Random Particle Mesh (U-FRPM method. The U-FRPM method is developed by extending the FRPM method proposed by Ewert et al. and is utilized to synthesize turbulence flow field from unsteady RANS solutions. The H-CAA technique combined with U-FRPM method is applied to predict broadband as well as tonal noises of a centrifugal fan unit in a household refrigerator. Firstly, unsteady flow field driven by a rotating fan is computed by solving the RANS equations with Computational Fluid Dynamic (CFD techniques. Main source regions around the rotating fan are identified by examining the computed flow fields. Then, turbulence flow fields in the main source regions are synthesized by applying the U-FRPM method. The acoustic analogy is applied to model acoustic sources in the main source regions. Finally, the centrifugal fan noise is predicted by feeding the modeled acoustic sources into an acoustic solver based on the Boundary Element Method (BEM. The sound spectral levels predicted using the current numerical method show good agreements with the measured spectra at the Blade Pass Frequencies (BPFs as well as in the high frequency range. On the more, the present method enables quantitative assessment of relative contributions of identified source regions to the sound field by comparing predicted sound pressure spectrum due to modeled sources.

  17. Communicating the Signal of Climate Change in The Presence of Non-Random Noise

    Science.gov (United States)

    Mann, M. E.

    2015-12-01

    The late Stephen Schneider spoke eloquently of the double ethical bind that we face: we must strive to communicate effectively but honestly. This is no simple task given the considerable "noise" generated in our public discourse by vested interests instead working to misinform the public. To do so, we must convey what is known in plainspoken jargon-free language, while acknowledging the real uncertainties that exist. Further, we must explain the implications of those uncertainties, which in many cases imply the possibility of greater, not lesser, risk. Finally, we must not be averse to discussing the policy implications of the science, lest we fail to provide our audience with critical information that can help them make informed choices about their own actions as citizens. I will use examples from my current collaboration with Washington Post editorial cartoonist Tom Toles.

  18. Single vacancy defect spectroscopy on HfO2 using random telegraph noise signals from scanning tunneling microscopy

    Science.gov (United States)

    Thamankar, R.; Raghavan, N.; Molina, J.; Puglisi, F. M.; O'Shea, S. J.; Shubhakar, K.; Larcher, L.; Pavan, P.; Padovani, A.; Pey, K. L.

    2016-02-01

    Random telegraph noise (RTN) measurements are typically carried out at the device level using standard probe station based electrical characterization setup, where the measured current represents a cumulative effect of the simultaneous response of electron capture/emission events at multiple oxygen vacancy defect (trap) sites. To better characterize the individual defects in the high-κ dielectric thin film, we propose and demonstrate here the measurement and analysis of RTN at the nanoscale using a room temperature scanning tunneling microscope setup, with an effective area of interaction of the probe tip that is as small as 10 nm in diameter. Two-level and multi-level RTN signals due to single and multiple defect locations (possibly dispersed in space and energy) are observed on 4 nm HfO2 thin films deposited on n-Si (100) substrate. The RTN signals are statistically analyzed using the Factorial Hidden Markov Model technique to decode the noise contribution of more than one defect (if any) and estimate the statistical parameters of each RTN signal (i.e., amplitude of fluctuation, capture and emission time constants). Observation of RTN at the nanoscale presents a new opportunity for studies on defect chemistry, single-defect kinetics and their stochastics in thin film dielectric materials. This method allows us to characterize the fast traps with time constants ranging in the millisecond to tens of seconds range.

  19. Two-year follow-up of a randomized trial of spectacles alone or combined with Bangerter filters for treating anisometropic amblyopia.

    Science.gov (United States)

    Agervi, Pia; Kugelberg, Ulla; Kugelberg, Maria; Zetterström, Charlotta

    2013-02-01

    To compare spectacle correction alone to spectacle correction with Bangerter filters as treatments for anisometropic amblyopia in children 1 year after completion of a 1-year randomized trial. In a randomized clinical trial, 80 children (mean age, 4.4 years) with anisometropic amblyopia and a best median visual acuity (VA) in the amblyopic eye of 0.4 logarithm of the minimum angle of resolution (logMAR) were assigned to treatment with either spectacles or spectacles in combination with a Bangerter filter for 1 year. After 1 year, treatment with spectacles continued. If the VA differed by ≥ 2 lines, treatment with Bangerter filters was continued if originally prescribed. The main outcome measure was the median change in VA of the amblyopic eye after 2 years. The median change in VA of the amblyopic eye did not differ significantly between the groups (0.4 log unit for both groups) at the 2-year visit. At that time, the VA in the amblyopic eyes and the fellow eyes was 0.0 median logMAR in both groups. Between years 1 and 2, the median VA improved in the amblyopic eyes; in the spectacles group (p = 0.0181) and in the Bangerter filter group (p = 0.0342). The median anisometropia decreased in both groups (p spectacles alone did not differ significantly from that after treatment with spectacles and a Bangerter filter for anisometropic amblyopia. © 2011 The Authors. Acta Ophthalmologica © 2011 Acta Ophthalmologica Scandinavica Foundation.

  20. Fully automated high-performance signal-to-noise ratio enhancement based on an iterative three-point zero-order Savitzky-Golay filter.

    Science.gov (United States)

    Schulze, H Georg; Foist, Rod B; Ivanov, Andre; Turner, Robin F B

    2008-10-01

    The automated processing of data from high-throughput and real-time collection procedures is becoming a pressing problem. Currently the focus is shifting to automated smoothing techniques where, unlike background subtraction techniques, very few methods exist. We have developed a filter based on the widely used and conceptually simple moving average method or zero-order Savitzky-Golay filter and its iterative relative, the Kolmogorov-Zurbenko filter. A crucial difference, however, between these filters and our implementation is that our fully automated smoothing filter requires no parameter specification or parameter optimization. Results are comparable to, or better than, Savitzky-Golay filters with optimized parameters and superior to the automated iterative median filter. Our approach, because it is based on the highly familiar moving average concept, is intuitive, fast, and straightforward to implement and should therefore be of immediate and considerable practical use in a wide variety of spectroscopy applications.

  1. Conservation laws in coupled multiplicative random arrays lead to $1/f$ noise

    CERN Document Server

    Thurner, S; Teich, M C; Thurner, Stefan; Feurstein, Markus C.; Teich, Malvin C.

    1997-01-01

    We consider the dynamic evolution of a coupled array of N multiplicative random variables. The magnitude of each is constrained by a lower bound w_0 and their sum is conserved. Analytical calculation shows that the simplest case, N=2 and w_0=0, exhibits a Lorentzian spectrum which gradually becomes fractal as w_0 increases. Simulation results for larger $N$ reveal fractal spectra for moderate to high values of w_0 and power-law amplitude fluctuations at all values. The results are applied to estimating the fractal exponents for cochlear-nerve-fiber action-potential sequences with remarkable success, using only two parameters.

  2. Effectiveness of Earplugs in Preventing Recreational Noise-Induced Hearing Loss: A Randomized Clinical Trial.

    Science.gov (United States)

    Ramakers, Geerte G J; Kraaijenga, Véronique J C; Cattani, Guido; van Zanten, Gijsbert A; Grolman, Wilko

    2016-06-01

    The incidence of hearing loss has risen in past years. Attendance at music festivals and concerts may contribute to this increasing problem. To assess the effectiveness of earplugs in preventing temporary hearing loss immediately following music exposure. A randomized, single-blind clinical trial was conducted on September 5, 2015, at an outdoor music festival in Amsterdam, the Netherlands. Normal-hearing adult volunteers were recruited via social media. An exclusion criterion was the participants' intention to wear earplugs. Of the 86 volunteers assessed, 51 were included in the study. All analyses were performed on an intention-to-treat basis. Participants were randomly assigned to a group using earplugs or an unprotected group during a 4½-hour festival visit. The primary study outcome was a temporary threshold shift (TTS) on the audiogram, primarily for frequencies at 3 and 4 kHz. Secondary study outcomes included distortion product otoacoustic emission (DPOAE) measurements and claims of tinnitus using a questionnaire and tinnitus matching experiments. Of 51 participants included, 25 were randomized to the earplug group and 26 to the unprotected group. Nine in each group (36% and 35%, respectively) were men, and the mean (SD) ages were 27.3 (5.6) years in the earplug group and 27.0 (6.2) years in the unprotected group. Baseline demographics were similar in both groups. The time-averaged, equivalent A-weighted sound pressure level experienced was 100 dBA during the festival. A TTS over frequencies at 3 and 4 kHz after exposure was seen in 4 of 50 ears (8%) in the earplug group compared with 22 of 52 ears (42%) in the unprotected group (P earplug group. The number needed to treat with earplugs for preventing 1 TTS was 2.9. The DPOAE amplitudes decreased significantly more over the frequencies 2 to 8 kHz in the unprotected group: the mean (SD) decrease in magnitude was 0.6 (2.8) dB in the earplug group vs 2.2 (1.9) dB in the unprotected group (P = .04

  3. Number of traps and trap depth position on statistical distribution of random telegraph noise in scaled NAND flash memory

    Science.gov (United States)

    Tomita, Toshihiro; Miyaji, Kousuke

    2016-04-01

    The dependence of random telegraph noise (RTN) amplitude distribution on the number of traps and trap depth position is investigated using three-dimensional Monte Carlo device simulation including random dopant fluctuation (RDF) in a 30 nm NAND multi level flash memory. The ΔV th tail distribution becomes broad at fixed double traps, indicating that the number of traps greatly affects the worst RTN characteristics. It is also found that for both fixed single and fixed double traps, the ΔV th distribution in the lowest cell threshold voltage (V th) state shows the broadest distribution among all cell V th states. This is because the drain current flows at the channel surface in the lowest cell V th state, while at a high cell V th, it flows at the deeper position owing to the fringing coupling between the control gate (CG) and the channel. In this work, the ΔV th distribution with the number of traps following the Poisson distribution is also considered to cope with the variations in trap number. As a result, it is found that the number of traps is an important factor for understanding RTN characteristics. In addition, considering trap position in the tunnel oxide thickness direction is also an important factor.

  4. Sample-whitened matched filters

    DEFF Research Database (Denmark)

    Andersen, Ib

    1973-01-01

    A sample-whitened matched filter (SWMF) for a channel with intersymbol interference and additive white Gaussian noise is defined as a linear filter with the properties that its output samples are a sufficient statistic for the MAP estimation of the transmitted sequence and have uncorrelated noise...

  5. Point process analysis of noise in early invertebrate vision.

    Directory of Open Access Journals (Sweden)

    Kris V Parag

    2017-10-01

    Full Text Available Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps. Here, randomness of both the photon inputs (regarded as extrinsic noise and the conversion process (intrinsic noise are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance. This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter and shape (amplitude and width variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this

  6. Between Noise and Silence: Architecture since the 1970s

    Directory of Open Access Journals (Sweden)

    Alexandra Brown

    2012-12-01

    Full Text Available This essay considers noise in architectural discourse as it might lend form to issues hitherto tabled in rather different terms. We ask what noise offers this discussion or, perhaps better put, what seeing architectural debates in terms of distinctions between noise and silence, random and structured sound, silence as absence and pregnant void might add to disciplinary debates within architectural theory and criticism. By treating these acoustic values analogously rather than literally we wish to suggest that reading the late postmodern moment through this filter opens out new possibilities for a critical assessment of this period and its present-day legacies.

  7. Digital filters

    CERN Document Server

    Hamming, Richard W

    1997-01-01

    Digital signals occur in an increasing number of applications: in telephone communications; in radio, television, and stereo sound systems; and in spacecraft transmissions, to name just a few. This introductory text examines digital filtering, the processes of smoothing, predicting, differentiating, integrating, and separating signals, as well as the removal of noise from a signal. The processes bear particular relevance to computer applications, one of the focuses of this book.Readers will find Hamming's analysis accessible and engaging, in recognition of the fact that many people with the s

  8. Treatment of neonatal jaundice with filtered sunlight in Nigerian neonates: study protocol of a non-inferiority, randomized controlled trial.

    Science.gov (United States)

    Slusher, Tina M; Olusanya, Bolajoko O; Vreman, Hendrik J; Wong, Ronald J; Brearley, Ann M; Vaucher, Yvonne E; Stevenson, David K

    2013-12-28

    Severe neonatal jaundice and its progression to kernicterus is a leading cause of death and disability among newborns in poorly-resourced countries, particularly in sub-Saharan Africa. The standard treatment for jaundice using conventional phototherapy (CPT) with electric artificial blue light sources is often hampered by the lack of (functional) CPT devices due either to financial constraints or erratic electrical power. In an attempt to make phototherapy (PT) more readily available for the treatment of pathologic jaundice in underserved tropical regions, we set out to test the hypothesis that filtered sunlight phototherapy (FS-PT), in which potentially harmful ultraviolet and infrared rays are appropriately screened, will be as efficacious as CPT. This prospective, non-blinded randomized controlled non-inferiority trial seeks to enroll infants with elevated total serum/plasma bilirubin (TSB, defined as 3 mg/dl below the level recommended by the American Academy of Pediatrics for high-risk infants requiring PT) who will be randomly and equally assigned to receive FS-PT or CPT for a total of 616 days at an inner-city maternity hospital in Lagos, Nigeria. Two FS-PT canopies with pre-tested films will be used. One canopy with a film that transmits roughly 33% blue light (wavelength range: 400 to 520 nm) will be used during sunny periods of a day. Another canopy with a film that transmits about 79% blue light will be used during overcast periods of the day. The infants will be moved from one canopy to the other as needed during the day with the goal of keeping the blue light irradiance level above 8 μW/cm²/nm. FS-PT will be as efficacious as CPT in reducing the rate of rise in bilirubin levels. Secondary outcome: The number of infants requiring exchange transfusion under FS-PT will not be more than those under CPT. This novel study offers the prospect of an effective treatment for infants at risk of severe neonatal jaundice and avoidable exchange transfusion in

  9. Random genetic drift, natural selection, and noise in human cranial evolution.

    Science.gov (United States)

    Roseman, Charles C

    2016-08-01

    This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  10. A Cluster Randomized Controlled Trial to Reduce Childhood Diarrhea Using Hollow Fiber Water Filter and/or Hygiene–Sanitation Educational Interventions

    OpenAIRE

    Lindquist, Erik D.; George, C. M.; Perin, Jamie; Neiswender de Calani, Karen J.; Norman, W. Ray; Davis, Thomas P.; Perry, Henry

    2014-01-01

    Safe domestic potable water supplies are urgently needed to reduce childhood diarrheal disease. In periurban neighborhoods in Cochabamba, Bolivia, we conducted a cluster randomized controlled trial to evaluate the efficacy of a household-level hollow fiber filter and/or behavior change communication (BCC) on water, sanitation, and hygiene (WASH) to reduce the diarrheal disease in children less than 5 years of age. In total, 952 households were followed for a period of 12 weeks post-distributi...

  11. Robust random telegraph conductivity noise in single crystals of the ferromagnetic insulating manganite La0.86Ca0.14MnO3

    Science.gov (United States)

    Przybytek, J.; Fink-Finowicki, J.; Puźniak, R.; Shames, A.; Markovich, V.; Mogilyansky, D.; Jung, G.

    2017-03-01

    Robust random telegraph conductivity fluctuations have been observed in La0.86Ca0.14MnO3 manganite single crystals. At room temperatures, the spectra of conductivity fluctuations are featureless and follow a 1 /f shape in the entire experimental frequency and bias range. Upon lowering the temperature, clear Lorentzian bias-dependent excess noise appears on the 1 /f background and eventually dominates the spectral behavior. In the time domain, fully developed Lorentzian noise appears as pronounced two-level random telegraph noise with a thermally activated switching rate, which does not depend on bias current and applied magnetic field. The telegraph noise is very robust and persists in the exceptionally wide temperature range of more than 50 K. The amplitude of the telegraph noise decreases exponentially with increasing bias current in exactly the same manner as the sample resistance increases with the current, pointing out the dynamic current redistribution between percolation paths dominated by phase-separated clusters with different conductivity as a possible origin of two-level conductivity fluctuations.

  12. Faraday anomalous dispersion optical filters

    Science.gov (United States)

    Shay, T. M.; Yin, B.; Alvarez, L. S.

    1993-01-01

    The effect of Faraday anomalous dispersion optical filters on infrared and blue transitions of some alkali atoms is calculated. A composite system is designed to further increase the background noise rejection. The measured results of the solar background rejection and image quality through the filter are presented. The results show that the filter may provide high transmission and high background noise rejection with excellent image quality.

  13. A filter bank for rotationally invariant image recognition

    Directory of Open Access Journals (Sweden)

    S Rodtook

    2005-12-01

    Full Text Available We present new rotation moment invariants based on multiresolution filter bank techniques. The multiresolution pyramid motivates our simple but efficient feature selection procedure based on the fuzzy C-mean clustering methodology combined with the Mahalanobis distance measure. The proposed procedure verifies an impact of random noise as well as an interesting, less known impact of noise due to spatial transformations. The recognition accuracy of the proposed technique has been tested with the Zernike moments, the Fourier-Mellin moments as well as with wavelet based schemes. The numerical experiments, with more than 30 000 images, demonstrate a tangible accuracy increase of about 3% for low level noise, 8% for the average level noise and 15% for high level noise.

  14. Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.

    Science.gov (United States)

    Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

    2015-10-14

    In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

  15. Low-Pass Parabolic FFT Filter for Airborne and Satellite Lidar Signal Processing

    Directory of Open Access Journals (Sweden)

    Zhongke Jiao

    2015-10-01

    Full Text Available In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF, median filter (MF, empirical mode decomposition (EMD and wavelet transform (WT were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL. Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

  16. Analysis of magnetic random telegraph noise in individual arrangements of a small number of coupled MnAs nanoclusters

    Science.gov (United States)

    Fischer, Martin; Elm, Matthias T.; Kato, Hiroaki; Sakita, Shinya; Hara, Shinjiro; Klar, Peter J.

    2015-10-01

    The temporal dependence of the resistance of MnAs nanocluster arrangements grown by selective-area metal-organic vapor-phase epitaxy is investigated at different temperatures. The resistance of such arrangements exhibits random telegraph noise with jumps between discrete resistance levels. The effect is attributed to thermally activated switching of the magnetic domain structure resulting in alterations of spin-dependent scattering between the MnAs clusters of the arrangements. The behavior can be qualitatively understood by a simple model in which it is assumed that the nanocluster arrangement consists of three domains in accordance with investigations by magnetic force microscopy. The magnetizations of the outer larger domains remain fixed, whereas the magnetization of a smaller intermediate domain (or domain wall) exhibits thermally activated switching between local minima of its energy landscape. The results of the model indicate that the time scale of an actual switching event of the entire intermediate domain comprises the nucleation of a seed domain consisting of a few thousand Mn spins followed by the transformation of the entire domain by domain-wall motion in order to reorient its magnetization.

  17. Transcranial random noise stimulation and cognitive training to improve learning and cognition of the atypically developing brain: A pilot study.

    Science.gov (United States)

    Looi, Chung Yen; Lim, Jenny; Sella, Francesco; Lolliot, Simon; Duta, Mihaela; Avramenko, Alexander Alexandrovich; Cohen Kadosh, Roi

    2017-07-05

    Learning disabilities that affect about 10% of human population are linked to atypical neurodevelopment, but predominantly treated by behavioural interventions. Behavioural interventions alone have shown little efficacy, indicating limited success in modulating neuroplasticity, especially in brains with neural atypicalities. Even in healthy adults, weeks of cognitive training alone led to inconsistent generalisable training gains, or "transfer effects" to non-trained materials. Meanwhile, transcranial random noise stimulation (tRNS), a painless and more direct neuromodulation method was shown to further promote cognitive training and transfer effects in healthy adults without harmful effects. It is unknown whether tRNS on the atypically developing brain might promote greater learning and transfer outcomes than training alone. Here, we show that tRNS over the bilateral dorsolateral prefrontal cortices (dlPFCs) improved learning and performance of children with mathematical learning disabilities (MLD) during arithmetic training compared to those who received sham (placebo) tRNS. Training gains correlated positively with improvement on a standardized mathematical diagnostic test, and this effect was strengthened by tRNS. These findings mirror those in healthy adults, and encourage replications using larger cohorts. Overall, this study offers insights into the concept of combining tRNS and cognitive training for improving learning and cognition of children with learning disabilities.

  18. The application of online transcranial random noise stimulation and perceptual learning in the improvement of visual functions in mild myopia.

    Science.gov (United States)

    Camilleri, Rebecca; Pavan, Andrea; Campana, Gianluca

    2016-08-01

    It has recently been demonstrated how perceptual learning, that is an improvement in a sensory/perceptual task upon practice, can be boosted by concurrent high-frequency transcranial random noise stimulation (tRNS). It has also been shown that perceptual learning can generalize and produce an improvement of visual functions in participants with mild refractive defects. By using three different groups of participants (single-blind study), we tested the efficacy of a short training (8 sessions) using a single Gabor contrast-detection task with concurrent hf-tRNS in comparison with the same training with sham stimulation or hf-tRNS with no concurrent training, in improving visual acuity (VA) and contrast sensitivity (CS) of individuals with uncorrected mild myopia. A short training with a contrast detection task is able to improve VA and CS only if coupled with hf-tRNS, whereas no effect on VA and marginal effects on CS are seen with the sole administration of hf-tRNS. Our results support the idea that, by boosting the rate of perceptual learning via the modulation of neuronal plasticity, hf-tRNS can be successfully used to reduce the duration of the perceptual training and/or to increase its efficacy in producing perceptual learning and generalization to improved VA and CS in individuals with uncorrected mild myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. A curvature filter and PDE based non-uniformity correction algorithm

    Science.gov (United States)

    Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui; Yin, Shimin

    2016-10-01

    In this paper, a curvature filter and PDE based non-uniformity correction algorithm is proposed, the key point of this algorithm is the way to estimate FPN. We use anisotropic diffusion to smooth noise and Gaussian curvature filter to extract the details of original image. Then combine these two parts together by guided image filter and subtract the result from original image to get the crude approximation of FPN. After that, a Temporal Low Pass Filter (TLPF) is utilized to filter out random noise and get the accurate FPN. Finally, subtract the FPN from original image to achieve non-uniformity correction. The performance of this algorithm is tested with two infrared image sequences, and the experimental results show that the proposed method achieves a better non-uniformity correction performance.

  20. The effects of noise vocoding on speech quality perception.

    Science.gov (United States)

    Anderson, Melinda C; Arehart, Kathryn H; Kates, James M

    2014-03-01

    Speech perception depends on access to spectral and temporal acoustic cues. Temporal cues include slowly varying amplitude changes (i.e. temporal envelope, TE) and quickly varying amplitude changes associated with the center frequency of the auditory filter (i.e. temporal fine structure, TFS). This study quantifies the effects of TFS randomization through noise vocoding on the perception of speech quality by parametrically varying the amount of original TFS available above 1500Hz. The two research aims were: 1) to establish the role of TFS in quality perception, and 2) to determine if the role of TFS in quality perception differs between subjects with normal hearing and subjects with sensorineural hearing loss. Ratings were obtained from 20 subjects (10 with normal hearing and 10 with hearing loss) using an 11-point quality scale. Stimuli were processed in three different ways: 1) A 32-channel noise-excited vocoder with random envelope fluctuations in the noise carrier, 2) a 32-channel noise-excited vocoder with the noise-carrier envelope smoothed, and 3) removal of high-frequency bands. Stimuli were presented in quiet and in babble noise at 18dB and 12dB signal-to-noise ratios. TFS randomization had a measurable detrimental effect on quality ratings for speech in quiet and a smaller effect for speech in background babble. Subjects with normal hearing and subjects with sensorineural hearing loss provided similar quality ratings for noise-vocoded speech. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Generalized Selection Weighted Vector Filters

    Directory of Open Access Journals (Sweden)

    Rastislav Lukac

    2004-09-01

    Full Text Available This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03 in Grado, Italy.

  2. FPGA implementation of filtered image using 2D Gaussian filter

    OpenAIRE

    Leila kabbai; Anissa Sghaier; Ali Douik; Mohsen Machhout

    2016-01-01

    Image filtering is one of the very useful techniques in image processing and computer vision. It is used to eliminate useless details and noise from an image. In this paper, a hardware implementation of image filtered using 2D Gaussian Filter will be present. The Gaussian filter architecture will be described using a different way to implement convolution module. Thus, multiplication is in the heart of convolution module, for this reason, three different ways to implement multiplication opera...

  3. Estimation of signal-to-noise - A new procedure applied to AVIRIS data

    Science.gov (United States)

    Curran, Paul J.; Dungan, Jennifer L.

    1989-01-01

    To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

  4. A Cluster Randomized Controlled Trial to Reduce Childhood Diarrhea Using Hollow Fiber Water Filter and/or Hygiene–Sanitation Educational Interventions

    Science.gov (United States)

    Lindquist, Erik D.; George, C. M.; Perin, Jamie; Neiswender de Calani, Karen J.; Norman, W. Ray; Davis, Thomas P.; Perry, Henry

    2014-01-01

    Safe domestic potable water supplies are urgently needed to reduce childhood diarrheal disease. In periurban neighborhoods in Cochabamba, Bolivia, we conducted a cluster randomized controlled trial to evaluate the efficacy of a household-level hollow fiber filter and/or behavior change communication (BCC) on water, sanitation, and hygiene (WASH) to reduce the diarrheal disease in children less than 5 years of age. In total, 952 households were followed for a period of 12 weeks post-distribution of the study interventions. Households using Sawyer PointONE filters had significantly less diarrheal disease compared with the control arm during the intervention period, which was shown by diarrheal prevalence ratios of 0.21 (95% confidence interval [95% CI] = 0.15–0.30) for the filter arm and 0.27 (95% CI = 0.22–0.34) for the filter and WASH BCC arm. A non-significant reduction in diarrhea prevalence was reported in the WASH BCC study arm households (0.71, 95% CI = 0.59–0.86). PMID:24865680

  5. A cluster randomized controlled trial to reduce childhood diarrhea using hollow fiber water filter and/or hygiene-sanitation educational interventions.

    Science.gov (United States)

    Lindquist, Erik D; George, C M; Perin, Jamie; Neiswender de Calani, Karen J; Norman, W Ray; Davis, Thomas P; Perry, Henry

    2014-07-01

    Safe domestic potable water supplies are urgently needed to reduce childhood diarrheal disease. In periurban neighborhoods in Cochabamba, Bolivia, we conducted a cluster randomized controlled trial to evaluate the efficacy of a household-level hollow fiber filter and/or behavior change communication (BCC) on water, sanitation, and hygiene (WASH) to reduce the diarrheal disease in children less than 5 years of age. In total, 952 households were followed for a period of 12 weeks post-distribution of the study interventions. Households using Sawyer PointONE filters had significantly less diarrheal disease compared with the control arm during the intervention period, which was shown by diarrheal prevalence ratios of 0.21 (95% confidence interval [95% CI] = 0.15-0.30) for the filter arm and 0.27 (95% CI = 0.22-0.34) for the filter and WASH BCC arm. A non-significant reduction in diarrhea prevalence was reported in the WASH BCC study arm households (0.71, 95% CI = 0.59-0.86). © The American Society of Tropical Medicine and Hygiene.

  6. Impulse Detectors for Noised Sequences

    Directory of Open Access Journals (Sweden)

    R. Lukac

    2001-06-01

    Full Text Available This paper is focused on a problem of impulse detection in thedynamic image environments corrupted by impulse noise. Using a proposedarchitecture that includes an impulse detector and the median filter,the effective methods can be designed. Thus, the image points areclassified into two classes such as a class of noise free samples and aclass of noised image points. In the case of impulse detection theestimate is performed by a median filter whereas a noise free sample ispassed on the output without the change i.e. system works as anidentity filter.

  7. Filtering of Interferometric SAR Phase Images as a Fuzzy Matching-Pursuit Blind Estimation

    Directory of Open Access Journals (Sweden)

    Luciano Alparone

    2005-12-01

    Full Text Available We present an original application of fuzzy logic to restoration of phase images from interferometric synthetic aperture radar (InSAR, which are affected by zero-mean uncorrelated noise, whose variance depends on the underlying coherence, thereby yielding a nonstationary random noise process. Spatial filtering of the phase noise is recommended, either before phase unwrapping is accomplished, or simultaneously with it. In fact, phase unwrapping basically relies on a smoothness constraint of the phase field, which is severely hampered by the noise. Space-varying linear MMSE estimation is stated as a problem of matching pursuit, in which the estimator is obtained as an expansion in series of a finite number of prototype estimators, fitting the spatial features of the different statistical classes encountered, for example, fringes and steep slope areas. Such estimators are calculated in a fuzzy fashion through an automatic training procedure. The space-varying coefficients of the expansion are stated as degrees of fuzzy membership of a pixel to each of the estimators. Neither a priori knowledge on the noise variance is required nor particular signal and noise models are assumed. Filtering performances on simulated phase images show a steady SNR improvement over conventional box filtering. Applications of the proposed filter to interferometric phase images demonstrate a superior ability of restoring fringes yet preserving their discontinuities, together with an effective noise smoothing performance, irrespective of locally varying coherence characteristics.

  8. Influence of correspondence noise and spatial scaling on the upper limit for spatial displacement in fully-coherent random-dot kinematogram stimuli.

    Directory of Open Access Journals (Sweden)

    Srimant P Tripathy

    Full Text Available Correspondence noise is a major factor limiting direction discrimination performance in random-dot kinematograms. In the current study we investigated the influence of correspondence noise on Dmax, which is the upper limit for the spatial displacement of the dots for which coherent motion is still perceived. Human direction discrimination performance was measured, using 2-frame kinematograms having leftward/rightward motion, over a 200-fold range of dot-densities and a four-fold range of dot displacements. From this data Dmax was estimated for the different dot densities tested. A model was proposed to evaluate the correspondence noise in the stimulus. This model summed the outputs of a set of elementary Reichardt-type local detectors that had receptive fields tiling the stimulus and were tuned to the two directions of motion in the stimulus. A key assumption of the model was that the local detectors would have the radius of their catchment areas scaled with the displacement that they were tuned to detect; the scaling factor k linking the radius to the displacement was the only free parameter in the model and a single value of k was used to fit all of the psychophysical data collected. This minimal, correspondence-noise based model was able to account for 91% of the variability in the human performance across all of the conditions tested. The results highlight the importance of correspondence noise in constraining the largest displacement that can be detected.

  9. Noise suppression by noise

    OpenAIRE

    Vilar, J. M. G.; Rubí Capaceti, José Miguel

    2001-01-01

    We have analyzed the interplay between an externally added noise and the intrinsic noise of systems that relax fast towards a stationary state, and found that increasing the intensity of the external noise can reduce the total noise of the system. We have established a general criterion for the appearance of this phenomenon and discussed two examples in detail.

  10. Time-Dependent Noise in GPS Position Time Series By a Network Noise Estimator

    Science.gov (United States)

    Dmitrieva, K.; Segall, P.

    2014-12-01

    Some current estimates of GPS velocity uncertainties for continuous stations with more than a decade of data can be very low, noise, such as random walk. Traditional estimators, based on individual time series, are insensitive to low amplitude random walk, yet such noise significantly increases GPS velocity uncertainties. We develop a new approach to estimating noise in GPS time series, focusing on areas where the signal in the data is well characterized. We analyze data from the seismically inactive parts of central US. The data is decomposed into signal, plate rotation and Glacial Isostatic Adjustment (GIA), and various noise components. Our method processes multiple stations simultaneously with a Kalman Filter, and estimates average noise components for the network by maximum likelihood. Currently, we model white noise, flicker noise and random walk. Synthetic tests show that this approach correctly estimates the velocity uncertainty by determining a good estimate of random walk variance, even when it is too small to be correctly estimated by traditional approaches. We present preliminary results from a network of 15 GPS stations in the central USA. The data is in a North America fixed reference frame, we subtract seasonal components and GIA displacements used in the SNARF model. Hence, all data in this reference frame is treated as noise. We estimate random walk of 0.82 mm/yr0.5, flicker noise of 3.96 mm/yr0.25 and white noise of 1.05 mm. From these noise parameters the estimated velocity uncertainty is 0.29 mm/yr for 10 years of daily data. This uncertainty is significantly greater than estimated by the traditional methods, at 0.12 mm/yr. The estimated uncertainty is still less than the median residual velocity in the North America fixed reference frame, which could indicate that the true uncertainties are even larger. Additionally we estimated noise parameters and velocity uncertainties for the vertical component and for the data with common-mode signal

  11. A LBL Positioning Method Based on Feedback Kalman Filter

    Directory of Open Access Journals (Sweden)

    Jucheng Zhang

    2014-01-01

    Full Text Available LBL (Long Basic Line positioning is an important and high-precision method for underwater vehicle navigation. Due to its narrow work frequency-band, system would be easily affected by external factors and gave wrong results. A new Kalman filter model based on the feedback from travel time and position information was presented in this paper. By combining travel time with positioning in the Kalman filter, the navigation state of underwater vehicle was accurately estimated. Experimental results show that the influence of random high-frequency measurement noise on positioning results was effectively solved and the navigation precision was improved.

  12. Critical ratios in harbor porpoises (Phocoena phocoena) for tonal signals between 0.315 and 150 kHz in random Gaussian white noise.

    Science.gov (United States)

    Kastelein, Ronald A; Wensveen, Paul J; Hoek, Lean; Au, Whitlow W L; Terhune, John M; de Jong, Christ A F

    2009-09-01

    A psychoacoustic behavioral technique was used to determine the critical ratios (CRs) of two harbor porpoises for tonal signals with frequencies between 0.315 and 150 kHz, in random Gaussian white noise. The masked 50% detection hearing thresholds were measured using a "go/no-go" response paradigm and an up-down staircase psychometric method. CRs were determined at one masking noise level for each test frequency and were similar in both animals. For signals between 0.315 and 4 kHz, the CRs were relatively constant at around 18 dB. Between 4 and 150 kHz the CR increased gradually from 18 to 39 dB ( approximately 3.3 dB/octave). Generally harbor porpoises can detect tonal signals in Gaussian white noise slightly better than most odontocetes tested so far. By combining the mean CRs found in the present study with the spectrum level of the background noise levels at sea, the basic audiogram, and the directivity index, the detection threshold levels of harbor porpoises for tonal signals in various sea states can be calculated.

  13. Noise upon the Sinusoids

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2005-01-01

    Sinusoids are used for making harmonic and other sounds. In order to having life in the sounds and adding a wide variety of noises, irregularities are inserted in the frequency and amplitudes. A simple and intuitive noise model is presented, consisting of a low-pass filtered noise, and having...... control for strength and bandwidth. The noise is added on the frequency and amplitudes of the sinusoids, and the resulting irregularity’s (jitter and shimmer) bandwidth is derived. This, together with an overview of investigation methods of the jitter and shimmer results in an analysis of the necessary...

  14. The Dependence of Signal-To-Noise Ratio (S/N) Between Star Brightness and Background on the Filter Used in Images Taken by the Vulcan Photometric Planet Search Camera

    Science.gov (United States)

    Mena-Werth, Jose

    1998-01-01

    The Vulcan Photometric Planet Search is the ground-based counterpart of Kepler Mission Proposal. The Kepler Proposal calls for the launch of telescope to look intently at a small patch of sky for four year. The mission is designed to look for extra-solar planets that transit sun-like stars. The Kepler Mission should be able to detect Earth-size planets. This goal requires an instrument and software capable of detecting photometric changes of several parts per hundred thousand in the flux of a star. The goal also requires the continuous monitoring of about a hundred thousand stars. The Kepler Mission is a NASA Discovery Class proposal similar in cost to the Lunar Prospector. The Vulcan Search is also a NASA project but based at Lick Observatory. A small wide-field telescope monitors various star fields successively during the year. Dozens of images, each containing tens of thousands of stars, are taken any night that weather permits. The images are then monitored for photometric changes of the order of one part in a thousand. These changes would reveal the transit of an inner-orbit Jupiter-size planet similar to those discovered recently in spectroscopic searches. In order to achieve a one part in one thousand photometric precision even the choice of a filter used in taking an exposure can be critical. The ultimate purpose of an filter is to increase the signal-to-noise ratio (S/N) of one's observation. Ideally, filters reduce the sky glow cause by street lights and, thereby, make the star images more distinct. The higher the S/N, the higher is the chance to observe a transit signal that indicates the presence of a new planet. It is, therefore, important to select the filter that maximizes the S/N.

  15. Wiener filter for filtered back projection in digital breast tomosynthesis

    Science.gov (United States)

    Wang, Xinying; Mainprize, James G.; Wu, Gang; Yaffe, Martin J.

    2012-03-01

    Conventional filtered back projection (FBP) reconstruction for digital breast tomosynthesis (DBT) can suffer from a low signal to noise ratio. Because of the strong amplification by the reconstruction filters (ramp, apodization and slice thickness), noise at high spatial frequencies can be greatly increased. Image enhancement by Wiener filtering is investigated as a possible method to improve image quality. A neighborhood wavelet coefficient window technique is used to estimate the noise content of projection images and a Wiener filter is applied to the projection images. The neighborhood wavelet coefficient window is a non-linear technique, which may cause the Wiener filters estimated before and after the application of the reconstruction filters to be different. Image quality of a FBP reconstruction with and without Wiener filtering is investigated using a Fourier-based observer detectability metric ( d' ) for evaluation. Simulations of tomosynthesis are performed in both homogeneous and anatomic textured backgrounds containing lowcontrast masses or small microcalcifications. Initial results suggest that improvements in detectability can be achieved when the Wiener filter is applied, especially when the Wiener filter is estimated for the reconstruction filtered projections.

  16. Noise Cancellation in ECG Signals using Computationally

    OpenAIRE

    D.V. Rama Koti Reddy; Mohammad Zia Ur Rahman; Rafi Ahamed Shaik

    2009-01-01

    Several signed LMS based adaptive filters, which are computationally superior having multiplier free weight update loops are proposed for noise cancellation in the ECG signal. The adaptive filters essentially minimizes the mean-squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Different filter structures...

  17. A pseudo-matched filter for chaos

    OpenAIRE

    Cohen, Seth D.; Gauthier, Daniel J.

    2012-01-01

    A matched filter maximizes the signal-to-noise ratio of a signal. In the recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is derived for the chaotic waveforms produced by a piecewise-linear system. Motivated by these results, we describe a pseudo-matched filter, which removes noise from the same chaotic signal. It consists of a notch filter followed by a first-order, low-pass filter. We compare quantitatively the matched filter's performance to that of our pseudo-match...

  18. Polarisation filtering of magnetotelluric data - Using an advanced wavelet processing scheme to discriminate between contribution of signal and noise to the data

    Science.gov (United States)

    Schmoldt, J.; Jones, A. G.; Garcia, X. A.

    2009-12-01

    The magnetotelluric (MT) method investigates the structure of the Earth by studying its vertical and lateral electric conductivity distribution. For that purpose natural electromagnetic (EM) fields are measured at Earth’s surface, and thus derive a spatially and frequency dependent impedance response function that can be modelled in terms of Earth structure. Long period natural EM fields (>1 s) are generated by the interaction of electrical charged particles radiated from the Sun with the Earth’s magnetosphere and ionosphere. In phases of low solar activity the source signal for MT is weak, especially at longer periods (>1,000 s) and the effects of noise can result in poor response function estimates. A significant contribution to noise can be cultural sources fixed in space, such as mining areas, electric fences and television transmitters. Electromagnetic waves generated by such sources exhibit a preferential polarisation ellipticity and direction that differs from the natural signals generated at the Earth’s outer magnetosphere and ionosphere. In MT, the ellipticity and direction of the polarisation can be determined because the magnetic component of the electromagnetic field is measured in orthogonal directions. In addition, the continuous wavelet transform (CWT) analysis is an efficient way to localize segments of chosen polarisation in the recorded dataset in both time and frequency. We have developed an algorithm that selects data segments according to their polarisation properties allowing us to improve the signal-to-noise ratio of MT responses. After rejecting segments of certain polarisation direction and therefore low signal-to-noise ratio for the signals we wish to record, the remaining data can be used for subsequent conventional MT processing. Using synthetic data and a MT dataset collected during the PICASSO fieldwork campaign in Spain in 2007, we test our pre-processing algorithm. In this paper we present a comparative analysis and results

  19. Estimates of Small Signal/Noise Ratios

    Science.gov (United States)

    Howard, L. D.

    1985-01-01

    Signal/Noise Ratio Meter measures ratio of signal power to noise power in input that contains both signal and noise. Signal and noise first filtered and normalized in analog circuitry, then digitized and sampled. Performance of SNR meter determined by statistical algorithm chosen for analysis of samples.

  20. On the attenuation and amplification of molecular noise in genetic regulatory networks

    Directory of Open Access Journals (Sweden)

    Wang Yu-Chao

    2006-02-01

    Full Text Available Abstract Background Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanisms of genetic regulatory networks to attenuate the molecular noise to achieve regulatory ability or to amplify the molecular noise to randomize outcomes to the advantage of diversity. Therefore, the noise filtering of genetic regulatory network is an important topic for gene networks under intrinsic fluctuation and extrinsic noise. Results Based on stochastic dynamic regulation equation, the intrinsic fluctuation in reaction rates is modeled as a state-dependent stochastic process, which will influence the stability of gene regulatory network, especially, with low concentrations of reacting species. Then the mechanisms of genetic regulatory network to attenuate or amplify extrinsic fluctuation are revealed from the nonlinear stochastic filtering point of view. Furthermore, a simple measure of attenuation level or amplification level of extrinsic noise for genetic regulatory networks is also introduced by nonlinear robust filtering method. Based on the global linearization scheme, a convenient method is introduced to measure noise attenuation or amplification for each gene of the nonlinear stochastic regulatory network by solving a set of filtering problems, which correspond to a set of linearized stochastic regulatory networks. Finally, by the proposed methods, several simulation examples of genetic regulatory networks are given to measure their robust stability under intrinsic fluctuations, and to estimate the genes' attenuation and amplification levels under extrinsic noises. Conclusion In this study, a stochastic nonlinear dynamic model is developed for genetic regulatory networks under intrinsic fluctuation and extrinsic noise. By the method we proposed, we could determine the robust stability under intrinsic fluctuations and identify the genes that are

  1. Dip filters; Filtros de echado recursivos

    Energy Technology Data Exchange (ETDEWEB)

    Cabrales Vargas, A.; Chavez Perez, S. [Facultad de Ingenieria, UNAM, Mexico, D.F. (Mexico)

    2002-09-01

    In exploration seismology, dip filters are used to enhance subsoil images by attenuating coherent noise and other signals. They can be applied in frequency-wavenumber (f-k), frequency-distance (f-x), time-wavenumber (t-k) or time distance (t-k) domains. Fourier domain assumes constant dips. Recursive dip filters are applied in t-x domain, as they do not have this limitation. However, we have to determine their optimal parameters by trial and error. Recursive dip filters are based on single order Butterworth filters, by adding the wavenumber. Their amplitude spectrum is a surface. We perform a bilinear transform to digitize the filter and pass from the f-k to the t-k domain. We obtain the t-x domain filter by inverse transforming through wavenumber and by using a three-coefficient approximation (leading to a tridiagonal matrix). For the sake of illustration in geophysical engineering, we apply these filters to a shallow field record, to attenuate the air wave and random noise, and to a marine seismic section to enhance a fault zone. Both examples show that these filters are useful and practical to enhance seismic data. Their use is easier and more economical than median filters, utilized nowadays in commercial software for the oil industry. [Spanish] En sismologia de exploracion, los filtros de echado se utilizan para enfatizar imagenes del subsuelo, atenuado ruido coherente y otras senales. Pueden aplicarse en los dominios de frecuencia y numero de onda (f-k), frecuencia y distancia (f-x), tiempo y numero de onda (t-k) o tiempo y distancia (t-x). En el dominio de Fourier suponemos echados constantes. Los filtros de echado recursivos se aplican en el dominio t-x, careciendo de esta limitante. Sin embargo, tenemos que recurrir al ensayo y error para determinar sus parametros optimos. Los filtros de hecho recursivos se basan en filtros de Butterworth de orden uno, anadiendo el numero de onda. Su espectro de amplitud es una superficie. Utilizamos la trasformada

  2. Efficacy of low-level laser therapy in the management of tinnitus due to noise-induced hearing loss: a double-blind randomized clinical trial.

    Science.gov (United States)

    Mollasadeghi, Abolfazl; Mirmohammadi, Seyyed Jalil; Mehrparvar, Amir Houshang; Davari, Mohammad Hossein; Shokouh, Pedram; Mostaghaci, Mehrdad; Baradaranfar, Mohammad Hossein; Bahaloo, Maryam

    2013-01-01

    Background. Several remedial modalities for the treatment of tinnitus have been proposed, but an effective standard treatment is still to be confirmed. In the present study, we aimed to evaluate the effect of low-level laser therapy on tinnitus accompanied by noise-induced hearing loss. Methods. This was a double-blind randomized clinical trial on subjects suffering from tinnitus accompanied by noise-induced hearing loss. The study intervention was 20 sessions of low-level laser therapy every other day, 20 minutes each session. Tinnitus was assessed by three methods (visual analog scale, tinnitus handicap inventory, and tinnitus loudness) at baseline, immediately and 3 months after the intervention. Results. All subjects were male workers with age range of 30-51 years. The mean tinnitus duration was 1.85 ± 0.78 years. All three measurement methods have shown improved values after laser therapy compared with the placebo both immediately and 3 months after treatment. Laser therapy revealed a U-shaped efficacy throughout the course of follow-up. Nonresponse rate of the intervention was 57% and 70% in the two assessment time points, respectively. Conclusion. This study found low-level laser therapy to be effective in alleviating tinnitus in patients with noise-induced hearing loss, although this effect has faded after 3 months of follow-up. This trial is registered with the Australian New Zealand clinical trials registry with identifier ACTRN12612000455864).

  3. Image enhancement and performance evaluation using various filters for IRS-P6 Satellite Liss IV remotely sensed data

    OpenAIRE

    Kumar, T. Ganesh; Murugan, D.; Rajalakshmi, K.; Manish, T. I.

    2015-01-01

    This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic filter and selected noises salt and pepper and Gaussian noise used with filter. Selected images tested...

  4. Boundary Value Problems Arising in Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Bashirov Agamirza

    2008-01-01

    Full Text Available The classic Kalman filtering equations for independent and correlated white noises are ordinary differential equations (deterministic or stochastic with the respective initial conditions. Changing the noise processes by taking them to be more realistic wide band noises or delayed white noises creates challenging partial differential equations with initial and boundary conditions. In this paper, we are aimed to give a survey of this connection between Kalman filtering and boundary value problems, bringing them into the attention of mathematicians as well as engineers dealing with Kalman filtering and boundary value problems.

  5. Boundary Value Problems Arising in Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Sinem Ertürk

    2009-01-01

    Full Text Available The classic Kalman filtering equations for independent and correlated white noises are ordinary differential equations (deterministic or stochastic with the respective initial conditions. Changing the noise processes by taking them to be more realistic wide band noises or delayed white noises creates challenging partial differential equations with initial and boundary conditions. In this paper, we are aimed to give a survey of this connection between Kalman filtering and boundary value problems, bringing them into the attention of mathematicians as well as engineers dealing with Kalman filtering and boundary value problems.

  6. Comparison of New Technology Integrated and Nonintegrated Arterial Filters Used in Cardiopulmonary Bypass Surgery: A Randomized, Prospective, and Single Blind Study

    Directory of Open Access Journals (Sweden)

    Özgür Gürsu

    2013-01-01

    Full Text Available Background. Innovative cardiopulmonary bypass (CPB settings have been developed in order to integrate the concepts of “surface-coating,” “blood-filtration,” and “miniaturization.” Objectives. To compare integrated and nonintegrated arterial line filters in terms of peri- and postoperative clinical variables, inflammatory response, and transfusion needs. Material and Methods. Thirty-six patients who underwent coronary bypass surgery were randomized into integrated (Group In and nonintegrated arterial line filter (Group NIn groups. Arterial blood samples for the assessments of complete hemogram, biochemical screening, interleukin-6, interleukin-2R, and C-reactive protein were analyzed before and after surgery. Need for postoperative dialysis, inotropic therapy and transfusion, in addition to extubation time, total amount of drainage (mL, length of intensive care unit, and hospital stay, and mortality rates was also recorded for each patient. Results. Prime volume was significantly higher and mean intraoperative hematocrit value was lower in Group NIn, but need for erythrocyte transfusion was significantly higher in Group NIn. C-reactive protein values did not differ significantly except for postoperative second day's results, which were found significantly lower in Group In than in Group NIn. Conclusion. Intraoperative hematocrit levels were higher and need for postoperative erythrocyte transfusion was decreased in Group In.

  7. Narrowband (LPC-10) Vocoder Performance under Combined Effects of Random Bit Errors and Jet Aircraft Cabin Noise.

    Science.gov (United States)

    1983-12-01

    Environment 52 34. Comparison of Regression Lines Estimating Scores for the Sustention Intelligibility Feature vs Bit Error Rate for the DOD LPC-10 Vocoder in...both conditions, the feature "sibilation" obtained the highest scores, and the features "graveness" and " sustention " received the poorest scores, but...were under much greater impairment in the noise environment. Details of the variations in scores for sustention are shown in Figure 34, and, for

  8. A randomized controlled trial of the plastic-housing BioSand filter and its impact on diarrheal disease in Copan, Honduras.

    Science.gov (United States)

    Fabiszewski de Aceituno, Anna M; Stauber, Christine E; Walters, Adam R; Meza Sanchez, Rony E; Sobsey, Mark D

    2012-06-01

    Point of use drinking water treatment with the BioSand filter (BSF) allows people to treat their water in the home. The purpose of this research was to document the ability of the Hydraid plastic-housing BSF to reduce diarrheal disease in households who received a BSF in a randomized controlled trial. The trial of the Hydraid plastic-housing BSF was carried out in rural, mountainous communities in Copan, Honduras during April of 2008 to February of 2009. A logistic regression adjusting for clustering showed that the incidence of diarrheal disease in children under 5 years was reduced by approximately 45% (odds ratio = 0.55, 95% confidence interval = 0.28, 1.10) in households that had a BSF compared with those households without a BSF, but this finding fluctuated depending on season and was not statistically significant. Households with a BSF had significantly better drinking water quality regardless of water source or season.

  9. Looking for the Signal: A guide to iterative noise and artefact removal in X-ray tomographic reconstructions of porous geomaterials

    Science.gov (United States)

    Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.

    2017-07-01

    X-ray micro- and nanotomography has evolved into a quantitative analysis tool rather than a mere qualitative visualization technique for the study of porous natural materials. Tomographic reconstructions are subject to noise that has to be handled by image filters prior to quantitative analysis. Typically, denoising filters are designed to handle random noise, such as Gaussian or Poisson noise. In tomographic reconstructions, noise has been projected from Radon space to Euclidean space, i.e. post reconstruction noise cannot be expected to be random but to be correlated. Reconstruction artefacts, such as streak or ring artefacts, aggravate the filtering process so algorithms performing well with random noise are not guaranteed to provide satisfactory results for X-ray tomography reconstructions. With sufficient image resolution, the crystalline origin of most geomaterials results in tomography images of objects that are untextured. We developed a denoising framework for these kinds of samples that combines a noise level estimate with iterative nonlocal means denoising. This allows splitting the denoising task into several weak denoising subtasks where the later filtering steps provide a controlled level of texture removal. We describe a hands-on explanation for the use of this iterative denoising approach and the validity and quality of the image enhancement filter was evaluated in a benchmarking experiment with noise footprints of a varying level of correlation and residual artefacts. They were extracted from real tomography reconstructions. We found that our denoising solutions were superior to other denoising algorithms, over a broad range of contrast-to-noise ratios on artificial piecewise constant signals.

  10. A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

    Science.gov (United States)

    Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

    2017-10-01

    Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary

  11. ANALYSIS OF EFFECT OF APPROXIMATING OUTPUT SAMPLES USING RANDOM SUB-SAMPLING OF INPUT FOR COMPUTATION REDUCTION IN FILTERING OPERATION

    Directory of Open Access Journals (Sweden)

    AMANPREET SINGH

    2006-12-01

    Full Text Available Communication plays a significant role in today’s life. Integration of computing and communicating devices, wide-spread internet access through World Wide Web (WWW, and wireless links are an increasing demand for mobile cellular services at the consumer end, so it has led to new signal processing technologies. Signal processing and communications are tightly inter-woven and immensely influence each other. As the need for sophisticated signal processing algorithms and hardware increase, their potential to make contributions to the communication revolution appears unbounded. Digital signal processing (DSP technology is widely used in numerous familiar products, peripherals of computers and the electronics world. This paper deals with the optimization of DSP environment for communication applications. Emphasis is given to the receiver part of the communication system; more specifically the channel separation aspect is discussed. No such algorithm for the computational saving for receiver part of communication system has been reported earlier. In this paper an attempt has been made to optimize the filtering operation.

  12. Perspectives on Nonlinear Filtering

    KAUST Repository

    Law, Kody

    2015-01-07

    The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

  13. Signal enhancement with variable span linear filters

    CERN Document Server

    Benesty, Jacob; Jensen, Jesper R

    2016-01-01

    This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of ...

  14. Signal Enhancement with Variable Span Linear Filters

    DEFF Research Database (Denmark)

    Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Jesper Rindom

    This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed....... Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal......-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both...

  15. A Novel SFG Structure for C-T Highpass Filters

    DEFF Research Database (Denmark)

    Nielsen, Ivan Riis

    1992-01-01

    MOSFET-C building blocks. The noise performance is considerably enhanced when compared to other highpass filter structures. Well within the stopband the output noise is dominated by amplifier noise, but only one amplifier contributes and its equivalent input noise is simply copied to the output (not...... amplified). Around the passband frequency MOSFET-resistor noise is the dominant noise source, but the number of MOSFET-resistors is kept at a minimum, thus reducing this noise source. The above mentioned noise properties are directly related to the new filter structure, which in addition to this has...

  16. Structured filtering

    Science.gov (United States)

    Granade, Christopher; Wiebe, Nathan

    2017-08-01

    A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.

  17. The guided bilateral filter: when the joint/cross bilateral filter becomes robust.

    Science.gov (United States)

    Caraffa, Laurent; Tarel, Jean-Philippe; Charbonnier, Pierre

    2015-04-01

    The bilateral filter and its variants, such as the joint/cross bilateral filter, are well-known edge-preserving image smoothing tools used in many applications. The reason of this success is its simple definition and the possibility of many adaptations. The bilateral filter is known to be related to robust estimation. This link is lost by the ad hoc introduction of the guide image in the joint/cross bilateral filter. We here propose a new way to derive the joint/cross bilateral filter as a particular case of a more generic filter, which we name the guided bilateral filter. This new filter is iterative, generic, inherits the robustness properties of the robust bilateral filter, and uses a guide image. The link with robust estimation allows us to relate the filter parameters with the statistics of input images. A scheme based on graduated nonconvexity is proposed, which allows converging to an interesting local minimum even when the cost function is nonconvex. With this scheme, the guided bilateral filter can handle non-Gaussian noise on the image to be filtered. A complementary scheme is also proposed to handle non-Gaussian noise on the guide image even if both are strongly correlated. This allows the guided bilateral filter to handle situations with more noise than the joint/cross bilateral filter can work with and leads to high peak signal-to-noise ratio values as shown experimentally.

  18. Evaluating noise reduction techniques while considering anatomical noise in dual-energy contrast-enhanced mammography.

    Science.gov (United States)

    Allec, Nicholas; Abbaszadeh, Shiva; Scott, Chris C; Karim, Karim S; Lewin, John M

    2013-05-01

    The authors describe modifications to previously developed cascaded systems analysis to include the anatomical noise in evaluation of dual-energy noise reduction techniques. Previous models have ignored the anatomical noise in theoretical analysis of noise reduction techniques. The inclusion of anatomical noise leads to more accurate estimation of potential noise reduction improvements and optimization. The model is applied to dual-energy contrast-enhanced mammography. The effect of linear noise reduction filters on the anatomical noise is taken into account using cascaded systems analysis. The noise model is included in the ideal observer detectability for performance evaluation of the noise reduction techniques. Dual-energy image noise with and without including the effect of anatomical noise in noise reduction technique analysis is reported. The theoretical model is compared with clinical images from a previous dual-energy contrast enhanced mammography clinical study and good agreement is observed. The results suggest that the inclusion of anatomical noise in the evaluation and comparison of noise reduction techniques is highly warranted for more accurate analysis. This work establishes a useful extension to dual-energy cascaded systems analysis for maximizing image quality using noise reduction techniques. The extension includes the effect of linear image filtering, such as that used for noise reduction, on anatomical noise. The results suggest that the inclusion of anatomical noise in the evaluation of noise reduction techniques can lead to more accurate optimization, noise, and performance estimations.

  19. A model of the ethylene signaling pathway and its gene response in Arabidopsis thaliana: Pathway cross-talk and noise-filtering properties

    Science.gov (United States)

    Díaz, José; Álvarez-Buylla, Elena R.

    2006-06-01

    Dynamic models of molecular networks and pathways enable in silico evaluations of the consistency of proposed interactions and the outcomes of perturbations as well as of hypotheses on system-level structure and function. We postulate a continuous model of the activation dynamics of the ethylene response factor 1 (ERF1) gene in response to ethylene signaling. This activation elicits the response of the plant defensin 1 (PDF1) gene, which also responds to jasmonic acid, and the inhibition of the putative auxin responsive factor 2 (ARF2) gene, that also responds to auxin. Our model allows the effect of different ethylene concentrations in eliciting contrasting genetic and phenotypic responses to be evaluated allows the effect of different ethylene concentrations in eliciting contrasting genetic and phenotypic responses to be evaluated and seems to consider key components of the ethylene pathway because the ERF1 dose-response curve that we predict has the same qualitative form as the phenotypic dose-response curves obtained experimentally. Therefore, our model suggests that the phenotypic dose-response curves obtained experimentally could be due, at least in part, to ERF1 changes to different ethylene concentrations. Stability analyses show that the model's results are robust to parameter estimates. Of interest is that our model predicts that the ethylene pathway may filter stochastic and rapid chaotic fluctuations in ethylene availability. This novel approach may be applied to any cellular signaling and response pathway in plants and animals.

  20. Microwave Filters

    OpenAIRE

    Zhou, Jiafeng

    2010-01-01

    The general theory of microwave filter design based on lumped-element circuit is described in this chapter. The lowpass prototype filters with Butterworth, Chebyshev and quasielliptic characteristics are synthesized, and the prototype filters are then transformed to bandpass filters by lowpass to bandpass frequency mapping. By using immitance inverters ( J - or K -inverters), the bandpass filters can be realized by the same type of resonators. One design example is given to verify the theory ...

  1. GENERALIZATION OF RAYLEIGH MAXIMUM LIKELIHOOD DESPECKLING FILTER USING QUADRILATERAL KERNELS

    Directory of Open Access Journals (Sweden)

    S. Sridevi

    2013-02-01

    Full Text Available Speckle noise is the most prevalent noise in clinical ultrasound images. It visibly looks like light and dark spots and deduce the pixel intensity as murkiest. Gazing at fetal ultrasound images, the impact of edge and local fine details are more palpable for obstetricians and gynecologists to carry out prenatal diagnosis of congenital heart disease. A robust despeckling filter has to be contrived to proficiently suppress speckle noise and simultaneously preserve the features. The proposed filter is the generalization of Rayleigh maximum likelihood filter by the exploitation of statistical tools as tuning parameters and use different shapes of quadrilateral kernels to estimate the noise free pixel from neighborhood. The performance of various filters namely Median, Kuwahura, Frost, Homogenous mask filter and Rayleigh maximum likelihood filter are compared with the proposed filter in terms PSNR and image profile. Comparatively the proposed filters surpass the conventional filters.

  2. Noise Gating Solar Images

    Science.gov (United States)

    DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

    2017-08-01

    I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

  3. Measurement and analyses of spectral noise power in computed tomography; Medida y analisis del espectro de potencias del ruido en imagenes de tomografia computarizada

    Energy Technology Data Exchange (ETDEWEB)

    Castro Tejero, P.; Garayoa Roca, J.

    2014-07-01

    Noise is an important feature of image quality. The standard deviation of pixel value in a uniform region has been frequently used as a metric to characterize noise. However, this measure does not provide any information about the noise spatial distribution. A more complete description is given by the Noise Power Spectrum (NPS) which provides both the amount and the spatial correlation of noise. The objective of the present work is to present a methodology and a computing tool to obtain the NPS, in order to analyze its components and study their behaviour for computed tomography (TC) images. Our results show that the major contribution to NPS is a random source for all the explored working conditions. The structural component is constrained to the low frequency region, where it can be as important as the random component. Moreover, we observe that the reconstruction filter and the acquisition technique, axial or helical, have a clear impact on the image noise. (Author)

  4. A pseudo-matched filter for chaos.

    Science.gov (United States)

    Cohen, Seth D; Gauthier, Daniel J

    2012-09-01

    A matched filter maximizes the signal-to-noise ratio of a signal. In the recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is derived for the chaotic waveforms produced by a piecewise-linear system. This system produces a readily available binary symbolic dynamics that can be used to perform correlations in the presence of large amounts of noise using the matched filter. Motivated by these results, we describe a pseudo-matched filter, which operates similarly to the original matched filter. It consists of a notch filter followed by a first-order, low-pass filter. We compare quantitatively the matched filter's performance to that of our pseudo-matched filter using correlation functions. On average, the pseudo-matched filter performs with a correlation signal-to-noise ratio that is 2.0 dB below that of the matched filter. Our pseudo-matched filter, though somewhat inferior in comparison to the matched filter, is easily realizable at high speed (>1 GHz) for potential radar applications.

  5. Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA.

    Science.gov (United States)

    Potapov, Pavel; Longo, Paolo; Okunishi, Eiji

    2017-05-01

    STEM spectrum-imaging with collecting EDX signal is considered in view of the extraction of maximum information from very noisy data. It is emphasized that spectrum-images with weak EDX signal often suffer from information loss in the course of PCA treatment. The loss occurs when the level of random noise exceeds a certain threshold. Weighted PCA, though potentially helpful in isolation of meaningful variations from noise, might provoke the complete loss of information in the situation of weak EDX signal. Filtering datasets prior PCA can improve the situation and recover the lost information. In particular, Gaussian kernel filters are found to be efficient. A new filter useful in the case of sparse atomic-resolution EDX spectrum-images is suggested. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Water Filters

    Science.gov (United States)

    1993-01-01

    The Aquaspace H2OME Guardian Water Filter, available through Western Water International, Inc., reduces lead in water supplies. The filter is mounted on the faucet and the filter cartridge is placed in the "dead space" between sink and wall. This filter is one of several new filtration devices using the Aquaspace compound filter media, which combines company developed and NASA technology. Aquaspace filters are used in industrial, commercial, residential, and recreational environments as well as by developing nations where water is highly contaminated.

  7. Mathematical models and simulations of phase noise in phase-locked loops

    Directory of Open Access Journals (Sweden)

    Sethapong Limkumnerd

    2007-07-01

    Full Text Available Phase noises in Phase-Locked Loops (PLLs are a key parameter for communication systems that contribute the bit-rate-error of communication systems and cause synchronization problems. Accurate predictions of phase noises through mathematical models are consequently desirable for practical designs of PLLs. Despite many phase noise models derived from noise sources from electronic devices such as an oscillator and a multiplier have been proposed, no phase noise models that include noises from loop filters have specifically been investigated. This paper therefore investigates the roles of loop filters in phase noise contribution. The major scopes of this paper is a detailed analysis and simulations of phase noise models resulting from all components. i.e. a voltage-controlled oscillator, a multiplier and a filter. Two particular second-order passive and active low-pass filters are compared. The results show that simulations of phase noises without an inclusion of filter noises may not be accurate because the filter noises, particularly the active filter, significantly contribute the total phase noise. Moreover, the passive filter does not significantly dominate the phase noise at low offset frequency while the active filters entirely dominate. Therefore, the passive filter is a more efficient filter for PLL circuit at low offset frequency. The phase noise models presented in this paper are relatively simple and can be used for accurate phase noise prediction for PLL designs.

  8. Signal Enhancement with Variable Span Linear Filters

    DEFF Research Database (Denmark)

    Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Jesper Rindom

    . Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise...... the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.......This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed...

  9. Luminance noise as a novel approach for measuring contrast sensitivity within the magnocellular and parvocellular pathways.

    Science.gov (United States)

    Hall, Cierra M; McAnany, J Jason

    2017-07-01

    This study evaluated the extent to which different types of luminance noise can be used to target selectively the inferred magnocellular (MC) and parvocellular (PC) visual pathways. Letter contrast sensitivity (CS) was measured for three visually normal subjects for letters of different size (0.8°-5.3°) under established paradigms intended to target the MC pathway (steady-pedestal paradigm) and PC pathway (pulsed-pedestal paradigm). Results obtained under these paradigms were compared to those obtained in asynchronous static noise (a field of unchanging luminance noise) and asynchronous dynamic noise (a field of randomly changing luminance noise). CS was measured for letters that were high- and low-pass filtered using a range of filter cutoffs to quantify the object frequency information (cycles per letter) mediating letter identification, which was used as an index of the pathway mediating CS. A follow-up experiment was performed to determine the range of letter duration over which MC and PC pathway CS can be targeted. Analysis of variance indicated that the object frequencies measured under the static noise and steady-pedestal paradigms did not differ significantly (p ≥ 0.065), but differed considerably from those measured under the dynamic noise (both p noise, and in dynamic noise. These data suggest that the spatiotemporal characteristics of noise can be manipulated to target the inferred MC (static noise) and PC (dynamic noise) pathways. The results also suggest that CS within these pathways can be measured at long stimulus durations, which has potential importance in the design of future clinical CS tests.

  10. The subjective importance of noise spectral content

    Science.gov (United States)

    Baxter, Donald; Phillips, Jonathan; Denman, Hugh

    2014-01-01

    This paper presents secondary Standard Quality Scale (SQS2) rankings in overall quality JNDs for a subjective analysis of the 3 axes of noise, amplitude, spectral content, and noise type, based on the ISO 20462 softcopy ruler protocol. For the initial pilot study, a Python noise simulation model was created to generate the matrix of noise masks for the softcopy ruler base images with different levels of noise, different low pass filter noise bandwidths and different band pass filter center frequencies, and 3 different types of noise: luma only, chroma only, and luma and chroma combined. Based on the lessons learned, the full subjective experiment, involving 27 observers from Google, NVIDIA and STMicroelectronics was modified to incorporate a wider set of base image scenes, and the removal of band pass filtered noise masks to ease observer fatigue. Good correlation was observed with the Aptina subjective noise study. The absence of tone mapping in the noise simulation model visibly reduced the contrast at high levels of noise, due to the clipping of the high levels of noise near black and white. Under the 34-inch viewing distance, no significant difference was found between the luma only noise masks and the combined luma and chroma noise masks. This was not the intuitive expectation. Two of the base images with large uniform areas, `restaurant' and `no parking', were found to be consistently more sensitive to noise than the texture rich scenes. Two key conclusions are (1) there are fundamentally different sensitivities to noise on a flat patch versus noise in real images and (2) magnification of an image accentuates visual noise in a way that is non-representative of typical noise reduction algorithms generating the same output frequency. Analysis of our experimental noise masks applied to a synthetic Macbeth ColorChecker Chart confirmed the color-dependent nature of the visibility of luma and chroma noise.

  11. The Signal Importance of Noise

    Science.gov (United States)

    Macy, Michael; Tsvetkova, Milena

    2015-01-01

    Noise is widely regarded as a residual category--the unexplained variance in a linear model or the random disturbance of a predictable pattern. Accordingly, formal models often impose the simplifying assumption that the world is noise-free and social dynamics are deterministic. Where noise is assigned causal importance, it is often assumed to be a…

  12. Filter Bank Fusion Frames

    OpenAIRE

    Chebira, Amina; Fickus, Matthew; Mixon, Dustin G.

    2010-01-01

    In this paper we characterize and construct novel oversampled filter banks implementing fusion frames. A fusion frame is a sequence of orthogonal projection operators whose sum can be inverted in a numerically stable way. When properly designed, fusion frames can provide redundant encodings of signals which are optimally robust against certain types of noise and erasures. However, up to this point, few implementable constructions of such frames were known; we show how to construct them using ...

  13. Water Filters

    Science.gov (United States)

    1987-01-01

    A compact, lightweight electrolytic water filter generates silver ions in concentrations of 50 to 100 parts per billion in the water flow system. Silver ions serve as effective bactericide/deodorizers. Ray Ward requested and received from NASA a technical information package on the Shuttle filter, and used it as basis for his own initial development, a home use filter.

  14. Restoration of Medical Images with Different Types of Noise; Restauracion de Imagenes Medicas con Diferentes Tipos de Ruido

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, M. G.; Vidal, V.; Verdu, G.; Mayo, P.; Rodenas, F.

    2013-07-01

    In this paper, a method is proposed to reduce the Gaussian, speckle and impulsive noise. This filter, named PGMFDNL filter combines a nonlinear diffusion and fuzzy peer group. The proposed filter can effectively reduce image noise without any information about the noise present in the image. As a result, the proposed method obtains good performance in different types of noise.

  15. Noise estimation for remote sensing image data analysis

    Science.gov (United States)

    Du, Qian

    2004-01-01

    Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.

  16. Does the central limit theorem always apply to phase noise? Some implications for radar problems

    Science.gov (United States)

    Gray, John E.; Addison, Stephen R.

    2017-05-01

    The phase noise problem or Rayleigh problem occurs in all aspects of radar. It is an effect that a radar engineer or physicist always has to take into account as part of a design or in attempt to characterize the physics of a problem such as reverberation. Normally, the mathematical difficulties of phase noise characterization are avoided by assuming the phase noise probability distribution function (PDF) is uniformly distributed, and the Central Limit Theorem (CLT) is invoked to argue that the superposition of relatively few random components obey the CLT and hence the superposition can be treated as a normal distribution. By formalizing the characterization of phase noise (see Gray and Alouani) for an individual random variable, the summation of identically distributed random variables is the product of multiple characteristic functions (CF). The product of the CFs for phase noise has a CF that can be analyzed to understand the limitations CLT when applied to phase noise. We mirror Kolmogorov's original proof as discussed in Papoulis to show the CLT can break down for receivers that gather limited amounts of data as well as the circumstances under which it can fail for certain phase noise distributions. We then discuss the consequences of this for matched filter design as well the implications for some physics problems.

  17. Optimal filtering

    CERN Document Server

    Anderson, Brian D O

    1979-01-01

    This graduate-level text augments and extends beyond undergraduate studies of signal processing, particularly in regard to communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to students in such diverse areas as statistics, economics, bioengineering, and operations research.Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing of discrete-time signals. Additional subjects e

  18. Calibration of an audio frequency noise generator

    DEFF Research Database (Denmark)

    Diamond, Joseph M.

    1966-01-01

    it is used for measurement purposes. The spectral density of a noise source may be found by measuring its rms output over a known noise bandwidth. Such a bandwidth may be provided by a passive filter using accurately known elements. For example, the parallel resonant circuit with purely parallel damping has...... a noise bandwidth Bn = π/2 × (3dB bandwidth). To apply this method to low audio frequencies, the noise bandwidth of the low Q parallel resonant circuit has been found, including the effects of both series and parallel damping. The method has been used to calibrate a General Radio 1390-B noise generator......A noise generator of known output is very convenient in noise measurement. At low audio frequencies, however, all devices, including noise sources, may be affected by excess noise (1/f noise). It is therefore very desirable to be able to check the spectral density of a noise source before...

  19. Decision-Based Marginal Total Variation Diffusion for Impulsive Noise Removal in Color Images

    Directory of Open Access Journals (Sweden)

    Hongyao Deng

    2017-01-01

    Full Text Available Impulsive noise removal for color images usually employs vector median filter, switching median filter, the total variation L1 method, and variants. These approaches, however, often introduce excessive smoothing and can result in extensive visual feature blurring and thus are suitable only for images with low density noise. A marginal method to reduce impulsive noise is proposed in this paper that overcomes this limitation that is based on the following facts: (i each channel in a color image is contaminated independently, and contaminative components are independent and identically distributed; (ii in a natural image the gradients of different components of a pixel are similar to one another. This method divides components into different categories based on different noise characteristics. If an image is corrupted by salt-and-pepper noise, the components are divided into the corrupted and the noise-free components; if the image is corrupted by random-valued impulses, the components are divided into the corrupted, noise-free, and the possibly corrupted components. Components falling into different categories are processed differently. If a component is corrupted, modified total variation diffusion is applied; if it is possibly corrupted, scaled total variation diffusion is applied; otherwise, the component is left unchanged. Simulation results demonstrate its effectiveness.

  20. On optimal infinite impulse response edge detection filters

    Science.gov (United States)

    Sarkar, Sudeep; Boyer, Kim L.

    1991-01-01

    The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

  1. Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise

    Directory of Open Access Journals (Sweden)

    Lukas Ebner

    2014-01-01

    Full Text Available Objective:The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP and an iterative reconstruction (IR algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany was investigated. Materials and Methods: 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP, SOMATOM Definition Flash (IR, and SOMATOM Definition Edge (ICD and IR. Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. Results: Dose-length product (DLP with FBP for the average chest CT was 308 mGycm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGycm ± 68.8 (P = 0.0001. Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGycm ± 54.5 (P = 0.033. The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048. Overall contrast-to-noise ratio (CNR improved with declining DLP. Conclusion: The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

  2. Noise prevention

    Science.gov (United States)

    Methods for noise abatement are discussed. Noise nuisance, types of noise (continuous, fluctuating, intermittent, pulsed), and types of noise abatement (absorption, vibration damping, isolation) are defined. Rockwool panels, industrial ceiling panels, baffles, acoustic foam panels, vibration dampers, acoustic mats, sandwich panels, isolating cabins and walls, ear protectors, and curtains are presented.

  3. CUDA-based acceleration of collateral filtering in brain MR images

    Science.gov (United States)

    Li, Cheng-Yuan; Chang, Herng-Hua

    2017-02-01

    Image denoising is one of the fundamental and essential tasks within image processing. In medical imaging, finding an effective algorithm that can remove random noise in MR images is important. This paper proposes an effective noise reduction method for brain magnetic resonance (MR) images. Our approach is based on the collateral filter which is a more powerful method than the bilateral filter in many cases. However, the computation of the collateral filter algorithm is quite time-consuming. To solve this problem, we improved the collateral filter algorithm with parallel computing using GPU. We adopted CUDA, an application programming interface for GPU by NVIDIA, to accelerate the computation. Our experimental evaluation on an Intel Xeon CPU E5-2620 v3 2.40GHz with a NVIDIA Tesla K40c GPU indicated that the proposed implementation runs dramatically faster than the traditional collateral filter. We believe that the proposed framework has established a general blueprint for achieving fast and robust filtering in a wide variety of medical image denoising applications.

  4. Signal-to-Noise Ratio Analysis of a Phase-Sensitive Voltmeter for Electrical Impedance Tomography.

    Science.gov (United States)

    Murphy, Ethan K; Takhti, Mohammad; Skinner, Joseph; Halter, Ryan J; Odame, Kofi

    2017-04-01

    In this paper, thorough analysis along with mathematical derivations of the matched filter for a voltmeter used in electrical impedance tomography systems are presented. The effect of the random noise in the system prior to the matched filter, generated by other components, are considered. Employing the presented equations allow system/circuit designers to find the maximum tolerable noise prior to the matched filter that leads to the target signal-to-noise ratio (SNR) of the voltmeter, without having to over-design internal components. A practical model was developed that should fall within 2 dB and 5 dB of the median SNR measurements of signal amplitude and phase, respectively. In order to validate our claims, simulation and experimental measurements have been performed with an analog-to-digital converter (ADC) followed by a digital matched filter, while the noise of the whole system was modeled as the input referred at the ADC input. The input signal was contaminated by a known value of additive white Gaussian noise (AWGN) noise, and the noise level was swept from 3% to 75% of the least significant bit (LSB) of the ADC. Differences between experimental and both simulated and analytical SNR values were less than 0.59 and 0.35 dB for RMS values ≥ 20% of an LSB and less than 1.45 and 2.58 dB for RMS values circuit designers in EIT, and a more accurate error analysis that was previously missing in EIT literature.

  5. Metal Mesh Filters for Terahertz Receivers Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The technical objective of this SBIR program is to develop and demonstrate metal mesh filters for use in NASA's low noise receivers for terahertz astronomy and...

  6. SAR Image Enhancement using Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a...

  7. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

    Science.gov (United States)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

    2011-12-01

    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  8. Gaussian filters and filter synthesis using a Hermite/Laguerre neural network.

    Science.gov (United States)

    Mackenzie, Mark; Tieu, Kiet

    2004-01-01

    A neural network for calculating the correlation of a signal with a Gaussian function is described. The network behaves as a Gaussian filter and has two outputs: the first approximates the noisy signal and the second represents the filtered signal. The filtered output provides improvement by a factor of ten in the signal-to-noise ratio. A higher order Gaussian filter was synthesized by combining several Hermite functions together.

  9. Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

    Science.gov (United States)

    Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

    2017-01-01

    A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

  10. CUDA-based acceleration and BPN-assisted automation of bilateral filtering for brain MR image restoration.

    Science.gov (United States)

    Chang, Herng-Hua; Chang, Yu-Ning

    2017-04-01

    relative error in terms of peak signal-to-noise ratio (PSNR) less than 0.1%. In comparison with many state-of-the-art filters, the proposed automation framework with CUDA-based bilateral filtering provided more favorable results both quantitatively and qualitatively. Possessing unique characteristics and demonstrating exceptional performances, the proposed CUDA-based bilateral filter adequately removed random noise in multifarious brain MR images for further study in neurosciences and radiological sciences. It requires no prior knowledge of the noise variance and automatically restores MR images while preserving fine details. The strategy of exploiting the CUDA to accelerate the computation and incorporating texture features into the BPN to completely automate the bilateral filtering process is achievable and validated, from which the best performance is reached. © 2017 American Association of Physicists in Medicine.

  11. Track inspection data filtering based on EMD

    Science.gov (United States)

    Wang, YiJun; Liang, Guangzhu

    2017-04-01

    In order to reduce the influence of the coarse error noise in the original data acquired by railway inspection instrument, we propose that filtering the original data by Empirical Mode Decomposition combine with ROR criterion. The ROR criterion is used to identify and eliminate the coarse error in the first layer of original data which is IMF1 obtained by empirical mode decomposition, and then we can get the signal after removal of noise by inverse operation of empirical mode decomposition. The mean square error and the signal-to-noise ratio are used to analyze and evaluate the effect of recursive median method and proposed method on filtering noise, the advantage of proposed method in dealing with nonlinear nonstationary signals is verified. The example shows that the method proposed in this paper can effectively identify the coarse error in the signal and eliminate the noise, and get the ideal filtering result.

  12. Nonlinear Adaptive Filters based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Faten BEN ARFIA

    2009-07-01

    Full Text Available This paper presents a particle swarm optimization (PSO algorithm to adjust the parameters of the nonlinear filter and to make this type of the filters more powerful for the elimination of the Gaussian noise and also the impulse noise. In this paper we apply the particle swarm optimization to the rational filters and we completed this work with the comparison between our results and other adaptive nonlinear filters like the LMS adaptive median filters and the no-adaptive rational filter.

  13. RSSI based indoor tracking in sensor networks using Kalman filters

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Skjøth, Flemming; Munksgaard, Lene

    2010-01-01

    We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio of the obse......We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio...

  14. A Digital Image Denoising Algorithm Based on Gaussian Filtering and Bilateral Filtering

    Directory of Open Access Journals (Sweden)

    Piao Weiying

    2018-01-01

    Full Text Available Bilateral filtering has been applied in the area of digital image processing widely, but in the high gradient region of the image, bilateral filtering may generate staircase effect. Bilateral filtering can be regarded as one particular form of local mode filtering, according to above analysis, an mixed image de-noising algorithm is proposed based on Gaussian filter and bilateral filtering. First of all, it uses Gaussian filter to filtrate the noise image and get the reference image, then to take both the reference image and noise image as the input for range kernel function of bilateral filter. The reference image can provide the image’s low frequency information, and noise image can provide image’s high frequency information. Through the competitive experiment on both the method in this paper and traditional bilateral filtering, the experimental result showed that the mixed de-noising algorithm can effectively overcome staircase effect, and the filtrated image was more smooth, its textural features was also more close to the original image, and it can achieve higher PSNR value, but the amount of calculation of above two algorithms are basically the same.

  15. Recursive framework for joint inpainting and de-noising of photographic films.

    Science.gov (United States)

    Subrahmanyam, G R K S; Rajagopalan, A N; Aravind, R

    2010-05-01

    We address the problem of inpainting noisy photographs. We present a recursive image recovery scheme based on the unscented Kalman filter (UKF) to simultaneously inpaint identified damaged portions in an image and suppress film-grain noise. Inpainting of the missing observations is guided by a mask-dependent reconstruction of the image edges. Prediction within the UKF is based on a discontinuity-adaptive Markov random field prior that attempts to preserve edges while achieving noise reduction in uniform regions. We demonstrate the capability of the proposed method with many examples.

  16. Improving working memory: exploring the effect of transcranial random noise stimulation and transcranial direct current stimulation on the dorsolateral prefrontal cortex.

    Science.gov (United States)

    Mulquiney, Paul G; Hoy, Kate E; Daskalakis, Zafiris J; Fitzgerald, Paul B

    2011-12-01

    The aim of this study was to determine if working memory (WM) performance is significantly improved after the delivery of transcranial random noise stimulation (tRNS) to the left dorsolateral prefrontal cortex (DLPFC), compared to an active comparator or sham. Ten participants undertook three experimental sessions in which they received 10 min of anodal tDCS (active comparator), tRNS or sham tDCS whilst performing the Sternberg WM task. Intra-stimulation engagement in a WM task was undertaken as this has been previously shown to enhance the effects of tDCS. Experimental sessions were separated by a minimum of 1 week. Immediately prior to and after each stimulation session the participants were measured on speed and accuracy of performance on an n-back task. There was significant improvement in speed of performance following anodal tDCS on the 2-back WM task; this was the only significant finding. The results do not provide support for the hypothesis that tRNS improves WM. However, the study does provide confirmation of previous findings that anodal tDCS enhances some aspects of DLPFC functioning. Methodological limitations that may have contributed to the lack of significant findings following tRNS are discussed. Anodal tDCS may have significant implications for WM remediation in psychiatric conditions, particularly schizophrenia. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  17. Improvement of uncorrected visual acuity (UCVA and contrast sensitivity (UCCS with perceptual learning and transcranial random noise stimulation (tRNS in individuals with mild myopia

    Directory of Open Access Journals (Sweden)

    Rebecca eCamilleri

    2014-10-01

    Full Text Available Perceptual learning has been shown to produce an improvement of visual acuity (VA and contrast sensitivity (CS both in subjects with amblyopia and refractive defects such as myopia or presbyopia. Transcranial random noise stimulation (tRNS has proven to be efficacious in accelerating neural plasticity and boosting perceptual learning in healthy participants. In this study we investigated whether a short behavioural training regime using a contrast detection task combined with online tRNS was as effective in improving visual functions in participants with mild myopia compared to a two-month behavioural training regime without tRNS (Camilleri et al., 2014. After two weeks of perceptual training in combination with tRNS, participants showed an improvement of 0.15 LogMAR in uncorrected VA (UCVA that was comparable with that obtained after eight weeks of training with no tRNS, and an improvement in uncorrected CS (UCCS at various spatial frequencies (whereas no UCCS improvement was seen after eight weeks of training with no tRNS. On the other hand, a control group that trained for two weeks without stimulation did not show any significant UCVA or UCCS improvement. These results suggest that the combination of behavioural and neuromodulatory techniques can be fast and efficacious in improving sight in individuals with mild myopia.

  18. True randomness from an incoherent source

    Science.gov (United States)

    Qi, Bing

    2017-11-01

    Quantum random number generators (QRNGs) harness the intrinsic randomness in measurement processes: the measurement outputs are truly random, given the input state is a superposition of the eigenstates of the measurement operators. In the case of trusted devices, true randomness could be generated from a mixed state ρ so long as the system entangled with ρ is well protected. We propose a random number generation scheme based on measuring the quadrature fluctuations of a single mode thermal state using an optical homodyne detector. By mixing the output of a broadband amplified spontaneous emission (ASE) source with a single mode local oscillator (LO) at a beam splitter and performing differential photo-detection, we can selectively detect the quadrature fluctuation of a single mode output of the ASE source, thanks to the filtering function of the LO. Experimentally, a quadrature variance about three orders of magnitude larger than the vacuum noise has been observed, suggesting this scheme can tolerate much higher detector noise in comparison with QRNGs based on measuring the vacuum noise. The high quality of this entropy source is evidenced by the small correlation coefficients of the acquired data. A Toeplitz-hashing extractor is applied to generate unbiased random bits from the Gaussian distributed raw data, achieving an efficiency of 5.12 bits per sample. The output of the Toeplitz extractor successfully passes all the NIST statistical tests for random numbers.

  19. Random field estimation approach to robot dynamics

    Science.gov (United States)

    Rodriguez, Guillermo

    1990-01-01

    The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.

  20. Speech production in amplitude-modulated noise

    DEFF Research Database (Denmark)

    Macdonald, Ewen N; Raufer, Stefan

    2013-01-01

    the consequences of temporally fluctuating noise. In the present study, 20 talkers produced speech in a variety of noise conditions, including both steady-state and amplitude-modulated white noise. While listening to noise over headphones, talkers produced randomly generated five word sentences. Similar...... to previous studies, talkers raised the level of their voice in steady-state noise. While talkers also increased the level of their voice in amplitude-modulated noise, the increase was not as large as that observed in steady-state noise. Importantly, for the 2 and 4 Hz amplitude-modulated noise conditions...

  1. Programmable Baseband Filter for Multistandard Mobile Phones

    DEFF Research Database (Denmark)

    Jensen, Rasmus Glarborg; Christensen, Kåre Tais; Bruun, Erik

    2003-01-01

    of the input transconductor. The entire filter consumes between 2.5 mW and 7.5 mW, depending on the desired noise performance. It is implemented in a standard 0.25 mum CMOS process. A test circuit has been developed and fabricated and measurements show that both the required programmability and the required......This paper describes a channel selection filter for mobile communication systems using a direct down conversion architecture. The filter can be programmed to meet the requirements of different communication standards, including GSM (Global System for Mobile communication), WCDMA (Wideband Code...... Division Multiple Access), and Bluetooth. The filter includes a novel DC offset compensation circuit that combines offset sampling in GSM mode with high pass filtering in WCDMA mode. The filter can be programmed to different noise performance levels by programming the impedance level and power consumption...

  2. Oracle Wiener filtering of a Gaussian signal

    NARCIS (Netherlands)

    Babenko, A.|info:eu-repo/dai/nl/304824518; Belitser, E.N.|info:eu-repo/dai/nl/159499585

    2011-01-01

    We study the problem of filtering a Gaussian process whose trajectories, in some sense, have an unknown smoothness β0 from the white noise of small intensity . If we knew the parameter β0, we would use the Wiener filter which has the meaning of oracle. Our goal is now to mimic the oracle, i.e.,

  3. Variable Span Filters for Speech Enhancement

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

    2016-01-01

    optimal filters using a joint diagonalization as a basis. This gives excellent control over the performance, as we can optimize for noise reduction or signal distortion performance. Results from real data experiments show that the proposed variable span filters can achieve better performance than existing...

  4. Real-valued composite filters for optical pattern recognition

    Science.gov (United States)

    Balendra, A.; Rajan, P. K.

    1993-01-01

    The design of real-valued composite filters for optical pattern recognition and classification is considered. A procedure to design a real-valued minimum average correlation energy (MACE) filter is developed. Also, the design of a real MVSDF-MACE filter that minimizes the output variance due to input noise while maintaining a sharp correlation peak is developed. Computer simulation indicates that the performance of these real filters is almost as good as that of the complex filters.

  5. Application of Machine Learning Techniques for Amplitude and Phase Noise Characterization

    DEFF Research Database (Denmark)

    Zibar, Darko; de Carvalho, Luis Henrique Hecker; Piels, Molly

    2015-01-01

    In this paper, tools from machine learning community, such as Bayesian filtering and expectation maximization parameter estimation, are presented and employed for laser amplitude and phase noise characterization. We show that phase noise estimation based on Bayesian filtering outperforms conventi......In this paper, tools from machine learning community, such as Bayesian filtering and expectation maximization parameter estimation, are presented and employed for laser amplitude and phase noise characterization. We show that phase noise estimation based on Bayesian filtering outperforms...... conventional time-domain approach in the presence of moderate measurement noise. Additionally, carrier synchronization based on Bayesian filtering, in combination with expectation maximization, is demonstrated for the first time experimentally....

  6. Speckle filtering in satellite SAR change detection imagery

    NARCIS (Netherlands)

    Dekker, R.J.

    1998-01-01

    Repeat-pass Synthetic Aperture Radar (SAR) imagery is useful for change detection. A disadvantage of SAR is the system-inherent speckle noise. This can be reduced by filtering. Various filter types and methods are described in the literature, but not one fits the speckle noise in change detection

  7. Optical iconic filters for large class recognition.

    Science.gov (United States)

    Casasent, D; Mahalamobis, A

    1987-06-01

    Approaches are advanced for pattern recognition when a large number of classes must be identified. Multilevel encoded multiple-iconic filters are considered for this problem. Hierarchical arrangements of iconic filters and/or preprocessing stages are described. A theoretical basis for the sidelobe level and noise effects of filters designed for large class problems is advanced. Experimental data are provided for an optical character recognition case study.

  8. Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions

    Science.gov (United States)

    Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej

    2014-05-01

    The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a

  9. Photographic filters

    Science.gov (United States)

    Rodigues, Jose Eduardo; Santosdealmeida, Wagner

    1987-12-01

    Some of the main aspects related to photographic filters are examined and prepared as a reference for researchers and students of remote sensing. A large range of information about the filters including their basic fundamentals, classification, and main types is presented. The theme cannot be exhausted in this or any other individual publication because of its great complexity, profound theoretical publication, and dynmaic technological development. The subject does not deal only with filter applications in remote sensing. As much as possible, additional information about the utilization of these products in other professional areas, as pictorial photography, photographic processing, and optical engineering, were included.

  10. Noise Pollution

    Science.gov (United States)

    ... primarily to one’s overall health. Top of Page Health Effects Noise pollution adversely affects the lives of millions of people. ... its effect, disseminate information to the public regarding noise pollution and its adverse health effects, respond to inquiries on matters related to noise, ...

  11. STATISTICAL CHARACTERISTICS INVESTIGATION OF PREDICTION ERRORS FOR INTERFEROMETRIC SIGNAL IN THE ALGORITHM OF NONLINEAR KALMAN FILTERING

    Directory of Open Access Journals (Sweden)

    E. L. Dmitrieva

    2016-05-01

    Full Text Available Basic peculiarities of nonlinear Kalman filtering algorithm applied to processing of interferometric signals are considered. Analytical estimates determining statistical characteristics of signal values prediction errors were obtained and analysis of errors histograms taking into account variations of different parameters of interferometric signal was carried out. Modeling of the signal prediction procedure with known fixed parameters and variable parameters of signal in the algorithm of nonlinear Kalman filtering was performed. Numerical estimates of prediction errors for interferometric signal values were obtained by formation and analysis of the errors histograms under the influence of additive noise and random variations of amplitude and frequency of interferometric signal. Nonlinear Kalman filter is shown to provide processing of signals with randomly variable parameters, however, it does not take into account directly the linearization error of harmonic function representing interferometric signal that is a filtering error source. The main drawback of the linear prediction consists in non-Gaussian statistics of prediction errors including cases of random deviations of signal amplitude and/or frequency. When implementing stochastic filtering of interferometric signals, it is reasonable to use prediction procedures based on local statistics of a signal and its parameters taken into account.

  12. IMAGE RESTORATION: DESIGN OF NON-LINEAR FILTER (LR

    Directory of Open Access Journals (Sweden)

    Shenbagarajan Anantharajan

    2012-11-01

    Full Text Available In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.

  13. Performance comparison of denoising filters for source camera identification

    Science.gov (United States)

    Cortiana, A.; Conotter, V.; Boato, G.; De Natale, F. G. B.

    2011-02-01

    Source identification for digital content is one of the main branches of digital image forensics. It relies on the extraction of the photo-response non-uniformity (PRNU) noise as a unique intrinsic fingerprint that efficiently characterizes the digital device which generated the content. Such noise is estimated as the difference between the content and its de-noised version obtained via denoising filter processing. This paper proposes a performance comparison of different denoising filters for source identification purposes. In particular, results achieved with a sophisticated 3D filter are presented and discussed with respect to state-of-the-art denoising filters previously employed in such a context.

  14. Statistical Analysis of the Random Telegraph Noise in a 1.1 μm Pixel, 8.3 MP CMOS Image Sensor Using On-Chip Time Constant Extraction Method.

    Science.gov (United States)

    Chao, Calvin Yi-Ping; Tu, Honyih; Wu, Thomas Meng-Hsiu; Chou, Kuo-Yu; Yeh, Shang-Fu; Yin, Chin; Lee, Chih-Lin

    2017-11-23

    A study of the random telegraph noise (RTN) of a 1.1 μm pitch, 8.3 Mpixel CMOS image sensor (CIS) fabricated in a 45 nm backside-illumination (BSI) technology is presented in this paper. A noise decomposition scheme is used to pinpoint the noise source. The long tail of the random noise (RN) distribution is directly linked to the RTN from the pixel source follower (SF). The full 8.3 Mpixels are classified into four categories according to the observed RTN histogram peaks. A theoretical formula describing the RTN as a function of the time difference between the two phases of the correlated double sampling (CDS) is derived and validated by measured data. An on-chip time constant extraction method is developed and applied to the RTN analysis. The effects of readout circuit bandwidth on the settling ratios of the RTN histograms are investigated and successfully accounted for in a simulation using a RTN behavior model.

  15. A quantum extended Kalman filter

    Science.gov (United States)

    Emzir, Muhammad F.; Woolley, Matthew J.; Petersen, Ian R.

    2017-06-01

    In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements.

  16. Effects of reducing exposure to air pollution on submaximal cardiopulmonary test in patients with heart failure: Analysis of the randomized, double-blind and controlled FILTER-HF trial.

    Science.gov (United States)

    Vieira, Jefferson L; Guimaraes, Guilherme V; de Andre, Paulo A; Saldiva, Paulo H Nascimento; Bocchi, Edimar A

    2016-07-15

    Air pollution exposure could mitigate the health benefits of exercise in patients with heart failure (HF). We tested the effects of a respiratory filter on HF patients exposed to air pollution during exercise. Ancillary analysis of the FILTER-HF trial, focused on the exercise outcomes. In a randomized, double-blind, 3-way crossover design, 26 HF patients and 15 control volunteers were exposed to clean air, unfiltered dilute diesel engine exhaust (DE), or filtered DE for 6min during a submaximal cardiopulmonary testing in a controlled-exposure facility. Prospectively collected data included six-minute walking test [6mwt], VO2, VE/VCO2 Slope, O2Pulse, pulmonary ventilation [VE], tidal volume, VD/Vt, oxyhemoglobin saturation and CO2-rebreathing. Compared to clean air, DE adversely affected VO2 (11.0±3.9 vs. 8.4±2.8ml/kg/min; peffects of pollution on VO2 and O2Pulse. Given the worldwide prevalence of exposure to traffic-related air pollution, these findings are relevant for public health especially in this highly susceptible population. The filter intervention holds great promise that needs to be tested in future studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. Tunable Multiband Microwave Photonic Filters

    Directory of Open Access Journals (Sweden)

    Mable P. Fok

    2017-11-01

    Full Text Available The increasing demand for multifunctional devices, the use of cognitive wireless technology to solve the frequency resource shortage problem, as well as the capabilities and operational flexibility necessary to meet ever-changing environment result in an urgent need of multiband wireless communications. Spectral filter is an essential part of any communication systems, and in the case of multiband wireless communications, tunable multiband RF filters are required for channel selection, noise/interference removal, and RF signal processing. Unfortunately, it is difficult for RF electronics to achieve both tunable and multiband spectral filtering. Recent advancements of microwave photonics have proven itself to be a promising candidate to solve various challenges in RF electronics including spectral filtering, however, the development of multiband microwave photonic filtering still faces lots of difficulties, due to the limited scalability and tunability of existing microwave photonic schemes. In this review paper, we first discuss the challenges that were facing by multiband microwave photonic filter, then we review recent techniques that have been developed to tackle the challenge and lead to promising developments of tunable microwave photonic multiband filters. The successful design and implementation of tunable microwave photonic multiband filter facilitate the vision of dynamic multiband wireless communications and radio frequency signal processing for commercial, defense, and civilian applications.

  18. Self-generation and positivity effects following transcranial random noise stimulation in medial prefrontal cortex: A reality monitoring task in older adults.

    Science.gov (United States)

    Mammarella, Nicola; Di Domenico, Alberto; Palumbo, Rocco; Fairfield, Beth

    2017-06-01

    Activation of medial Prefrontal Cortex (mPFC) has been typically found during reality monitoring tasks (i.e., distinguishing between internal self-generated vs external information). No study, however, has yet investigated whether transcranial Random Noise Stimulation (tRNS) over the mPFC leads to a reduction in reality-monitoring misattributions in aging. In particular, stimulating mPFC should increase the number of cognitive operations engaged while encoding and this distinctive information may help older adults to discriminate between internal and external sources better. In addition, given that older adults are more sensitive to positively-charged information compared to younger adults and that mPFC is typically recruited during encoding of positive stimuli with reference to themselves, activation of mPFC should further sustain source retrieval in older adults. In this double-blind, sham-controlled study, we examined whether tRNS over the mPFC of healthy younger and older adults during encoding enhances subsequent reality monitoring for seen versus imagined emotionally-charged words. Our findings show that tRNS enhances reality monitoring for positively-charged imagined words in the older adult group alone, highlighting the role that mPFC plays in their memory for positive information. In line with the control-based account of positivity effects, our results add evidence about the neurocognitive processes involved in reality monitoring when older adults face emotionally-charged events. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Random Number Generators in Secure Disk Drives

    Directory of Open Access Journals (Sweden)

    Hars Laszlo

    2009-01-01

    Full Text Available Abstract Cryptographic random number generators seeded by physical entropy sources are employed in many embedded security systems, including self-encrypting disk drives, being manufactured by the millions every year. Random numbers are used for generating encryption keys and for facilitating secure communication, and they are also provided to users for their applications. We discuss common randomness requirements, techniques for estimating the entropy of physical sources, investigate specific nonrandom physical properties, estimate the autocorrelation, then mix reduce the data until all common randomness tests pass. This method is applied to a randomness source in disk drives: the always changing coefficients of an adaptive filter for the read channel equalization. These coefficients, affected by many kinds of physical noise, are used in the reseeding process of a cryptographic pseudorandom number generator in a family of self encrypting disk drives currently in the market.

  20. Use of a high-frequency linear transducer and MTI filtered color flow mapping in the assessment of fetal heart anatomy at the routine 11 to 13 + 6-week scan: a randomized trial.

    Science.gov (United States)

    Votino, C; Kacem, Y; Dobrescu, O; Dessy, H; Cos, T; Foulon, W; Jani, J

    2012-02-01

    To prospectively assess the contribution of a high-frequency linear transducer and of moving target indicator (MTI) filtered color flow mapping in the visualization of cardiac fetal anatomy at the routine 11 to 13 + 6-week scan. This was a cross-sectional prospective study, including 300 singleton fetuses at 11 to 13 + 6 weeks' gestation. Patients were randomized into four groups and a detailed fetal cardiac examination was conducted transabdominally using either a conventional curvilinear transducer, a conventional curvilinear transducer and MTI filtered color flow mapping, a high-frequency linear transducer or a high-frequency linear transducer and MTI filtered color flow mapping. Regression analysis was used to investigate the effect on the ability to visualize different cardiac structures of the following parameters: gestational age at ultrasound examination; fetal crown-rump length (CRL); maternal body mass index (BMI); transducer-heart distance; the technique used at ultrasound; and the position of the placenta. The four-chamber view was visualized in 89.0% of fetuses and regression analysis showed this rate was correlated with CRL and the use of MTI filtered color flow mapping during ultrasonography, and inversely correlated with BMI and transducer-heart distance. Use of a conventional curvilinear transducer and MTI filtered color flow mapping allowed visualization of the four-chamber view in 97.3% of fetuses, while this was only possible in 84.0% of fetuses using a high-frequency linear transducer. The left and right outflow tracts were visualized in 62.3 and 57.7% of fetuses, respectively. Regression analysis showed that the ability to visualize the left or the right outflow tract was correlated with the use of MTI filtered color flow mapping during scanning and was inversely correlated with transducer-heart distance. The use of a conventional curvilinear transducer and MTI filtered color flow mapping allowed visualization of the left and right outflow

  1. Transcranial Random Noise Stimulation Does Not Improve Behavioral and Neurophysiological Measures in Patients with Subacute Vegetative-Unresponsive Wakefulness State (VS-UWS

    Directory of Open Access Journals (Sweden)

    Mauro Mancuso

    2017-11-01

    Full Text Available Background: The absence of efficient treatments capable to promote central nervous system recovery in patients in vegetative state (VS due to a severe acquired brain injury highlights the need of exploring alternative neuromodulatory treatments that can lead to neurobehavioral gains. Some encouraging preliminary observations suggest that transcranial direct current stimulation could be effective in disorders of consciousness (DoC patients, especially when applied on the dorsolateral prefrontal cortex (DLPFC in patients with minimally conscious state (MCS but not in those with VS.Objective: The primary aim of the present study was to verify if the application of transcranial random noise stimulation (tRNS on the DLPFC might favor improvements of consciousness recovery in subacute VS-UWS.Methods: Nine patients with DoC due to traumatic brain injury (n = 1, anoxia (n = 3, and vascular damage (n = 5, have undergone a randomized, double-blind, sham-controlled, neuromodulatory trial with tRNS of bilateral DLPFC. All patients were in a post-acute phase and the DoC onset ranged from 30 days to 4 months. The diagnosis of DoC was based on internationally established criteria from the Multi-Society Task Force on PVS, and classified as VS or MCS using the JFK Coma Recovery Scale-Revised scores (CRS-R. We used CRS-R, Synek Scale, Ad-Hoc semi-quantitative scale and the Clinical Global Impression-Improvement scale to measure behavioral and electrophysiological changes during tRNS intervention. All patients were also treated with daily conventional rehabilitation treatment.Results: No significant differences emerged between active and sham groups regarding improvements of level of consciousness, as well as on electroencephalographic data. Only one patient showed emergence from VS-UWS, evolving from VS to MCS after the tRNS stimulation, at a distance of 3 weeks from the enrolment into the study.Conclusion: Repeated applications of tRNS of the DLPFC, even if

  2. Auditory filters at low-frequencies

    DEFF Research Database (Denmark)

    Orellana, Carlos Andrés Jurado; Pedersen, Christian Sejer; Møller, Henrik

    2009-01-01

    Prediction and assessment of low-frequency noise problems requires information about the auditory filter characteristics at low-frequencies. Unfortunately, data at low-frequencies is scarce and practically no results have been published for frequencies below 100 Hz. Extrapolation of ERB results...... from previous studies suggests the filter bandwidth keeps decreasing below 100 Hz, although at a relatively lower rate than at higher frequencies. Main characteristics of the auditory filter were studied from below 100 Hz up to 1000 Hz. Center frequencies evaluated were 50, 63, 125, 250, 500, and 1000...... Hz. The notched-noise method was used, with the noise masker at 40 dB spectral density. A rounded exponential auditory filter model (roex(p,r)) was used to fit the masking data. Preliminary data on 1 subject is discussed. Considering the system as a whole (e.g. without removing the assumed middle...

  3. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

    Directory of Open Access Journals (Sweden)

    Wonseok Kang

    2015-09-01

    Full Text Available In very high-resolution (VHR push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3 with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments.

  4. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

    Science.gov (United States)

    Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

    2015-01-01

    In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532

  5. Adaptive EMG noise reduction in ECG signals using noise level approximation

    Science.gov (United States)

    Marouf, Mohamed; Saranovac, Lazar

    2017-12-01

    In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

  6. Image Filtering with Neural Networks: applications and performance evaluation

    NARCIS (Netherlands)

    Spreeuwers, Lieuwe Jan

    1992-01-01

    A simple and elegant method to design image filters with neural networks is proposed: using small networks that scan the image and perform position invariant filtering. In the theses examples of image filtering with error backpropagation networks for edge detection, image deblurring and noise

  7. Stabilization diagrams using operationalmodal analysis and sliding filters

    DEFF Research Database (Denmark)

    Olsen, Peter; Juul, Martin O.; Tarpø, Marius

    2017-01-01

    This paper presents a filtering technique for doing effective operational modal analysis. The result of the filtering method is construction of stabilization diagram that clearly separates physical poles from spurious noise poles needed for unbiased fitting. A band pass filter is moved slowly ove...

  8. Stabilization diagrams using operational modal analysis and sliding filters

    DEFF Research Database (Denmark)

    Olsen, Peter; Juul, Martin Ørum Ørhem; Tarpø, Marius Glindtvad

    2017-01-01

    This paper presents a filtering technique for doing effective operational modal analysis. The result of the filtering method is construction of stabilization diagram that clearly separates physical poles from spurious noise poles needed for unbiased fitting. A band pass filter is moved slowly ove...

  9. An adaptive filter for smoothing noisy radar images

    Science.gov (United States)

    Frost, V. S.; Stiles, J. A.; Shanmugam, K. S.; Holtzman, J. C.; Smith, S. A.

    1981-01-01

    A spatial domain adaptive Wiener filter for smoothing radar images corrupted by multiplicative noise is presented. The filter is optimum in a minimum mean squared error sense, computationally efficient, and preserves edges in the image better than other filters. The proposed algorithm can also be used for processing optical images with illumination variations that have a multiplicative effect.

  10. [The application of adaptive algorithm and wavelet transform in the filtering of ECG signal].

    Science.gov (United States)

    Zhang, Jingzhou; Zhang, Guanglei; Dai, Guanzhong

    2006-10-01

    Electrocardiographic (ECG) signal are a kind of basic physiological signals of human body, and are very important in clinical diagnosis. But the ECG signals from body surface are often interfered by noises such as 50 Hz noise, baseline displacemant, electromyography (EMG) noise and edv. These noises bring obstacle to the diagnosis of cardiovascular diseases. To eliminate the ECG signals noises mentioned above,this paper adopts LMS adaptive algorithm and wavelet transform theory to design three kinds of digital adaptive filters-adaptive noise cancellation filter, wavelet transform filter and adaptive signal dividing filter to filter the corresponding noises. The results show that the three kinds of noises existing in the ECG signal have been efficiently eliminated.

  11. Filtering multifocal VEP signals using Prony's method.

    Science.gov (United States)

    Fernández, A; de Santiago, L; Blanco, R; Pérez-Rico, C; Rodríguez-Ascariz, J M; Barea, R; Miguel-Jiménez, J M; García-Luque, J R; Ortiz del Castillo, M; Sánchez-Morla, E M; Boquete, L

    2015-01-01

    This paper describes use of Prony's method as a filter applied to multifocal visual-evoked-potential (mfVEP) signals. Prony's method can be viewed as an extension of Fourier analysis that allows a signal to be decomposed into a linear combination of functions with different amplitudes, damping factors, frequencies and phase angles. By selecting Prony method parameters, a frequency filter has been developed which improves signal-to-noise ratio (SNR). Three different criteria were applied to data recorded from control subjects to produce three separate datasets: unfiltered raw data, data filtered using the traditional method (fast Fourier transform: FFT), and data filtered using Prony's method. Filtering using Prony's method improved the signals' original SNR by 44.52%, while the FFT filter improved the SNR by 33.56%. The extent to which signal can be separated from noise was analysed using receiver-operating-characteristic (ROC) curves. The area under the curve (AUC) was greater in the signals filtered using Prony's method than in the original signals or in those filtered using the FFT. filtering using Prony's method improves the quality of mfVEP signal pre-processing when compared with the original signals, or with those filtered using the FFT. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Noise Reduction in the Time Domain using Joint Diagonalization

    DEFF Research Database (Denmark)

    Nørholm, Sidsel Marie; Benesty, Jacob; Jensen, Jesper Rindom

    2014-01-01

    , an estimate of the desired signal is found by subtraction of the noise estimate from the observed signal. The filter can be designed to obtain a desired trade-off between noise reduction and signal distortion, depending on the number of eigenvectors included in the filter design. This is explored through...

  13. Noise equivalent circuit of a semiconductor laser diode

    Science.gov (United States)

    Harder, C.; Margalit, S.; Yariv, A.; Katz, J.; Shacham, J.

    1982-01-01

    A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

  14. Noise equivalent circuit of a semiconductor laser diode

    Science.gov (United States)

    Harder, C.; Margalit, S.; Yariv, A.; Katz, J.; Shacham, J.

    1982-03-01

    A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

  15. Adaptive filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2006-01-01

    INTRODUCTIONSignal ProcessingAn ExampleOutline of the TextDISCRETE-TIME SIGNAL PROCESSINGDiscrete Time SignalsTransform-Domain Representation of Discrete-Time SignalsThe Z-TransformDiscrete-Time SystemsProblemsHints-Solutions-SuggestionsRANDOM VARIABLES, SEQUENCES, AND STOCHASTIC PROCESSESRandom Signals and DistributionsAveragesStationary ProcessesSpecial Random Signals and Probability Density FunctionsWiener-Khinchin RelationsFiltering Random ProcessesSpecial Types of Random ProcessesNonparametric Spectra EstimationParametric Methods of power Spectral EstimationProblemsHints-Solutions-SuggestionsWIENER FILTERSThe Mean-Square ErrorThe FIR Wiener FilterThe Wiener SolutionWiener Filtering ExamplesProblemsHints-Solutions-SuggestionsEIGENVALUES OF RX - PROPERTIES OF THE ERROR SURFACEThe Eigenvalues of the Correlation MatrixGeometrical Properties of the Error SurfaceProblemsHints-Solutions-SuggestionsNEWTON AND STEEPEST-DESCENT METHODOne-Dimensional Gradient Search MethodSteepest-Descent AlgorithmProblemsHints-Sol...

  16. Analog Electronic Filters Theory, Design and Synthesis

    CERN Document Server

    Dimopoulos, Hercules G

    2012-01-01

    Filters are essential subsystems in a huge variety of electronic systems. Filter applications are innumerable; they are used for noise reduction, demodulation, signal detection, multiplexing, sampling, sound and speech processing, transmission line equalization and image processing, to name just a few. In practice, no electronic system can exist without filters. They can be found in everything from power supplies to mobile phones and hard disk drives and from loudspeakers and MP3 players to home cinema systems and broadband Internet connections. This textbook introduces basic concepts and methods and the associated mathematical and computational tools employed in electronic filter theory, synthesis and design.  This book can be used as an integral part of undergraduate courses on analog electronic filters. Includes numerous, solved examples, applied examples and exercises for each chapter. Includes detailed coverage of active and passive filters in an independent but correlated manner. Emphasizes real filter...

  17. Low Noise Electronics for BASE Collaboration

    CERN Document Server

    Besirli, Mustafa

    2015-01-01

    In my summer student period, I worked within the BASE (Baryon Antibaryon Symmetry Experiment) Collaboration and I developed low noise electronics such as cryogenic low noise amplifier and high voltage filters. In this report, you can find designs and measurements of my projects.

  18. Filtering and segmentation of the Cassini synthetic aperture radar images on Titan

    Science.gov (United States)

    Bratsolis, E.; Bampasidis, G.; Solomonidou, A.; Coustenis, A.; Hirtzig, M.

    2011-10-01

    A filtering technique is applied to obtain the restored synthetic aperture radar (SAR) images. One of the major problems hampering the derivation of meaningful texture information from SAR imagery is the speckle noise. It overlays "real" structures and causes gray value variations even in homogeneous parts of the image. Our method, the TSPR (total sum preserving regularization) filter, is based on probabilistic methods and regards an image as a random element drawn from a prespecified set of possible images optimized by a synchronous local iterative method. The despeckle filter can be used as intermediate stage for the extraction of meaningful regions that correspond to structural units in the scene or distinguish objects of interest like lakes, drainage networks, equatorial dunes or impact craters, where different textures appear.

  19. Probabilistic solutions of nonlinear oscillators excited by combined colored and white noise excitations

    Science.gov (United States)

    Siu-Siu, Guo; Qingxuan, Shi

    2017-03-01

    In this paper, single-degree-of-freedom (SDOF) systems combined to Gaussian white noise and Gaussian/non-Gaussian colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations with four-coupled first-order differential equations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions, especially the ones in the tail regions of the PDFs. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis. Hopefully, our present work could provide insights into the investigation of structures under random loadings.

  20. Gaussian particle flow implementation of PHD filter

    Science.gov (United States)

    Zhao, Lingling; Wang, Junjie; Li, Yunpeng; Coates, Mark J.

    2016-05-01

    Particle filter and Gaussian mixture implementations of random finite set filters have been proposed to tackle the issue of jointly estimating the number of targets and their states. The Gaussian mixture PHD (GM-PHD) filter has a closed-form expression for the PHD for linear and Gaussian target models, and extensions using the extended Kalman filter or unscented Kalman Filter have been developed to allow the GM-PHD filter to accommodate mildly nonlinear dynamics. Errors resulting from linearization or model mismatch are unavoidable. A particle filter implementation of the PHD filter (PF-PHD) is more suitable for nonlinear and non-Gaussian target models. The particle filter implementations are much more computationally expensive and performance can suffer when the proposal distribution is not a good match to the posterior. In this paper, we propose a novel implementation of the PHD filter named the Gaussian particle flow PHD filter (GPF-PHD). It employs a bank of particle flow filters to approximate the PHD; these play the same role as the Gaussian components in the GM-PHD filter but are better suited to non-linear dynamics and measurement equations. Using the particle flow filter allows the GPF-PHD filter to migrate particles to the dense regions of the posterior, which leads to higher efficiency than the PF-PHD. We explore the performance of the new algorithm through numerical simulations.

  1. EFFECT OF NOISE DISTURBANCES ON THE RESPONSE

    Directory of Open Access Journals (Sweden)

    G. M. Alwan

    2013-05-01

    Full Text Available The present work studies the effect of noise on the dynamic response of pH, conductivity and thermocouple sensors which used into several industrial processes.Thermocouple would be proven had more stability against noise than conductivity and pH meter. The effect of noise on process signals could be condensate as low as possible by using suitable model of filter especially when the sensors were implemented to a digital computer. 

  2. Noise Protection

    Science.gov (United States)

    1980-01-01

    Environmental Health Systems puts forth an increasing effort in the U.S. to develop ways of controlling noise, particularly in industrial environments due to Federal and State laws, labor union insistence and new findings relative to noise pollution impact on human health. NASA's Apollo guidance control system aided in the development of a noise protection product, SMART. The basis of all SMART products is SMART compound a liquid plastic mixture with exceptional energy/sound absorbing qualities. The basic compound was later refined for noise protection use.

  3. Water Filters

    Science.gov (United States)

    1988-01-01

    Seeking to find a more effective method of filtering potable water that was highly contaminated, Mike Pedersen, founder of Western Water International, learned that NASA had conducted extensive research in methods of purifying water on board manned spacecraft. The key is Aquaspace Compound, a proprietary WWI formula that scientifically blends various types of glandular activated charcoal with other active and inert ingredients. Aquaspace systems remove some substances; chlorine, by atomic adsorption, other types of organic chemicals by mechanical filtration and still others by catalytic reaction. Aquaspace filters are finding wide acceptance in industrial, commercial, residential and recreational applications in the U.S. and abroad.

  4. Filter apparatus

    Science.gov (United States)

    Kuban, D.P.; Singletary, B.H.; Evans, J.H.

    A plurality of holding tubes are respectively mounted in apertures in a partition plate fixed in a housing receiving gas contaminated with particulate material. A filter cartridge is removably held in each holding tube, and the cartridges and holding tubes are arranged so that gas passes through apertures therein and across the the partition plate while particulate material is collected in the cartridges. Replacement filter cartridges are respectively held in holding canisters mounted on a support plate which can be secured to the aforesaid housing, and screws mounted on said canisters are arranged to push replacement cartridges into the cartridge holding tubes and thereby eject used cartridges therefrom.

  5. Robust noise attenuation based on nuclear norm minimization and a trace prediction strategy

    Science.gov (United States)

    Zhou, Yatong; Zhang, Shili

    2017-12-01

    Rejecting noise in seismic data while not affecting the amplitude of useful signals is a long standing problem in seismic data processing. Seismic noise attenuation can be formulated as a nuclear norm minimization (NNM) problem. To meet the assumption that seismic data should have low nuclear norm, we first map the seismic data into a low-rank matrix based on a trace prediction strategy. We provide detailed algorithm workflow and mathematical analysis of the trace prediction method. The seismic data after trace rearrangement is demonstrated to be locally low-rank. The NNM problem is then solved via the singular value thresholding (SVT) algorithm. The effectiveness of the proposed method is validated via both synthetic and field data examples. We also test the robustness of the proposed method with respect to random noise, spiky noise, and blending interference. Compared with the state-of-the-art predictive filtering method, median filtering method, singular spectrum analysis method, and curvelet thresholding method, the proposed method obtains an obviously better performance in compromising signal preservation and noise removal.

  6. Quantum image median filtering in the spatial domain

    Science.gov (United States)

    Li, Panchi; Liu, Xiande; Xiao, Hong

    2018-03-01

    Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

  7. Optical noise and temporal coherence

    Science.gov (United States)

    Chavel, P.

    1980-08-01

    Previous articles have been devoted to the study of optical noise as a function of spatial coherence. The present one completes this study by considering temporal coherence. Noise arising from defects in the pupil plane and affecting the high spatial frequencies of an image is notably reduced by white-light illumination. Temporal coherence has little effect on noise arising from defects in the object plane. However, impulse noise due to small isolated defects is reduced in size. Physical arguments are presented to explain these phenomena and a mathematical study of partially coherent imaging in the presence of random defects is given.

  8. Filter This

    Directory of Open Access Journals (Sweden)

    Audrey Barbakoff

    2011-03-01

    Full Text Available In the Library with the Lead Pipe welcomes Audrey Barbakoff, a librarian at the Milwaukee Public Library, and Ahniwa Ferrari, Virtual Experience Manager at the Pierce County Library System in Washington, for a point-counterpoint piece on filtering in libraries. The opinions expressed here are those of the authors, and are not endorsed by their employers. [...

  9. Techniques for noise removal and registration of TIMS data

    Science.gov (United States)

    Hummer-Miller, S.

    1990-01-01

    Extracting subtle differences from highly correlated thermal infrared aircraft data is possible with appropriate noise filters, constructed and applied in the spatial frequency domain. This paper discusses a heuristic approach to designing noise filters for removing high- and low-spatial frequency striping and banding. Techniques for registering thermal infrared aircraft data to a topographic base using Thematic Mapper data are presented. The noise removal and registration techniques are applied to TIMS thermal infrared aircraft data. -Author

  10. Adaptive Noise Cancellation for speech Employing Fuzzy and Neural Network

    OpenAIRE

    Mohammed Hussein Miry; Ali Hussein Miry; Hussain Kareem Khleaf

    2011-01-01

    Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications such as noise cancellation. Noise cancellation is a common occurrence in today telecommunication systems. The LMS algorithm which is one of the most efficient criteria for determining the values of the adaptive noise cancellation coefficient...

  11. Fast Noise Compensation and Adaptive Enhancement for Speech Separation

    Directory of Open Access Journals (Sweden)

    Hu Rong

    2008-01-01

    Full Text Available We propose a novel approach to improve adaptive decorrelation filtering- (ADF- based speech source separation in diffuse noise. The effects of noise on system adaptation and separation outputs are handled separately. First, fast noise compensation (NC is developed for adaptation of separation filters, forcing ADF to focus on source separation; next, output noises are suppressed by speech enhancement. By tracking noise components in output cross-correlation functions, the bias effect of noise on the system adaptation objective function is compensated, and by adaptively estimating output noise autocorrelations, the speech separation output is enhanced. For fast noise compensation, a blockwise fast ADF (FADF is implemented. Experiments were conducted on real and simulated diffuse noises. Speech mixtures were generated by convolving TIMIT speech sources with acoustic path impulse responses measured in a real room with reverberation time  second. The proposed techniques significantly improved separation performance and phone recognition accuracy of ADF outputs.

  12. Discrete filtering techniques applied to sequential GPS range measurements

    Science.gov (United States)

    Vangraas, Frank

    1987-01-01

    The basic navigation solution is described for position and velocity based on range and delta range (Doppler) measurements from NAVSTAR Global Positioning System satellites. The application of discrete filtering techniques is examined to reduce the white noise distortions on the sequential range measurements. A second order (position and velocity states) Kalman filter is implemented to obtain smoothed estimates of range by filtering the dynamics of the signal from each satellite separately. Test results using a simulated GPS receiver show a steady-state noise reduction, the input noise variance divided by the output noise variance, of a factor of four. Recommendations for further noise reduction based on higher order Kalman filters or additional delta range measurements are included.

  13. Time-domain noise reduction based on an orthogonal decomposition for desired signal extraction.

    Science.gov (United States)

    Benesty, Jacob; Chen, Jingdong; Arden Huang, Yiteng; Gaensler, Tomas

    2012-07-01

    This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.

  14. Clustering of noise-induced oscillations

    DEFF Research Database (Denmark)

    Sosnovtseva, Olga; Fomin, A I; Postnov, D E

    2001-01-01

    The subject of our study is clustering in a population of excitable systems driven by Gaussian white noise and with randomly distributed coupling strength. The cluster state is frequency-locked state in which all functional units run at the same noise-induced frequency. Cooperative dynamics...... of this regime is described in terms of effective synchronization and noise-induced coherence....

  15. Classroom Noise and Teachers' Voice Production

    Science.gov (United States)

    Rantala, Leena M.; Hakala, Suvi; Holmqvist, Sofia; Sala, Eeva

    2015-01-01

    Purpose: The aim of this study was to research the associations between noise (ambient and activity noise) and objective metrics of teachers' voices in real working environments (i.e., classrooms). Method: Thirty-two female and 8 male teachers from 14 elementary schools were randomly selected for the study. Ambient noise was measured during breaks…

  16. Summary of thermal, shot and flicker noise in detectors and readout circuits

    CERN Document Server

    Seller, P

    1999-01-01

    The techniques for calculating noise in electronic circuits are well known (P. Seller, Nucl. Instr. and Meth. A 408 (1998) 603). These have been used here to tabulate the output noise variance and the Equivalent input Noise Charge (ENC) for time-invariant filter circuits often used for reading out detector systems. This is followed by some comparisons of the performance of different filters.

  17. Spectral-spatial classification of hyperspectral images using trilateral filter and stacked sparse autoencoder

    Science.gov (United States)

    Zhao, Chunhui; Wan, Xiaoqing; Zhao, Genping; Yan, Yiming

    2017-01-01

    A spectral-spatial classification method using a trilateral filter (TF) and stacked sparse autoencoder (SSA) for improving the classification accuracy of hyperspectral image (HSI) is proposed. The operation is carried out in two main stages: edge-preserved smoothing and high-level feature learning. First, a reference image obtained from dual tree complex wavelet transform is adopted in a TF for smoothing the HSI. As expected, the filter not only can effectively attenuate the mixed noise (e.g., Gaussian noise and impulse noise) where the bilateral filter shows poor performance but also can produce useful spectral-spatial features from HSI by considering geometric closeness and photometric similarity between pixels simultaneously. Second, an artificial fish swarm algorithm (AFSA) is first introduced into a SSA, and the proposed deep learning architecture is used to adaptively exploit more abstract and differentiable high-level feature representations from the smoothed HSI, based on the factor that AFSA provides better trade-off among concurrency, search efficiency, and convergence rate compared with gradient descent and back-propagation algorithms in a traditional SSA. Finally, a random forest classifier is utilized to perform supervised fine-tuning and classification. Experimental results on two real HSI data sets demonstrate that the proposed method generates competitive performance compared with those of conventional methods.

  18. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  19. Estimasi Variabel Dinamik Menggunakan Metode Kalman Filter

    Directory of Open Access Journals (Sweden)

    Nathanael Leon Gozali

    2013-09-01

    Full Text Available Sebuah sistem pengendalian kapal dituntut untuk memiliki akurasi yang tinggi. Hal ini dituntut dengan adanya sistem pengendalian otomatis yang dibuat dengan menjadikan feedback dari alat ukur sebagai nilai yang mempengaruhi  pengendali. Dengan alat ukur yang memiliki noise dan sistem yang memiliki noise sehingga tidak sesuai dengan perancangan sistem tersebut menjadi penyebab ketidaktepatan dalam pengendalian kapal. Meskipun noise bernilai kecil namun dalam waktu yang lama dan terus menerus terakumulasi sehingga pengendalian tidak berjalan dengan baik. Tujuan dari penelitian ini adalah untuk merancang sebuah estimator Kalman Filter pada kondisi noise dari alat ukur, noise dari sistem kapal dan ketidaktepatan dalam pemodelan. Metode Kalman Filter yang digunakan adalah metode Kalman Filter diskrit linier karena model dinamika kapal telah dilinierisai dan didiskritisasi terlebih dahulu. Variabel dinamik kapal yang diestimasi untuk keperluan steering adalah dinamika sway-yaw dengan variabel kecepatan sudut, posisi sudut dan kecepatan arah sway. Perancangan sistem berdasarkan spesifikasi kapal perang kelas SIGMA Extended. Berdasarkan hasil simulasi, estimator yang dirancang  mampu memberikan nilai estimasi pada ketiga variabel dinamika kapal dengan persentase integral absolute error dari sistem dengan noise sistem dan noise pengukuran sebesar 0,41% untuk variabel yaw, 4,30% untuk yaw-rate dan 6,78% untuk sway-rate.

  20. Water Filter

    Science.gov (United States)

    1982-01-01

    A compact, lightweight electrolytic water sterilizer available through Ambassador Marketing, generates silver ions in concentrations of 50 to 100 parts per billion in water flow system. The silver ions serve as an effective bactericide/deodorizer. Tap water passes through filtering element of silver that has been chemically plated onto activated carbon. The silver inhibits bacterial growth and the activated carbon removes objectionable tastes and odors caused by addition of chlorine and other chemicals in municipal water supply. The three models available are a kitchen unit, a "Tourister" unit for portable use while traveling and a refrigerator unit that attaches to the ice cube water line. A filter will treat 5,000 to 10,000 gallons of water.