Huang, Lei
2015-01-01
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. PMID:26437409
Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal
Lin, Tingting; Zhang, Yang; Yi, Xiaofeng; Fan, Tiehu; Wan, Ling
2018-05-01
When measuring in a geomagnetic field, the method of magnetic resonance sounding (MRS) is often limited because of the notably low signal-to-noise ratio (SNR). Most current studies focus on discarding spiky noise and power-line harmonic noise cancellation. However, the effects of random noise should not be underestimated. The common method for random noise attenuation is stacking, but collecting multiple recordings merely to suppress random noise is time-consuming. Moreover, stacking is insufficient to suppress high-level random noise. Here, we propose the use of time-frequency peak filtering for random noise attenuation, which is performed after the traditional de-spiking and power-line harmonic removal method. By encoding the noisy signal with frequency modulation and estimating the instantaneous frequency using the peak of the time-frequency representation of the encoded signal, the desired MRS signal can be acquired from only one stack. The performance of the proposed method is tested on synthetic envelope signals and field data from different surveys. Good estimations of the signal parameters are obtained at different SNRs. Moreover, an attempt to use the proposed method to handle a single recording provides better results compared to 16 stacks. Our results suggest that the number of stacks can be appropriately reduced to shorten the measurement time and improve the measurement efficiency.
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.
Block matching 3D random noise filtering for absorption optical projection tomography
International Nuclear Information System (INIS)
Fumene Feruglio, P; Vinegoni, C; Weissleder, R; Gros, J; Sbarbati, A
2010-01-01
Absorption and emission optical projection tomography (OPT), alternatively referred to as optical computed tomography (optical-CT) and optical-emission computed tomography (optical-ECT), are recently developed three-dimensional imaging techniques with value for developmental biology and ex vivo gene expression studies. The techniques' principles are similar to the ones used for x-ray computed tomography and are based on the approximation of negligible light scattering in optically cleared samples. The optical clearing is achieved by a chemical procedure which aims at substituting the cellular fluids within the sample with a cell membranes' index matching solution. Once cleared the sample presents very low scattering and is then illuminated with a light collimated beam whose intensity is captured in transillumination mode by a CCD camera. Different projection images of the sample are subsequently obtained over a 360 0 full rotation, and a standard backprojection algorithm can be used in a similar fashion as for x-ray tomography in order to obtain absorption maps. Because not all biological samples present significant absorption contrast, it is not always possible to obtain projections with a good signal-to-noise ratio, a condition necessary to achieve high-quality tomographic reconstructions. Such is the case for example, for early stage's embryos. In this work we demonstrate how, through the use of a random noise removal algorithm, the image quality of the reconstructions can be considerably improved even when the noise is strongly present in the acquired projections. Specifically, we implemented a block matching 3D (BM3D) filter applying it separately on each acquired transillumination projection before performing a complete three-dimensional tomographical reconstruction. To test the efficiency of the adopted filtering scheme, a phantom and a real biological sample were processed. In both cases, the BM3D filter led to a signal-to-noise ratio increment of over 30 d
Directory of Open Access Journals (Sweden)
Hongtao Yang
2018-01-01
Full Text Available This paper proposes a novel strong tracking filter (STF, which is suitable for dealing with the filtering problem of nonlinear systems when the following cases occur: that is, the constructed model does not match the actual system, the measurements have the one-step random delay, and the process and measurement noises are correlated at the same epoch. Firstly, a framework of decoupling filter (DF based on equivalent model transformation is derived. Further, according to the framework of DF, a new extended Kalman filtering (EKF algorithm via using first-order linearization approximation is developed. Secondly, the computational process of the suboptimal fading factor is derived on the basis of the extended orthogonality principle (EOP. Thirdly, the ultimate form of the proposed STF is obtained by introducing the suboptimal fading factor into the above EKF algorithm. The proposed STF can automatically tune the suboptimal fading factor on the basis of the residuals between available and predicted measurements and further the gain matrices of the proposed STF tune online to improve the filtering performance. Finally, the effectiveness of the proposed STF has been proved through numerical simulation experiments.
International Nuclear Information System (INIS)
Theodorsen, A; Garcia, O E; Rypdal, M
2017-01-01
Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here 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 lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model 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 identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type. (paper)
Passive Noise Filtering by Cellular Compartmentalization.
Stoeger, Thomas; Battich, Nico; Pelkmans, Lucas
2016-03-10
Chemical reactions contain an inherent element of randomness, which presents itself as noise that interferes with cellular processes and communication. Here we discuss the ability of the spatial partitioning of molecular systems to filter and, thus, remove noise, while preserving regulated and predictable differences between single living cells. In contrast to active noise filtering by network motifs, cellular compartmentalization is highly effective and easily scales to numerous systems without requiring a substantial usage of cellular energy. We will use passive noise filtering by the eukaryotic cell nucleus as an example of how this increases predictability of transcriptional output, with possible implications for the evolution of complex multicellularity. Copyright © 2016 Elsevier Inc. All rights reserved.
Musical noise reduction using an adaptive filter
Hanada, Takeshi; Murakami, Takahiro; Ishida, Yoshihisa; Hoya, Tetsuya
2003-10-01
This paper presents a method for reducing a particular noise (musical noise). The musical noise is artificially produced by Spectral Subtraction (SS), which is one of the most conventional methods for speech enhancement. The musical noise is the tin-like sound and annoying in human auditory. We know that the duration of the musical noise is considerably short in comparison with that of speech, and that the frequency components of the musical noise are random and isolated. In the ordinary SS-based methods, the musical noise is removed by the post-processing. However, the output of the ordinary post-processing is delayed since the post-processing uses the succeeding frames. In order to improve this problem, we propose a novel method using an adaptive filter. In the proposed system, the observed noisy signal is used as the input signal to the adaptive filter and the output of SS is used as the reference signal. In this paper we exploit the normalized LMS (Least Mean Square) algorithm for the adaptive filter. Simulation results show that the proposed method has improved the intelligibility of the enhanced speech in comparison with the conventional method.
Filter apparatus for actively reducing noise
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
A filter apparatus for actively reducing noise
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
Noise reduction with complex bilateral filter.
Matsumoto, Mitsuharu
2017-12-01
This study introduces a noise reduction technique that uses a complex bilateral filter. A bilateral filter is a nonlinear filter originally developed for images that can reduce noise while preserving edge information. It is an attractive filter and has been used in many applications in image processing. When it is applied to an acoustical signal, small-amplitude noise is reduced while the speech signal is preserved. However, a bilateral filter cannot handle noise with relatively large amplitudes owing to its innate characteristics. In this study, the noisy signal is transformed into the time-frequency domain and the filter is improved to handle complex spectra. The high-amplitude noise is reduced in the time-frequency domain via the proposed filter. The features and the potential of the proposed filter are also confirmed through experiments.
Selection of noise parameters for Kalman filter
Institute of Scientific and Technical Information of China (English)
Ka-Veng Yuen; Ka-In Hoi; Kai-Meng Mok
2007-01-01
The Bayesian probabilistic approach is proposed to estimate the process noise and measurement noise parameters for a Kalman filter. With state vectors and covariance matrices estimated by the Kalman filter, the likehood of the measurements can be constructed as a function of the process noise and measurement noise parameters. By maximizing the likklihood function with respect to these noise parameters, the optimal values can be obtained. Furthermore, the Bayesian probabilistic approach allows the associated uncertainty to be quantified. Examples using a single-degree-of-freedom system and a ten-story building illustrate the proposed method. The effect on the performance of the Kalman filter due to the selection of the process noise and measurement noise parameters was demonstrated. The optimal values of the noise parameters were found to be close to the actual values in the sense that the actual parameters were in the region with significant probability density. Through these examples, the Bayesian approach was shown to have the capability to provide accurate estimates of the noise parameters of the Kalman filter, and hence for state estimation.
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...... in the expected sense. The second scheme is a Las Vegas algorithm using filtering triggers: Its effectiveness is the same as enforcing are consistency after every domain event, while in the expected case it is faster by a factor of m/n, where n and m are, respectively, the number of nodes and edges...
Complex noise suppression using a sparse representation and 3D filtering of images
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.
Noise Reduction of Measurement Data using Linear Digital Filters
Directory of Open Access Journals (Sweden)
Hitzmann B.
2007-12-01
Full Text Available In this paper Butterworth, Chebyshev (Type I and II and Elliptic digital filters are designed for signal noise reduction. On-line data measurements of substrate concentration from E. coli fed-batch cultivation process are used. Application of the designed filters leads to a successful noise reduction of on-line glucose measurements. The digital filters presented here are simple, easy to implement and effective - the used filters allow for a smart compromise between signal information and noise corruption.
Simulation for noise cancellation using LMS adaptive filter
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.
Quantum-noise randomized ciphers
International Nuclear Information System (INIS)
Nair, Ranjith; Yuen, Horace P.; Kumar, Prem; Corndorf, Eric; Eguchi, Takami
2006-01-01
We review the notion of a classical random cipher and its advantages. We sharpen the usual description of random ciphers to a particular mathematical characterization suggested by the salient feature responsible for their increased security. We describe a concrete system known as αη and show that it is equivalent to a random cipher in which the required randomization is affected by coherent-state quantum noise. We describe the currently known security features of αη and similar systems, including lower bounds on the unicity distances against ciphertext-only and known-plaintext attacks. We show how αη used in conjunction with any standard stream cipher such as the Advanced Encryption Standard provides an additional, qualitatively different layer of security from physical encryption against known-plaintext attacks on the key. We refute some claims in the literature that αη is equivalent to a nonrandom stream cipher
Random Valued Impulse Noise Removal Using Region Based Detection Approach
Directory of Open Access Journals (Sweden)
S. Banerjee
2017-12-01
Full Text Available Removal of random valued noisy pixel is extremely challenging when the noise density is above 50%. The existing filters are generally not capable of eliminating such noise when density is above 70%. In this paper a region wise density based detection algorithm for random valued impulse noise has been proposed. On the basis of the intensity values, the pixels of a particular window are sorted and then stored into four regions. The higher density based region is considered for stepwise detection of noisy pixels. As a result of this detection scheme a maximum of 75% of noisy pixels can be detected. For this purpose this paper proposes a unique noise removal algorithm. It was experimentally proved that the proposed algorithm not only performs exceptionally when it comes to visual qualitative judgment of standard images but also this filter combination outsmarts the existing algorithm in terms of MSE, PSNR and SSIM comparison even up to 70% noise density level.
Kernel-based noise filtering of neutron detector signals
International Nuclear Information System (INIS)
Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki
2007-01-01
This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests
Preconditioner-free Wiener filtering with a dense noise matrix
Huffenberger, Kevin M.
2018-05-01
This work extends the Elsner & Wandelt (2013) iterative method for efficient, preconditioner-free Wiener filtering to cases in which the noise covariance matrix is dense, but can be decomposed into a sum whose parts are sparse in convenient bases. The new method, which uses multiple messenger fields, reproduces Wiener-filter solutions for test problems, and we apply it to a case beyond the reach of the Elsner & Wandelt (2013) method. We compute the Wiener-filter solution for a simulated Cosmic Microwave Background (CMB) map that contains spatially varying, uncorrelated noise, isotropic 1/f noise, and large-scale horizontal stripes (like those caused by atmospheric noise). We discuss simple extensions that can filter contaminated modes or inverse-noise-filter the data. These techniques help to address complications in the noise properties of maps from current and future generations of ground-based Microwave Background experiments, like Advanced ACTPol, Simons Observatory, and CMB-S4.
Dynamical noise filter and conditional entropy analysis in chaos synchronization.
Wang, Jiao; Lai, C-H
2006-06-01
It is shown that, in a chaotic synchronization system whose driving signal is exposed to channel noise, the estimation of the drive system states can be greatly improved by applying the dynamical noise filtering to the response system states. If the noise is bounded in a certain range, the estimation errors, i.e., the difference between the filtered responding states and the driving states, can be made arbitrarily small. This property can be used in designing an alternative digital communication scheme. An analysis based on the conditional entropy justifies the application of dynamical noise filtering in generating quality synchronization.
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.
Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering
Institute of Scientific and Technical Information of China (English)
FENG Yu-hu
2005-01-01
By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.
Kalman Filtering for Delayed Singular Systems with Multiplicative Noise
Institute of Scientific and Technical Information of China (English)
Xiao Lu; Linglong Wang; Haixia Wang; Xianghua Wang
2016-01-01
Kalman filtering problem for singular systems is dealt with, where the measurements consist of instantaneous measurements and delayed ones, and the plant includes multiplicative noise. By utilizing standard singular value decomposition, the restricted equivalent delayed system is presented, and the Kalman filters for the restricted equivalent system are given by using the well-known re-organization of innovation analysis lemma. The optimal Kalman filter for the original system is given based on the above Kalman filter by recursive Riccati equations, and a numerical example is presented to show the validity and efficiency of the proposed approach, where the comparison between the filter and predictor is also given.
High-order noise filtering in nontrivial quantum logic gates
CSIR Research Space (South Africa)
Green, T
2012-07-01
Full Text Available composed of arbitrary control sequences. We present a general method to calculate the ensemble-averaged entanglement fidelity to arbitrary order in terms of noise filter functions, and provide explicit expressions to fourth order in the noise strength...
Noise and resolution with digital filtering for nuclear spectrometry
International Nuclear Information System (INIS)
Lakatos, T.
1991-01-01
Digital noise filtering looks very promising for semiconductor spectrometry. The resolution and conversion speed of the analog to digital converter (ADC) used at the input of a digital signal processor and analyzer can strongly influence the signal to noise ratio, the peak position and shape. The article leads with the investigation of these effects using computer modelling. (orig.)
White noise theory of robust nonlinear filtering with correlated state and observation noises
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
White noise theory of robust nonlinear filtering with correlated state and observation noises
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
Noise Reduction with Optimal Variable Span Linear Filters
DEFF Research Database (Denmark)
Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll
2016-01-01
In this paper, the problem of noise reduction is addressed as a linear filtering problem in a novel way by using concepts from subspace-based enhancement methods, resulting in variable span linear filters. This is done by forming the filter coefficients as linear combinations of a number...... included in forming the filter. Using these concepts, a number of different filter designs are considered, like minimum distortion, Wiener, maximum SNR, and tradeoff filters. Interestingly, all these can be expressed as special cases of variable span filters. We also derive expressions for the speech...... demonstrate the advantages and properties of the variable span filter designs, and their potential performance gain compared to widely used speech enhancement methods....
Impulsive noise removal from color video with morphological filtering
Ruchay, Alexey; Kober, Vitaly
2017-09-01
This paper deals with impulse noise removal from color video. The proposed noise removal algorithm employs a switching filtering for denoising of color video; that is, detection of corrupted pixels by means of a novel morphological filtering followed by removal of the detected pixels on the base of estimation of uncorrupted pixels in the previous scenes. With the help of computer simulation we show that the proposed algorithm is able to well remove impulse noise in color video. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.
Particle filters for random set models
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...
Applications of adaptive filters in active noise control
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.
Kalman-Takens filtering in the presence of dynamical noise
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.
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.
High-order noise filtering in nontrivial quantum logic gates.
Green, Todd; Uys, Hermann; Biercuk, Michael J
2012-07-13
Treating the effects of a time-dependent classical dephasing environment during quantum logic operations poses a theoretical challenge, as the application of noncommuting control operations gives rise to both dephasing and depolarization errors 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 composed of arbitrary control sequences. We present a general method to calculate the ensemble-averaged entanglement fidelity to arbitrary order in terms of noise filter functions, and provide explicit expressions to fourth order in the noise strength. In the weak noise limit we derive explicit filter functions for a broad class of piecewise-constant control sequences, and use them to study the performance of dynamically corrected gates, yielding good agreement with brute-force numerics.
Removal of Stationary Sinusoidal Noise from Random Vibration Signals.
Energy Technology Data Exchange (ETDEWEB)
Johnson, Brian; Cap, Jerome S.
2018-02-01
In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metrics to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.
Reduced Rank Adaptive Filtering in Impulsive Noise Environments
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.
Reduced Rank Adaptive Filtering in Impulsive Noise Environments
Soury, Hamza; Abed-Meraim, Karim; Alouini, Mohamed-Slim
2014-01-01
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.
Arbitrary-step randomly delayed robust filter with application to boost phase tracking
Qin, Wutao; Wang, Xiaogang; Bai, Yuliang; Cui, Naigang
2018-04-01
The conventional filters such as extended Kalman filter, unscented Kalman filter and cubature Kalman filter assume that the measurement is available in real-time and the measurement noise is Gaussian white noise. But in practice, both two assumptions are invalid. To solve this problem, a novel algorithm is proposed by taking the following four steps. At first, the measurement model is modified by the Bernoulli random variables to describe the random delay. Then, the expression of predicted measurement and covariance are reformulated, which could get rid of the restriction that the maximum number of delay must be one or two and the assumption that probabilities of Bernoulli random variables taking the value one are equal. Next, the arbitrary-step randomly delayed high-degree cubature Kalman filter is derived based on the 5th-degree spherical-radial rule and the reformulated expressions. Finally, the arbitrary-step randomly delayed high-degree cubature Kalman filter is modified to the arbitrary-step randomly delayed high-degree cubature Huber-based filter based on the Huber technique, which is essentially an M-estimator. Therefore, the proposed filter is not only robust to the randomly delayed measurements, but robust to the glint noise. The application to the boost phase tracking example demonstrate the superiority of the proposed algorithms.
Precomputing Process Noise Covariance for Onboard Sequential Filters
Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell
2017-01-01
Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
A Tunable Low Noise Active Bandpass Filter Using a Noise Canceling Technique
Soltani, N.
2016-01-01
A monolithic tunable low noise active bandpass filter is presented in this study. Biasing voltages can control the center frequency and quality factor. By keeping the gain constant, the center frequency shift is 300 MHz. The quality factor can range from 90 to 290 at the center frequency. By using a noise cancelling circuit, noise is kept lower than 2.8 dB. The proposed filter is designed using MMIC technology with a center frequency of 2.4 GHz and a power consumption of 180 mW. ED02AH techno...
A Tunable Low Noise Active Bandpass Filter Using a Noise Canceling Technique
Directory of Open Access Journals (Sweden)
N. Soltani
2016-12-01
Full Text Available A monolithic tunable low noise active bandpass filter is presented in this study. Biasing voltages can control the center frequency and quality factor. By keeping the gain constant, the center frequency shift is 300 MHz. The quality factor can range from 90 to 290 at the center frequency. By using a noise cancelling circuit, noise is kept lower than 2.8 dB. The proposed filter is designed using MMIC technology with a center frequency of 2.4 GHz and a power consumption of 180 mW. ED02AH technology is used to simulate the circuit elements.
Kalman Filtering for Delayed Singular Systems with Multiplicative Noise
Institute of Scientific and Technical Information of China (English)
Xiao Lu; Linglong Wang; Haixia Wang; Xianghua Wang
2016-01-01
Kalman filtering problem for singular systems is dealt with,where the measurements consist of instantaneous measurements and delayed ones,and the plant includes multiplicative noise.By utilizing standard singular value decomposition,the restricted equivalent delayed system is presented,and the Kalman filters for the restricted equivalent system are given by using the well-known re-organization of innovation analysis lemma.The optimal Kalman filter for the original system is given based on the above Kalman filter by recursive Riccati equations,and a numerical example is presented to show the validity and efficiency of the proposed approach,where the comparison between the filter and predictor is also given.
Walsh-synthesized noise filters for quantum logic
International Nuclear Information System (INIS)
Ball, Harrison; Biercuk, Michael J.
2015-01-01
We study a novel class of open-loop control protocols constructed to perform arbitrary nontrivial single-qubit logic operations robust against time-dependent non-Markovian noise. Amplitude and phase modulation protocols are crafted leveraging insights from functional synthesis and the basis set of Walsh functions. We employ the experimentally validated generalized filter-transfer function formalism in order to find optimized control protocols for target operations in SU(2) by defining a cost function for the filter-transfer function to be minimized through the applied modulation. Our work details the various techniques by which we define and then optimize the filter-synthesis process in the Walsh basis, including the definition of specific analytic design rules which serve to efficiently constrain the available synthesis space. This approach yields modulated-gate constructions consisting of chains of discrete pulse-segments of arbitrary form, whose modulation envelopes possess intrinsic compatibility with digital logic and clocking. We derive novel families of Walsh-modulated noise filters designed to suppress dephasing and coherent amplitude-damping noise, and describe how well-known sequences derived in NMR also fall within the Walsh-synthesis framework. Finally, our work considers the effects of realistic experimental constraints such as limited modulation bandwidth on achievable filter performance. (orig.)
Walsh-synthesized noise filters for quantum logic
Energy Technology Data Exchange (ETDEWEB)
Ball, Harrison; Biercuk, Michael J. [The University of Sydney, ARC Centre for Engineered Quantum Systems, School of Physics, Sydney, NSW (Australia); National Measurement Institute, Sydney, NSW (Australia)
2015-05-14
We study a novel class of open-loop control protocols constructed to perform arbitrary nontrivial single-qubit logic operations robust against time-dependent non-Markovian noise. Amplitude and phase modulation protocols are crafted leveraging insights from functional synthesis and the basis set of Walsh functions. We employ the experimentally validated generalized filter-transfer function formalism in order to find optimized control protocols for target operations in SU(2) by defining a cost function for the filter-transfer function to be minimized through the applied modulation. Our work details the various techniques by which we define and then optimize the filter-synthesis process in the Walsh basis, including the definition of specific analytic design rules which serve to efficiently constrain the available synthesis space. This approach yields modulated-gate constructions consisting of chains of discrete pulse-segments of arbitrary form, whose modulation envelopes possess intrinsic compatibility with digital logic and clocking. We derive novel families of Walsh-modulated noise filters designed to suppress dephasing and coherent amplitude-damping noise, and describe how well-known sequences derived in NMR also fall within the Walsh-synthesis framework. Finally, our work considers the effects of realistic experimental constraints such as limited modulation bandwidth on achievable filter performance. (orig.)
Random Correlation Matrix and De-Noising
Ken-ichi Mitsui; Yoshio Tabata
2006-01-01
In Finance, the modeling of a correlation matrix is one of the important problems. In particular, the correlation matrix obtained from market data has the noise. Here we apply the de-noising processing based on the wavelet analysis to the noisy correlation matrix, which is generated by a parametric function with random parameters. First of all, we show that two properties, i.e. symmetry and ones of all diagonal elements, of the correlation matrix preserve via the de-noising processing and the...
Unscented Kalman filtering in the additive noise case
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The unscented Kalman filter(UKF) has four implementations in the additive noise case,according to whether the state is augmented with noise vectors and whether a new set of sigma points is redrawn from the predicted state(which is so-called resampling) for the observation prediction.This paper concerns the differences of performances for those implementations,such as accuracy,adaptability,computational complexity,etc.The conditionally equivalent relationships between the augmented and non-augmented unscented transforms(UTs) are proved for several sampling strategies that are commonly used.Then,we find that the augmented and non-augmented UKFs have the same filter results with the additive measurement noise,but only have the same state predictions with the additive process noise.Resampling is not believed to be necessary in some researches.However,we find out that resampling can be helpful for an adaptive Kalman gain.This will improve the convergence and accuracy of the filter when the large scale state modeling bias or unknown maneuvers occur.Finally,some universal designing principles for a practical UKF are given as follows:1) for the additive observation noise case,it’s better to use the non-augmented UKF;2) for the additive process noise case,when the small state modeling bias or maneuvers are involved,the non-resampling algorithms with state whether augmented or not are candidates for filters;3) the resampling and non-augmented algorithm is the only choice while the large state modeling bias or maneuvers are latent.
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.
Microseismic Event Location Improvement Using Adaptive Filtering for Noise Attenuation
de Santana, F. L., Sr.; do Nascimento, A. F.; Leandro, W. P. D. N., Sr.; de Carvalho, B. M., Sr.
2017-12-01
In this work we show how adaptive filtering noise suppression improves the effectiveness of the Source Scanning Algorithm (SSA; Kao & Shan, 2004) in microseism location in the context of fracking operations. The SSA discretizes the time and region of interest in a 4D vector and, for each grid point and origin time, a brigthness value (seismogram stacking) is calculated. For a given set of velocity model parameters, when origin time and hypocenter of the seismic event are correct, a maximum value for coherence (or brightness) is achieved. The result is displayed on brightness maps for each origin time. Location methods such as SSA are most effective when the noise present in the seismograms is incoherent, however, the method may present false positives when the noise present in the data is coherent as occurs in fracking operations. To remove from the seismograms, the coherent noise from the pump and engines used in the operation, we use an adaptive filter. As the noise reference, we use the seismogram recorded at the station closest to the machinery employed. Our methodology was tested on semi-synthetic data. The microseismic was represented by Ricker pulses (with central frequency of 30Hz) on synthetics seismograms, and to simulate real seismograms on a surface microseismic monitoring situation, we added real noise recorded in a fracking operation to these synthetics seismograms. The results show that after the filtering of the seismograms, we were able to improve our detection threshold and to achieve a better resolution on the brightness maps of the located events.
Reduced rank adaptive filtering in impulsive noise environments
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.
Development of a noise filter for radiation thickness gagemeter
International Nuclear Information System (INIS)
Jee, C. W.; Kim, Y. T.; Lee, H. H.
1995-01-01
The objective of this study is to develop a filter which attenuates sensor noises of radiation thickness gagemeters of the fifth stand of TCM No. 1 in Pohang steel works. The thickness control loop for the fifth stand is modelled as a system for filter design, where the system input is the speed control input and the system output is the gagemeter output. In the design of a filter, the system is described by an ARMAX(AutoRegressive Moving-Average with auXiliary input) model. The parameters of this model are then estimated by using a recursive least square method. Secondly, the ARMAX model, the estimated system, is transformed into an observer canonical state space form. Thirdly, Kalman filtering is applied to obtain optimal estimates of the state and hence those of thickness measurements of steel strips. In addition, a separate low pass filter is designed, which is directly applicable to the gagemeter outputs. Finally, the designed filter algorithms are implemented and tested on a VMEbus board computer under VxWorks real-time operating system. (author)
Shanmugavadivu, P.; Eliahim Jeevaraj, P. S.
2014-06-01
The Adaptive Iterated Functions Systems (AIFS) Filter presented in this paper has an outstanding potential to attenuate the fixed-value impulse noise in images. This filter has two distinct phases namely noise detection and noise correction which uses Measure of Statistics and Iterated Function Systems (IFS) respectively. The performance of AIFS filter is assessed by three metrics namely, Peak Signal-to-Noise Ratio (PSNR), Mean Structural Similarity Index Matrix (MSSIM) and Human Visual Perception (HVP). The quantitative measures PSNR and MSSIM endorse the merit of this filter in terms of degree of noise suppression and details/edge preservation respectively, in comparison with the high performing filters reported in the recent literature. The qualitative measure HVP confirms the noise suppression ability of the devised filter. This computationally simple noise filter broadly finds application wherein the images are highly degraded by fixed-value impulse noise.
Using Kalman Filters to Reduce Noise from RFID Location System
Xavier, José; Reis, Luís Paulo; Petry, Marcelo
2014-01-01
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). PMID:24592186
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.
Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images
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.
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.
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.
Image restoration by Wiener filtering in the presence of signal-dependent noise.
Kondo, K; Ichioka, Y; Suzuki, T
1977-09-01
An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.
Filtering Performance Comparison of Kernel and Wavelet Filters for Reactivity Signal Noise
International Nuclear Information System (INIS)
Park, Moon Ghu; Shin, Ho Cheol; Lee, Yong Kwan; You, Skin
2006-01-01
Nuclear reactor power deviation from the critical state is a parameter of specific interest defined by the reactivity measuring neutron population. Reactivity is an extremely important quantity used to define many of the reactor startup physics parameters. The time dependent reactivity is normally determined by solving the using inverse neutron kinetics equation. The reactivity computer is a device to provide an on-line solution of the inverse kinetics equation. The measurement signal of the neutron density is normally noise corrupted and the control rods movement typically gives reactivity variation with edge signals like saw teeth. Those edge regions should be precisely preserved since the measured signal is used to estimate the reactivity wroth which is a crucial parameter to assure the safety of the nuclear reactors. In this paper, three kind of edge preserving noise filters are proposed and their performance is demonstrated using stepwise signals. The tested filters are based on the unilateral, bilateral kernel and wavelet filters which are known to be effective in edge preservation. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters
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 are init...... 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...
A multiscale filter for noise reduction of low-dose cone beam projections.
Yao, Weiguang; Farr, Jonathan B
2015-08-21
The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024 × 768 pixels.
Adaptive mean filtering for noise reduction in CT polymer gel dosimetry
International Nuclear Information System (INIS)
Hilts, Michelle; Jirasek, Andrew
2008-01-01
X-ray computed tomography (CT) as a method of extracting 3D dose information from irradiated polymer gel dosimeters is showing potential as a practical means to implement gel dosimetry in a radiation therapy clinic. However, the response of CT contrast to dose is weak and noise reduction is critical in order to achieve adequate dose resolutions with this method. Phantom design and CT imaging technique have both been shown to decrease image noise. In addition, image postprocessing using noise reduction filtering techniques have been proposed. This work evaluates in detail the use of the adaptive mean filter for reducing noise in CT gel dosimetry. Filter performance is systematically tested using both synthetic patterns mimicking a range of clinical dose distribution features as well as actual clinical dose distributions. Both low and high signal-to-noise ratio (SNR) situations are examined. For all cases, the effects of filter kernel size and the number of iterations are investigated. Results indicate that adaptive mean filtering is a highly effective tool for noise reduction CT gel dosimetry. The optimum filtering strategy depends on characteristics of the dose distributions and image noise level. For low noise images (SNR ∼20), the filtered results are excellent and use of adaptive mean filtering is recommended as a standard processing tool. For high noise images (SNR ∼5) adaptive mean filtering can also produce excellent results, but filtering must be approached with more caution as spatial and dose distortions of the original dose distribution can occur
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.
IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform
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.
GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm
National Research Council Canada - National Science Library
Vanek, Barry
1999-01-01
.... The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter structure, which then adapts to changes in the real-world measurement noise strength...
On low-frequency errors of uniformly modulated filtered white-noise models for ground motions
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).
Design of low noise class D amplifiers using an integrated filter
International Nuclear Information System (INIS)
Wang Haishi; Zhang Bo
2012-01-01
This paper investigates the noise sources in a single-ended class D amplifier (SECDA) and suggests corresponding ways to lower the noise. The total output noise could be expressed as a function of the gain and noises from different sources. According to the function, the bias voltage (V B ) is a primary noise source, especially for a SECDA with a large gain. A low noise SECDA is obtained by integrating a filter into the SECDA to lower the noise of the V B . The filter utilizes an active resister and an 80 pF capacitance to get a 3 Hz pole. A noise test and fast Fourier transform analysis show that the noise performance of this SECDA is the same as that of a SECDA with an external filter. (semiconductor integrated circuits)
A multi-stage noise adaptive switching filter for extremely corrupted images
Dinh, Hai; Adhami, Reza; Wang, Yi
2015-07-01
A multi-stage noise adaptive switching filter (MSNASF) is proposed for the restoration of images extremely corrupted by impulse and impulse-like noise. The filter consists of two steps: noise detection and noise removal. The proposed extrema-based noise detection scheme utilizes the false contouring effect to get better over detection rate at low noise density. It is adaptive and will detect not only impulse but also impulse-like noise. In the noise removal step, a novel multi-stage filtering scheme is proposed. It replaces corrupted pixel with the nearest uncorrupted median to preserve details. When compared with other methods, MSNASF provides better peak signal to noise ratio (PSNR) and structure similarity index (SSIM). A subjective evaluation carried out online also demonstrates that MSNASF yields higher fidelity.
M2 FILTER FOR SPECKLE NOISE SUPPRESSION IN BREAST ULTRASOUND IMAGES
Directory of Open Access Journals (Sweden)
E.S. Samundeeswari
2016-11-01
Full Text Available Breast cancer, commonly found in women is a serious life threatening disease due to its invasive nature. Ultrasound (US imaging method plays an effective role in screening early detection and diagnosis of Breast cancer. Speckle noise generally affects medical ultrasound images and also causes a number of difficulties in identifying the Region of Interest. Suppressing speckle noise is a challenging task as it destroys fine edge details. No specific filter is designed yet to get a noise free BUS image that is contaminated by speckle noise. In this paper M2 filter, a novel hybrid of linear and nonlinear filter is proposed and compared to other spatial filters with 3×3 kernel size. The performance of the proposed M2 filter is measured by statistical quantity parameters like MSE, PSNR and SSI. The experimental analysis clearly shows that the proposed M2 filter outperforms better than other spatial filters by 2% high PSNR values with regards to speckle suppression.
Optimisation of digital noise filtering in the deconvolution of ultrafast kinetic data
International Nuclear Information System (INIS)
Banyasz, Akos; Dancs, Gabor; Keszei, Erno
2005-01-01
Ultrafast kinetic measurements in the sub-picosecond time range are always distorted by a convolution with the instrumental response function. To restore the undistorted signal, deconvolution of the measured data is needed, which can be done via inverse filtering, using Fourier transforms, if experimental noise can be successfully filtered. However, in the case of experimental data when no underlying physical model is available, no quantitative criteria are known to find an optimal noise filter which would remove excessive noise without distorting the signal itself. In this paper, we analyse the Fourier transforms used during deconvolution and describe a graphical method to find such optimal noise filters. Comparison of graphically found optima to those found by quantitative criteria in the case of known synthetic kinetic signals shows the reliability of the proposed method to get fairly good deconvolved kinetic curves. A few examples of deconvolution of real-life experimental curves with the graphical noise filter optimisation are also shown
Kalman filtering techniques for reducing variance of digital speckle displacement measurement noise
Institute of Scientific and Technical Information of China (English)
Donghui Li; Li Guo
2006-01-01
@@ Target dynamics are assumed to be known in measuring digital speckle displacement. Use is made of a simple measurement equation, where measurement noise represents the effect of disturbances introduced in measurement process. From these assumptions, Kalman filter can be designed to reduce variance of measurement noise. An optical and analysis system was set up, by which object motion with constant displacement and constant velocity is experimented with to verify validity of Kalman filtering techniques for reduction of measurement noise variance.
An Extension to a Filter Implementation of Local Quadratic Surface for Image Noise Estimation
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
1999-01-01
Based on regression analysis this paper gives a description for simple image filter design. Specifically 3x3 filter implementations of a quadratic surface, residuals from this surface, gradients and the Laplacian are given. For the residual a 5x5 filter is given also. It is shown that the 3x3......) it is concluded that if striping is to be considered as a part of the noise, the residual from a 3x3 median filter seems best. If we are interested in a salt-and-pepper noise estimator the proposed extension to the 3x3 filter for the residual from a quadratic surface seems best. Simple statistics...
A simple procedure to estimate reactivity with good noise filtering characteristics
International Nuclear Information System (INIS)
Shimazu, Yoichiro
2014-01-01
Highlights: • A new and simple on-line reactivity estimation method is proposed. • The estimator has robust noise filtering characteristics. • The noise filtering is equivalent to those of conventional reactivity meters. • The new estimator eliminates the burden of selecting optimum filter constants. • The new estimation performance is assessed without and with measurement noise. - Abstract: A new and simple on-line reactivity estimation method is proposed. The estimator has robust noise filtering characteristics without the use of complex filters. The noise filtering capability is equivalent to or better than that of a conventional estimator based on Inverse Point Kinetics (IPK). The new estimator can also eliminate the burden of selecting optimum filter time constants, such as would be required for the IPK-based estimator, or noise covariance matrices, which are needed if the extended Kalman filter (EKF) technique is used. In this paper, the new estimation method is introduced and its performance assessed without and with measurement noise
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...
INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING
Institute of Scientific and Technical Information of China (English)
Chen Ken; Napolitano; Zhang Yun; Li Dong
2010-01-01
The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.
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....
Lina, Ioan A; Lauer, Amanda M
2013-04-01
The notched noise method is an effective procedure for measuring frequency resolution and auditory filter shapes in both human and animal models of hearing. Briefly, auditory filter shape and bandwidth estimates are derived from masked thresholds for tones presented in noise containing widening spectral notches. As the spectral notch widens, increasingly less of the noise falls within the auditory filter and the tone becomes more detectible until the notch width exceeds the filter bandwidth. Behavioral procedures have been used for the derivation of notched noise auditory filter shapes in mice; however, the time and effort needed to train and test animals on these tasks renders a constraint on the widespread application of this testing method. As an alternative procedure, we combined relatively non-invasive auditory brainstem response (ABR) measurements and the notched noise method to estimate auditory filters in normal-hearing mice at center frequencies of 8, 11.2, and 16 kHz. A complete set of simultaneous masked thresholds for a particular tone frequency were obtained in about an hour. ABR-derived filter bandwidths broadened with increasing frequency, consistent with previous studies. The ABR notched noise procedure provides a fast alternative to estimating frequency selectivity in mice that is well-suited to high through-put or time-sensitive screening. Copyright © 2013 Elsevier B.V. All rights reserved.
Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise
International Nuclear Information System (INIS)
Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym
2008-01-01
This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method
Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering
Li, Guang; Xiao, Xiao; Tang, Jing-Tian; Li, Jin; Zhu, Hui-Jie; Zhou, Cong; Yan, Fa-Bao
2017-12-01
In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.
Frequency tracking and variable bandwidth for line noise filtering without a reference.
Kelly, John W; Collinger, Jennifer L; Degenhart, Alan D; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei
2011-01-01
This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.
Sridevi.Ravada,; Vani prasanna.Kanakala,; Ramya.Koilada
2011-01-01
A fuzzy filter is constructed from a set of fuzzy IF-THEN rules, these fuzzy rules come either from human experts or by matching input-output pairs .in this paper we propose a new fuzzy filter for the noise reduction of images corrupted with additive noise. here in this approach ,initially fuzzy derivatives for all eight directions that is N,E,W,S, NE,NW,SE,SW are calculated using “fuzzy IF-THEN rules “ and membership functions . Further the fuzzy derivative values obtained are used in the fu...
Discrete random signal processing and filtering primer with Matlab
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
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.
Random set particle filter for bearings-only multitarget tracking
Vihola, Matti
2005-05-01
The random set approach to multitarget tracking is a theoretically sound framework that covers joint estimation of the number of targets and the state of the targets. This paper describes a particle filter implementation of the random set multitarget filter. The contribution of this paper to the random set tracking framework is the formulation of a measurement model where each sensor report is assumed to contain at most one measurement. The implemented filter was tested in synthetic bearings-only tracking scenarios containing up to two targets in the presence of false alarms and missed measurements. The estimated target state consisted of 2D position and velocity components. The filter was capable to track the targets fairly well despite of the missing measurements and the relatively high false alarm rates. In addition, the filter showed robustness against wrong parameter values of false alarm rates. The results that were obtained during the limited tests of the filter show that the random set framework has potential for challenging tracking situations. On the other hand, the computational burden of the described implementation is quite high and increases approximately linearly with respect to the expected number of targets.
An Adaptive Filter for the Removal of Drifting Sinusoidal Noise Without a Reference.
Kelly, John W; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei
2016-01-01
This paper presents a method for filtering sinusoidal noise with a variable bandwidth filter that is capable of tracking a sinusoid's drifting frequency. The method, which is based on the adaptive noise canceling (ANC) technique, will be referred to here as the adaptive sinusoid canceler (ASC). The ASC eliminates sinusoidal contamination by tracking its frequency and achieving a narrower bandwidth than typical notch filters. The detected frequency is used to digitally generate an internal reference instead of relying on an external one as ANC filters typically do. The filter's bandwidth adjusts to achieve faster and more accurate convergence. In this paper, the focus of the discussion and the data is physiological signals, specifically electrocorticographic (ECoG) neural data contaminated with power line noise, but the presented technique could be applicable to other recordings as well. On simulated data, the ASC was able to reliably track the noise's frequency, properly adjust its bandwidth, and outperform comparative methods including standard notch filters and an adaptive line enhancer. These results were reinforced by visual results obtained from real ECoG data. The ASC showed that it could be an effective method for increasing signal to noise ratio in the presence of drifting sinusoidal noise, which is of significant interest for biomedical applications.
International Nuclear Information System (INIS)
Comani, S; Mantini, D; Alleva, G; Luzio, S Di; Romani, G L
2005-01-01
The greatest impediment to extracting high-quality fetal signals from fetal magnetocardiography (fMCG) is environmental magnetic noise, which may have peak-to-peak intensity comparable to fetal QRS amplitude. Being an unstructured Gaussian signal with large disturbances at specific frequencies, ambient field noise can be reduced with hardware-based approaches and/or with software algorithms that digitally filter magnetocardiographic recordings. At present, no systematic evaluation of filters' performances on shielded and unshielded fMCG is available. We designed high-pass and low-pass Chebychev II-type filters with zero-phase and stable impulse response; the most commonly used band-pass filters were implemented combining high-pass and low-pass filters. The achieved ambient noise reduction in shielded and unshielded recordings was quantified, and the corresponding signal-to-noise ratio (SNR) and signal-to-distortion ratio (SDR) of the retrieved fetal signals was evaluated. The study regarded 66 fMCG datasets at different gestational ages (22-37 weeks). Since the spectral structures of shielded and unshielded magnetic noise were very similar, we concluded that the same filter setting might be applied to both conditions. Band-pass filters (1.0-100 Hz) and (2.0-100 Hz) provided the best combinations of fetal signal detection rates, SNR and SDR; however, the former should be preferred in the case of arrhythmic fetuses, which might present spectral components below 2 Hz
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
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.
Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.
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.
The clustering of local maxima in random noise
International Nuclear Information System (INIS)
Coles, P.
1989-01-01
A mixture of analytic and numerical techniques is used to study the clustering properties of local maxima of random noise. Technical complexities restrict us to the case of 1D noise, but the results obtained should give a reasonably accurate picture of the behaviour of cosmological density peaks in noise defined on a 3D domain. We give estimates of the two-point correlation function of local maxima, for both Gaussian and non-Gaussian noise and show that previous approximations are not accurate. (author)
Reduced rank adaptive filtering in impulsive noise environments
Soury, Hamza; Abed-Meraim, Karim; Alouini, Mohamed-Slim
2014-01-01
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
Filtering, control and fault detection with randomly occurring incomplete information
Dong, Hongli; Gao, Huijun
2013-01-01
This book investigates the filtering, control and fault detection problems for several classes of nonlinear systems with randomly occurring incomplete information. It proposes new concepts, including RVNs, ROMDs, ROMTCDs, and ROQEs. The incomplete information under consideration primarily includes missing measurements, time-delays, sensor and actuator saturations, quantization effects and time-varying nonlinearities. The first part of this book focuses on the filtering, control and fault detection problems for several classes of nonlinear stochastic discrete-time systems and
Turbulence-cascade interaction noise using an advanced digital filter method
Gea Aguilera, Fernando; Gill, James; Zhang, Xin; Nodé-Langlois, Thomas
2016-01-01
Fan wakes interacting with outlet guide vanes is a major source of noise in modern turbofan engines. In order to study this source of noise, the current work presents two-dimensional simulations of turbulence-cascade interaction noise using a computational aeroacoustic methodology. An advanced digital filter method is used for the generation of isotropic synthetic turbulence in a linearised Euler equation solver. A parameter study is presented to assess the influence of airfoil thickness, mea...
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.
Optimal Linear Filters for Pulse Height Measurements in the Presence of Noise
International Nuclear Information System (INIS)
Nygaard, K.
1966-07-01
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
Effectual switching filter for removing impulse noise using a SCM detector
Yuan, Jin-xia; Zhang, Hong-juan; Ma, Yi-de
2012-03-01
An effectual method is proposed to remove impulse noise from corrupted color images. The spiking cortical model (SCM) is adopted as a noise detector to identify noisy pixels in each channel of color images, and detected noise pixels are saved in three marking matrices. According to the three marking matrices, the detected noisy pixels are divided into two types (type I and type II). They are filtered differently: an adaptive median filter is used for type I and an adaptive vector median for type II. Noise-free pixels are left unchanged. Extensive experiments show that the proposed method outperforms most of the other well-known filters in the aspects of both visual and objective quality measures, and this method can also reduce the possibility of generating color artifacts while preserving image details.
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.
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.
Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise
Directory of Open Access Journals (Sweden)
Bowen Hou
2017-11-01
Full Text Available As one of the most critical issues for target track, α -jerk model is an effective maneuver target track model. Non-Gaussian noises always exist in the track process, which usually lead to inconsistency and divergence of the track filter. A novel Kalman filter is derived and applied on α -jerk tracking model to handle non-Gaussian noise. The weighted least square solution is presented and the standard Kalman filter is deduced firstly. A novel Kalman filter with the weighted least square based on the maximum correntropy criterion is deduced. The robustness of the maximum correntropy criterion is also analyzed with the influence function and compared with the Huber-based filter, and, moreover, the kernel size of Gaussian kernel plays an important role in the filter algorithm. A new adaptive kernel method is proposed in this paper to adjust the parameter in real time. Finally, simulation results indicate the validity and the efficiency of the proposed filter. The comparison study shows that the proposed filter can significantly reduce the noise influence for α -jerk model.
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.
Effects of random noise in a dynamical model of love
International Nuclear Information System (INIS)
Xu Yong; Gu Rencai; Zhang Huiqing
2011-01-01
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.
The use of wavelet filters for reducing noise in posterior fossa Computed Tomography images
International Nuclear Information System (INIS)
Pita-Machado, Reinado; Perez-Diaz, Marlen; Lorenzo-Ginori, Juan V.; Bravo-Pino, Rolando
2014-01-01
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
Directory of Open Access Journals (Sweden)
R. Caballero-Águila
2014-01-01
Full Text Available The optimal least-squares linear estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems subject to randomly delayed measurements with different delay rates. For each sensor, a different binary sequence is used to model the delay process. The measured outputs are perturbed by both random parameter matrices and one-step autocorrelated and cross correlated noises. Using an innovation approach, computationally simple recursive algorithms are obtained for the prediction, filtering, and smoothing problems, without requiring full knowledge of the state-space model generating the signal process, but only the information provided by the delay probabilities and the mean and covariance functions of the processes (signal, random parameter matrices, and noises involved in the observation model. The accuracy of the estimators is measured by their error covariance matrices, which allow us to analyze the estimator performance in a numerical simulation example that illustrates the feasibility of the proposed algorithms.
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.
Transistor-based filter for inhibiting load noise from entering a power supply
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.
Kalman filter based fault diagnosis of networked control system with white noise
Institute of Scientific and Technical Information of China (English)
Yanwei WANG; Ying ZHENG
2005-01-01
The networked control system NCS is regarded as a sampled control system with output time-variant delay.White noise is considered in the model construction of NCS.By using the Kalman filter theory to compute the filter parameters,a Kalman filter is constructed for this NCS.By comparing the output of the filter and the practical system,a residual is generated to diagnose the sensor faults and the actuator faults.Finally,an example is given to show the feasibility of the approach.
SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation
Energy Technology Data Exchange (ETDEWEB)
Maitree, R; Guzman, G; Chundury, A; Roach, M; Yang, D [Washington University School of Medicine, St Louis, MO (United States)
2016-06-15
Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness of available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and
SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation
International Nuclear Information System (INIS)
Maitree, R; Guzman, G; Chundury, A; Roach, M; Yang, D
2016-01-01
Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness of available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and
Removal of jitter noise in 3D shape recovery from image focus by using Kalman filter.
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.
Impulse Noise Cancellation of Medical Images Using Wavelet Networks and Median Filters
Sadri, Amir Reza; Zekri, Maryam; Sadri, Saeid; Gheissari, Niloofar
2012-01-01
This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a preprocessing for the second stage. The second step is removing impulse noise with a median filter. The wavelet network presented here is a fixed one without learning. Experimental results show that our method acts on impulse noise effectively, and at the same time preserves chromaticity and image details very well. PMID:23493998
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
Influence of magnetizing and filtering frequencies on Barkhausen noise response
Czech Academy of Sciences Publication Activity Database
Stupakov, Oleksandr; Melikhov, Y.
2014-01-01
Roč. 50, č. 4 (2014), s. 6100104 ISSN 0018-9464 R&D Projects: GA ČR GA13-18993S Institutional support: RVO:68378271 Keywords : Barkhausen effect * filtering * frequency measurement * magnetic field measurement Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.386, year: 2014
The deterministic chaos and random noise in turbulent jet
International Nuclear Information System (INIS)
Yao, Tian-Liang; Liu, Hai-Feng; Xu, Jian-Liang; Li, Wei-Feng
2014-01-01
A turbulent flow is usually treated as a superposition of coherent structure and incoherent turbulence. In this paper, the largest Lyapunov exponent and the random noise in the near field of round jet and plane jet are estimated with our previously proposed method of chaotic time series analysis [T. L. Yao, et al., Chaos 22, 033102 (2012)]. The results show that the largest Lyapunov exponents of the round jet and plane jet are in direct proportion to the reciprocal of the integral time scale of turbulence, which is in accordance with the results of the dimensional analysis, and the proportionality coefficients are equal. In addition, the random noise of the round jet and plane jet has the same linear relation with the Kolmogorov velocity scale of turbulence. As a result, the random noise may well be from the incoherent disturbance in turbulence, and the coherent structure in turbulence may well follow the rule of chaotic motion
A generalized model via random walks for information filtering
International Nuclear Information System (INIS)
Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng
2016-01-01
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. - 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.
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.
Random matrix theory filters and currency portfolio optimisation
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.
Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms
Directory of Open Access Journals (Sweden)
Sihem SLATNIA
2011-01-01
Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks,extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.
Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms
Directory of Open Access Journals (Sweden)
Okba Kazar
2011-01-01
Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks, extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.
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.
Directory of Open Access Journals (Sweden)
Chong Shen
2016-05-01
Full Text Available 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.
Czech Academy of Sciences Publication Activity Database
Ökzan, E.; Šmídl, Václav; Saha, S.; Lundquist, C.; Gustafsson, F.
2013-01-01
Roč. 49, č. 6 (2013), s. 1566-1575 ISSN 0005-1098 R&D Projects: GA ČR(CZ) GAP102/11/0437 Keywords : Unknown Noise Statistics * Adaptive Filtering * Marginalized Particle Filter * Bayesian Conjugate prior Subject RIV: BC - Control Systems Theory Impact factor: 3.132, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/smidl-0393047.pdf
Institute of Scientific and Technical Information of China (English)
Li Shu; Zhuo Jiashou; Ren Qingwen
2000-01-01
In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.
Salt-and-pepper noise removal using modified mean filter and total variation minimization
Aghajarian, Mickael; McInroy, John E.; Wright, Cameron H. G.
2018-01-01
The search for effective noise removal algorithms is still a real challenge in the field of image processing. An efficient image denoising method is proposed for images that are corrupted by salt-and-pepper noise. Salt-and-pepper noise takes either the minimum or maximum intensity, so the proposed method restores the image by processing the pixels whose values are either 0 or 255 (assuming an 8-bit/pixel image). For low levels of noise corruption (less than or equal to 50% noise density), the method employs the modified mean filter (MMF), while for heavy noise corruption, noisy pixels values are replaced by the weighted average of the MMF and the total variation of corrupted pixels, which is minimized using convex optimization. Two fuzzy systems are used to determine the weights for taking average. To evaluate the performance of the algorithm, several test images with different noise levels are restored, and the results are quantitatively measured by peak signal-to-noise ratio and mean absolute error. The results show that the proposed scheme gives considerable noise suppression up to a noise density of 90%, while almost completely maintaining edges and fine details of the original image.
Random noise characterization on the carrying capacities of a ...
African Journals Online (AJOL)
The process of the survival of species dependent on a limited resource in a polluted environment which isnot a new idea can be described by the technique of a mathematical modelling. We have utilised the technique of a numerical simulation to study the impact of environmental random noise on the carrying capacities of ...
Adaptive nonlocal means filtering based on local noise level for CT denoising
International Nuclear Information System (INIS)
Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.; Blezek, Daniel J.; Manduca, Armando; Yu, Lifeng; Fletcher, Joel G.; McCollough, Cynthia H.
2014-01-01
Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the
Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.
2017-07-01
This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.
A generalized model via random walks for information filtering
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.
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.
Microphone directionality, pre-emphasis filter, and wind noise in cochlear implants.
Chung, King; McKibben, Nicholas
2011-10-01
Wind noise can be a nuisance or a debilitating masker for cochlear implant users in outdoor environments. Previous studies indicated that wind noise at the microphone/hearing aid output had high levels of low-frequency energy and the amount of noise generated is related to the microphone directionality. Currently, cochlear implants only offer either directional microphones or omnidirectional microphones for users at-large. As all cochlear implants utilize pre-emphasis filters to reduce low-frequency energy before the signal is encoded, effective wind noise reduction algorithms for hearing aids might not be applicable for cochlear implants. The purposes of this study were to investigate the effect of microphone directionality on speech recognition and perceived sound quality of cochlear implant users in wind noise and to derive effective wind noise reduction strategies for cochlear implants. A repeated-measure design was used to examine the effects of spectral and temporal masking created by wind noise recorded through directional and omnidirectional microphones and the effects of pre-emphasis filters on cochlear implant performance. A digital hearing aid was programmed to have linear amplification and relatively flat in-situ frequency responses for the directional and omnidirectional modes. The hearing aid output was then recorded from 0 to 360° at flow velocities of 4.5 and 13.5 m/sec in a quiet wind tunnel. Sixteen postlingually deafened adult cochlear implant listeners who reported to be able to communicate on the phone with friends and family without text messages participated in the study. Cochlear implant users listened to speech in wind noise recorded at locations that the directional and omnidirectional microphones yielded the lowest noise levels. Cochlear implant listeners repeated the sentences and rated the sound quality of the testing materials. Spectral and temporal characteristics of flow noise, as well as speech and/or noise characteristics before
Directory of Open Access Journals (Sweden)
Byeong Hak Kim
2017-12-01
Full Text Available 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.
Kim, Byeong Hak; Kim, Min Young; Chae, You Seong
2017-01-01
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. PMID:29280970
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.
Stability investigations of the ASDEX feedback system with filters for reducing thyristor noise
International Nuclear Information System (INIS)
Crisanti, F.; Schneider, F.
1983-06-01
A computer program for analysing the absolute and relative stabilities of any complex system by the root-locus method was developed. It is used to reanalyse the present horizontal position feed-back control in the ASDEX tokamak and to select the optimum parameters for this system with RCL filters for reducing thyristor noise. (orig.)
A modified LLCL-filter with the reduced conducted EMI noise
DEFF Research Database (Denmark)
Wu, Weimin; Sun, Yunjie; Lin, Zhe
2014-01-01
For a transformerless grid-tied converter using pulse width modulation, the harmonics of grid-injected current, the leakage current, and the electromagnetic interference (EMI) noise are three important issues during designing of the output filter. In this paper, the common mode and the differential...
A modified LLCL-filter with the reduced conducted EMI noise
DEFF Research Database (Denmark)
Wu, Weimin; Sun, Yunjie; Lin, Zhe
2013-01-01
For a transformerless grid-tied converter using Pulse Width Modulation (PWM), the harmonics of grid-injected current, the leakage current and the Electromagnetic Interference (EMI) noise are three important issues during design of the output filter. In this paper, the Common-Mode (CM...
Modeling Random Telegraph Noise Under Switched Bias Conditions Using Cyclostationary RTS Noise
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
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.
GPR random noise reduction using BPD and EMD
Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz
2018-04-01
Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.
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.
Generalized diffraction-stack migration and filtering of coherent noise
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.
Random walk in dynamically disordered chains: Poisson white noise disorder
International Nuclear Information System (INIS)
Hernandez-Garcia, E.; Pesquera, L.; Rodriguez, M.A.; San Miguel, M.
1989-01-01
Exact solutions are given for a variety of models of random walks in a chain with time-dependent disorder. Dynamic disorder is modeled by white Poisson noise. Models with site-independent (global) and site-dependent (local) disorder are considered. Results are described in terms of an affective random walk in a nondisordered medium. In the cases of global disorder the effective random walk contains multistep transitions, so that the continuous limit is not a diffusion process. In the cases of local disorder the effective process is equivalent to usual random walk in the absence of disorder but with slower diffusion. Difficulties associated with the continuous-limit representation of random walk in a disordered chain are discussed. In particular, the authors consider explicit cases in which taking the continuous limit and averaging over disorder sources do not commute
Mehdizadeh, Sina; Sanjari, Mohammad Ali
2017-11-07
This study aimed to determine the effect of added noise, filtering and time series length on the largest Lyapunov exponent (LyE) value calculated for time series obtained from a passive dynamic walker. The simplest passive dynamic walker model comprising of two massless legs connected by a frictionless hinge joint at the hip was adopted to generate walking time series. The generated time series was used to construct a state space with the embedding dimension of 3 and time delay of 100 samples. The LyE was calculated as the exponential rate of divergence of neighboring trajectories of the state space using Rosenstein's algorithm. To determine the effect of noise on LyE values, seven levels of Gaussian white noise (SNR=55-25dB with 5dB steps) were added to the time series. In addition, the filtering was performed using a range of cutoff frequencies from 3Hz to 19Hz with 2Hz steps. The LyE was calculated for both noise-free and noisy time series with different lengths of 6, 50, 100 and 150 strides. Results demonstrated a high percent error in the presence of noise for LyE. Therefore, these observations suggest that Rosenstein's algorithm might not perform well in the presence of added experimental noise. Furthermore, findings indicated that at least 50 walking strides are required to calculate LyE to account for the effect of noise. Finally, observations support that a conservative filtering of the time series with a high cutoff frequency might be more appropriate prior to calculating LyE. Copyright © 2017 Elsevier Ltd. All rights reserved.
Noise Reduction in Breath Sound Files Using Wavelet Transform Based Filter
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.
Energy Technology Data Exchange (ETDEWEB)
Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Department of Radiology, Stanford University, Stanford, California 94305 (United States) and Center for Medical Image Science and Visualization, Linkoeping University, Linkoeping (Sweden); Pattern Recognition Laboratory, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, 91054, Erlangen (Germany); Nuclear and Radiological Engineering and Medical Physics Programs, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Siemens AG Healthcare, Forchheim 91301 (Germany); Department of Radiology, Stanford University, Stanford, California 94305 (United States)
2011-11-15
Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8
International Nuclear Information System (INIS)
Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca
2011-01-01
Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold
Noise filtering algorithm for the MFTF-B computer based control system
International Nuclear Information System (INIS)
Minor, E.G.
1983-01-01
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions
Two-antenna GNSS Aided-INS Alignment Using Adaptive Control of Filter Noise Covariance
Directory of Open Access Journals (Sweden)
HAO Yushi
2018-04-01
Full Text Available This paper developed a theory of INS fine alignment in order to restrain the divergence of yaw angle,two antennas GNSS aided-INS integrated alignment algorithm was utilized.An attitude error measurement equation was conducted based on the relationship between baseline vectors calculated by two sensors and attitude error.The algorithm was executed by EKF using adaptive control of filter noise covariance.The experimental results showed that stability of the integrated system was improved under the system noise covariance adaptive control mechanism;The measurement noise covariance adaptive control mechanism can reduce the influence of measurement noise and improve the alignment absolute accuracy;Further improvement was achieved under the condition of minim bias of baseline length.The accuracy of roll and pitch was 0.02°,the accuracy of yaw was 0.04°.
Band-gap tunable dielectric elastomer filter for low frequency noise
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.
Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter
Sindelar, Charles V.; Grigorieff, Nikolaus
2012-01-01
The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the “single-particle Wiener filter”) to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation. PMID:22613568
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.
Random noise suppression of seismic data using non-local Bayes algorithm
Chang, De-Kuan; Yang, Wu-Yang; Wang, Yi-Hui; Yang, Qing; Wei, Xin-Jian; Feng, Xiao-Ying
2018-02-01
For random noise suppression of seismic data, we present a non-local Bayes (NL-Bayes) filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.
Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters
Munsky, Brian; Trinh, Brooke; Khammash, Mustafa
2010-03-01
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. 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. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.
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.
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
consider two cases, where, respectively, no distortion and distortion are incurred on the desired signal. The former can be achieved when the covariance matrix of the desired signal is rank deficient, which is the case, for example, for voiced speech. In the latter case, the covariance matrix......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...
Oh, Paul; Lee, Sukho; Kang, Moon Gi
2017-06-28
Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.
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.
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.
Optimal Linear Filters. 2. Pulse Time Measurements in the Presence of Noise
International Nuclear Information System (INIS)
Nygaard, K.
1966-09-01
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
Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems
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. Perf...
Effects of noise, nonlinear processing, and linear filtering on perceived music quality.
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.
Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise.
Cui, Bingbo; Chen, Xiyuan; Tang, Xihua; Huang, Haoqian; Liu, Xiao
2018-01-01
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.
Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise
Quaranta, Giuseppe; Trentadue, Francesco; Maruccio, Claudio; Marano, Giuseppe C.
2018-05-01
This paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers.
Seismic random noise attenuation using shearlet and total generalized variation
International Nuclear Information System (INIS)
Kong, Dehui; Peng, Zhenming
2015-01-01
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. (paper)
Seismic random noise attenuation using shearlet and total generalized variation
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.
Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction.
Lam, Frank; Lu, Hsiang-Wei; Wu, Chung-Che; Aliyazicioglu, Zekeriya; Kang, James S
2017-01-01
Clinical applications that require extraction and interpretation of physiological signals or waveforms are susceptible to corruption by noise or artifacts. Real-time hemodynamic monitoring systems are important for clinicians to assess the hemodynamic stability of surgical or intensive care patients by interpreting hemodynamic parameters generated by an analysis of aortic blood pressure (ABP) waveform measurements. Since hemodynamic parameter estimation algorithms often detect events and features from measured ABP waveforms to generate hemodynamic parameters, noise and artifacts integrated into ABP waveforms can severely distort the interpretation of hemodynamic parameters by hemodynamic algorithms. In this article, we propose the use of the Kalman filter and the 4-element Windkessel model with static parameters, arterial compliance C , peripheral resistance R , aortic impedance r , and the inertia of blood L , to represent aortic circulation for generating accurate estimations of ABP waveforms through noise and artifact reduction. Results show the Kalman filter could very effectively eliminate noise and generate a good estimation from the noisy ABP waveform based on the past state history. The power spectrum of the measured ABP waveform and the synthesized ABP waveform shows two similar harmonic frequencies.
Extended Kalman filtering for joint mitigation of phase and amplitude noise in coherent QAM systems.
Pakala, Lalitha; Schmauss, Bernhard
2016-03-21
We numerically investigate our proposed carrier phase and amplitude noise estimation (CPANE) algorithm using extend Kalman filter (EKF) for joint mitigation of linear and non-linear phase noise as well as amplitude noise on 4, 16 and 64 polarization multiplexed (PM) quadrature amplitude modulation (QAM) 224 Gb/s systems. The results are compared to decision directed (DD) carrier phase estimation (CPE), DD phase locked loop (PLL) and universal CPE (U-CPE) algorithms. Besides eliminating the necessity of phase unwrapping function, EKF-CPANE shows improved performance for both back-to-back (BTB) and transmission scenarios compared to the aforementioned algorithms. We further propose a weighted innovation approach (WIA) of the EKF-CPANE which gives an improvement of 0.3 dB in the Q-factor, compared to the original 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.
Directory of Open Access Journals (Sweden)
Li N.
2017-01-01
Full Text Available Affected by the unstable pulse radiation and the pulsar directional errors, the statistical characteristics of the pulsar measurement noise may vary with time slowly and cannot be accurately determined, which cause the filtering accuracy of the extended Kalman filter(EKF in pulsar navigation positioning system decline sharply or even diverge. To solve this problem, an adaptive extended Kalman filtering algorithm based on the empirical mode decomposition(EMD is proposed. In this method, the high frequency noise is separated from measurement information of pulsar by the method of EMD, and the noise variance can be estimated to update the parameters of EKF. The simulation results demonstrate that compared with conventional EKF, the proposed method can adaptively track the change of the measurement noise, and still keeps high estimation accuracy with unknown measurement noise, the positioning accuracy of the pulsar navigation is improved simultaneously.
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 cascad...... 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....
Information filtering via biased random walk on coupled social network.
Nie, Da-Cheng; Zhang, Zi-Ke; Dong, Qiang; Sun, Chongjing; Fu, Yan
2014-01-01
The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.
A realization of the RAM digital filter. [Random Access Memory
Zohar, S.
1976-01-01
The digital filtering algorithm of W. D. Little, which employs a large RAM to obtain high speed, is implemented in a simple hardware configuration. The nonrecursive version of this filter is compared to the counting digital filter and found to be competitive for low-order filters up to order 7 (8 coefficients).
International Nuclear Information System (INIS)
Perez Diaz, M.; Ruiz Gonzalez, Y.; Lorenzo Ginori, J. V.
2015-01-01
This paper describes a comparison among some wavelet filters and other most traditional filters in the frequency domain like Median, Wiener and Butter worth to reduce Poisson noise in Computed Tomography (CT) scans. Five slices of CT containing the posterior fossa from an anthropomorphic phantom and from patients were selected. As their original projections contain noise from the acquisition process, some simulated noise-free lesions were added on the images. After that, the whole images were artificially contaminated with Poisson noise over the sinogram-space. The configurations using wavelets drawn from four wavelet families, using various decomposition levels, and different thresholds, were tested in order to determine de-noising performance as well as the rest of the traditional filters. The quality of the resulting images was evaluated by using Contrast to Noise Ratio (CNR), HVS absolute norm (H1), and Structural Similarity Index (SSIM) as quantitative metrics. We have observed that Wavelet filtering is an alternative to be considered for Poisson noise reduction in image processing of posterior fossa images for head CT with similar behavior to Butter worth and better than Median or Wiener filters for the developed experiment. (Author)
International Nuclear Information System (INIS)
Axelsson, Jan; Sörensen, Jens
2013-01-01
In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence. We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamic time-series. The Scree-plot technique was used to determine which principal components to be rejected in the filter process. This filter was applied to [ 11 C]-acetate on heart and head-neck tumors, [ 18 F]-FDG on liver tumors and brain, and [ 11 C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to real PET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varying parts of a 90-frame [ 18 F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20 MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) were compared. The 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manually pick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focal Raclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissue uptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data is reliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior to Patlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dose reduction can be achieved for Patlak slope images without changing image quality or quantitation. The 2D Hotelling-filtering of dynamic PET data is a computer
International Nuclear Information System (INIS)
Dhurandhar, S.V.; Sathyaprakash, B.S.
1992-10-01
We discuss the problem of detecting gravitational wave signals embedded in coloured noise from coalescing binary systems. The signal is assumed to be Newtonian and matched filtering techniques are employed to filter out the signal. The problem is discussed at first for a general power spectral density of the noise and then specific numerical results are obtained for the standard recycling case. Since the signal parameters are unknown, a bank of filters is needed to carry out the signal detection. The number of filters in a bank, the spacing between filters etc. is obtained for different values of the minimum strength of the signal relative to the threshold. We also present an approximate analytical formula which relates the spacing between filters to the minimum strength. Finally, we discuss the problem of detection probabilities given a data train. (author). 21 refs, 2 figs, 3 tabs
Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.
2016-02-01
Spatial filtering is an important technique for reducing sky background noise in a satellite quantum key distribution downlink receiver. Atmospheric turbulence limits the extent to which spatial filtering can reduce sky noise without introducing signal losses. Using atmospheric propagation and compensation simulations, the potential benefit of adaptive optics (AO) to secure key generation (SKG) is quantified. Simulations are performed assuming optical propagation from a low-Earth-orbit satellite to a terrestrial receiver that includes AO. Higher-order AO correction is modeled assuming a Shack-Hartmann wavefront sensor and a continuous-face-sheet deformable mirror. The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain wave-optics hardware emulator. SKG rates are calculated for a decoy-state protocol as a function of the receiver field of view for various strengths of turbulence, sky radiances, and pointing angles. The results show that at fields of view smaller than those discussed by others, AO technologies can enhance SKG rates in daylight and enable SKG where it would otherwise be prohibited as a consequence of background optical noise and signal loss due to propagation and turbulence effects.
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...
Active control of time-varying broadband noise and vibrations using a sliding-window Kalman filter
van Ophem, S.; Berkhoff, Arthur P.; Sas, P.; Moens, D.; Denayer, H.
2014-01-01
Recently, a multiple-input/multiple-output Kalman filter technique was presented to control time-varying broadband noise and vibrations. By describing the feed-forward broadband active noise control problem in terms of a state estimation problem it was possible to achieve a faster rate of
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.
International Nuclear Information System (INIS)
Takeyama, Nobuyuki; Hayashi, Takaki; Ohgiya, Yoshimitsu
2011-01-01
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 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 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
Li, Linqian; Feng, Yiqiao; Zhang, Wenbo; Cui, Nan; Xu, Hengying; Tang, Xianfeng; Xi, Lixia; Zhang, Xiaoguang
2017-07-01
A joint carrier recovery scheme for polarization division multiplexing (PDM) coherent optical transmission system is proposed and demonstrated, in which the extended Kalman filter (EKF) is exploited to estimate and equalize the carrier frequency offset (CFO) and carrier phase noise (CPN) simultaneously. The proposed method is implemented and verified in the PDM-QPSK system and the PDM-16QAM system with the comparisons to conventional improved Mth-power (IMP) algorithm for CFO estimation, blind phase search (BPS) algorithm or Viterbi-Viterbi (V-V) algorithm for CPN recovery. It is demonstrated that the proposed scheme shows high CFO estimation accuracy, with absolute mean estimation error below 1.5 MHz. Meanwhile, the proposed method has the CFO tolerance of [±3 GHz] for PDM-QPSK system and [±0.9 GHz] for PDM-16QAM system. Compare with IMP/BPS and IMP/V-V, the proposed scheme can enhance the linewidth symbol duration product from 3 × 10-4 (IMP/BPS) and 2 × 10-4 (IMP/V-V) to 1 × 10-3 for PDM-QPSK, and from 1 × 10-4 (IMP/BPS) to 3 × 10-4 for PDM-16QAM, respectively, at the 1 dB optical signal-to-noise ratio (OSNR) penalty. The proposed Kalman filter also shows a fast convergence with only 100 symbols and much lower computational complexity.
Bird's nest versus the Kimray-Greenfield inferior vena cava filter: Randomized clinical study
International Nuclear Information System (INIS)
Athanasoulis, C.A.; Roberts, A.C.; Brown, K.; Geller, S.C.; Waltman, A.C.; Eckstein, M.R.
1987-01-01
A randomized clinical study was conducted comparing the percutaneously introduced bird's nest inferior vena cava (IVC) filter and the Kimray-Greenfield IVC filter. Study end points included recurrent pulmonary embolism, new or worse leg venous stasis symptoms, IVC thrombosis, and ease of filter introduction. Of the 109 patients in the study, 58 were randomly assigned to the BN and 51 to the KG filter. Demographic factors were comparable between the two groups. Follow-up entailed cavography, noninvasive assessment of the femoral veins, and standardized telephone interviews. The follow-up period was extended to 1 year after filter insertion. Results for the bird's nest versus the Kimray-Greenfield filter respectively were as follows: death due to massive pulmonary embolism, 3% versus 5%; recurrent pulmonary embolism, 1.5% versus 7.5%; filter migration, 1.1% versus 0.0%; IVC thrombosis, 6% versus 2.5%; new or worse leg edema, 28.5% versus 22%; ease of introduction (qualitative), maximal versus minimal; patient discomfort (qualitative), minimal versus maximal. The authors conclude the bird's nest filter is better than the Kimray-Greenfield filter in terms of prevention of recurrent pulmonary embolism and ease of introduction. In terms of venous stasis, the bird's nest filter is not better and may be worse than the Kimray-Greenfield filter. Filter migration is a problem with the bird's nest filter
Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors
International Nuclear Information System (INIS)
Jain, Ankit; Alam, Muhammad Ashraful
2014-01-01
A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (SNR) and the limit-of-detection (LOD) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate SNR and establish LOD of critical-point flexure sensors. We find that a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved SNR and LOD. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.
International Nuclear Information System (INIS)
Takahashi, Noriyuki; Ishii, Kiyoshi; Lee, Y.; Tsai, D.Y.
2007-01-01
The aim of this study was to evaluate the performance of a novel noise reduction filter for improving the visibility of early computed tomography (CT) signs of hyperacute stroke on nonenhanced CT images. Fourteen patients with a middle cerebral artery occlusion within 4.5 h after onset were evaluated. The signal-to-noise ratio (SNR) of the processed images with the noise reduction filter and that of original images were measured. Two neuroradiologists visually rated all the processed and original images on the visibility of normal and abnormal gray-white matter interfaces. The SNR value of the processed images was approximately eight times as high as that of the original images, and a 87% reduction of noise was achieved using this technique. For the visual assessment, the results showed that the visibility of normal gray-white matter interface and that of the loss of the gray-white matter interface were significantly improved using the proposed method (P<0.05). The noise reduction filter proposed in the present study has the potential to improve the visibility of early CT signs of hyperacute stroke on nonenhanced CT images. (author)
Morzfeld, M.; Atkins, E.; Chorin, A. J.
2011-12-01
covariance matrix Σ is assumed to be non-singular. In the present work we consider the case where the covariance Σ is singular. This happens in particular when the noise is spatially smooth and can be represented by a small number of Fourier coefficients, as is often the case in geophysical applications. We derive an implicit filter for this problem and show that it is very efficient, because the filter operates in a space whose dimension is the rank of Σ, rather than the full model dimension. We compare the implicit filter to SIR, to the Ensemble Kalman Filter and to variational methods, and also study how information from data is propagated from observed to unobserved variables. We illustrate the theory on two coupled nonlinear PDE's in one space dimension that have been used as a test-bed for geomagnetic data assimilation. We observe that the implicit filter gives good results with few (2-10) particles, while SIR requires thousands of particles for similar accuracy. We also find lower limits to the accuracy of the filter's reconstruction as a function of data availability.
Ichino, Shinya; Mawaki, Takezo; Teramoto, Akinobu; Kuroda, Rihito; Park, Hyeonwoo; Wakashima, Shunichi; Goto, Tetsuya; Suwa, Tomoyuki; Sugawa, Shigetoshi
2018-04-01
Random telegraph noise (RTN), which occurs in in-pixel source follower (SF) transistors, has become one of the most critical problems in high-sensitivity CMOS image sensors (CIS) because it is a limiting factor of dark random noise. In this paper, the behaviors of RTN toward changes in SF drain current conditions were analyzed using a low-noise array test circuit measurement system with a floor noise of 35 µV rms. In addition to statistical analysis by measuring a large number of transistors (18048 transistors), we also analyzed the behaviors of RTN parameters such as amplitude and time constants in the individual transistors. It is demonstrated that the appearance probability of RTN becomes small under a small drain current condition, although large-amplitude RTN tends to appear in a very small number of cells.
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager; Lazarov, Boyan Stefanov
2003-01-01
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...... frame with partial or full feed back from the movement of the top mass to the second and the first mass (top soil layer mass and base rock mass, respectively). Keywords: Clough-Penzien filtered white noise excitation, elasto-plastic shear frame oscillator, plastic displacement distributions, simplified...
The importance for speech intelligibility of random fluctuations in "steady" background noise.
Stone, Michael A; Füllgrabe, Christian; Mackinnon, Robert C; Moore, Brian C J
2011-11-01
Spectrally shaped steady noise is commonly used as a masker of speech. The effects of inherent random fluctuations in amplitude of such a noise are typically ignored. Here, the importance of these random fluctuations was assessed by comparing two cases. For one, speech was mixed with steady speech-shaped noise and N-channel tone vocoded, a process referred to as signal-domain mixing (SDM); this preserved the random fluctuations of the noise. For the second, the envelope of speech alone was extracted for each vocoder channel and a constant was added corresponding to the root-mean-square value of the noise envelope for that channel. This is referred to as envelope-domain mixing (EDM); it removed the random fluctuations of the noise. Sinusoidally modulated noise and a single talker were also used as backgrounds, with both SDM and EDM. Speech intelligibility was measured for N = 12, 19, and 30, with the target-to-background ratio fixed at -7 dB. For SDM, performance was best for the speech background and worst for the steady noise. For EDM, this pattern was reversed. Intelligibility with steady noise was consistently very poor for SDM, but near-ceiling for EDM, demonstrating that the random fluctuations in steady noise have a large effect.
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-07-12
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.
Sokolov, R. I.; Abdullin, R. R.
2017-11-01
The use of nonlinear Markov process filtering makes it possible to restore both video stream frames and static photos at the stage of preprocessing. The present paper reflects the results of research in comparison of these types image filtering quality by means of special algorithm when Gaussian or non-Gaussian noises acting. Examples of filter operation at different values of signal-to-noise ratio are presented. A comparative analysis has been performed, and the best filtered kind of noise has been defined. It has been shown the quality of developed algorithm is much better than quality of adaptive one for RGB signal filtering at the same a priori information about the signal. Also, an advantage over median filter takes a place when both fluctuation and pulse noise filtering.
Directory of Open Access Journals (Sweden)
Wilson S
2015-01-01
Full Text Available Scott Wilson,1,2 Andrea Bowyer,3 Stephen B Harrap4 1Department of Renal Medicine, The Alfred Hospital, 2Baker IDI, Melbourne, 3Department of Anaesthesia, Royal Melbourne Hospital, 4University of Melbourne, Parkville, VIC, Australia Abstract: The clinical characterization of cardiovascular dynamics during hemodialysis (HD has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information. Keywords: continuous monitoring, blood pressure
Wilson, Scott; Bowyer, Andrea; Harrap, Stephen B
2015-01-01
The clinical characterization of cardiovascular dynamics during hemodialysis (HD) has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP) changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP) readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF) algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information.
Simpplified extended Kalman filter phase noise estimation for CO-OFDM transmissions.
Nguyen, Tu T; Le, Son T; Wuilpart, Marc; Yakusheva, Tatiana; Mégret, Patrice
2017-10-30
We propose a flexible simplified extended Kalman filter (S-EKF) scheme that can be applied in both pilot-aided and blind modes for phase noise compensation in 16-QAM CO-OFDM transmission systems employing a small-to-moderate number of subcarriers. The performance of the proposed algorithm is evaluated and compared with conventional pilot-aided (PA) and blind phase search (BPS) methods via extensive an Monte Carlo simulation in a back-to-back configuration and with a dual polarization fiber transmission. For 64 subcarrier 32 Gbaud 16-QAM CO-OFDM systems with 200 kHz combined laser linewidths, an optical signal-to-noise ratio penalty as low as 1 dB can be achieved with the proposed S-EKF scheme using only 2 pilots in the pilot-aided mode and just 4 inputs in the blind mode, resulting in a spectrally efficient enhancement by a factor of 3 and a computational effort reduction by a factor of more than 50 in comparison with the conventional PA and the BPS methods, respectively.
Ophem, S. van; Berkhoff, A.P.
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
Super fast physical-random number generation using laser diode frequency noises
Ushiki, Tetsuro; Doi, Kohei; Maehara, Shinya; Sato, Takashi; Ohkawa, Masashi; Ohdaira, Yasuo
2011-02-01
Random numbers can be classified as either pseudo- or physical-random in character. Pseudo-random numbers' periodicity renders them inappropriate for use in cryptographic applications, but naturally-generated physical-random numbers have no calculable periodicity, thereby making them ideally-suited to the task. The laser diode naturally produces a wideband "noise" signal that is believed to have tremendous capacity and great promise, for the rapid generation of physical-random numbers for use in cryptographic applications. We measured a laser diode's output, at a fast photo detector and generated physical-random numbers from frequency noises. We then identified and evaluated the binary-number-line's statistical properties. The result shows that physical-random number generation, at speeds as high as 40Gbps, is obtainable, using the laser diode's frequency noise characteristic.
Institute of Scientific and Technical Information of China (English)
QI Wen-Juan; ZHANG Peng; DENG Zi-Li
2014-01-01
This paper deals with the problem of designing robust sequential covariance intersection (SCI) fusion Kalman filter for the clustering multi-agent sensor network system with measurement delays and uncertain noise variances. The sensor network is partitioned into clusters by the nearest neighbor rule. Using the minimax robust estimation principle, based on the worst-case conservative sensor network system with conservative upper bounds of noise variances, and applying the unbiased linear minimum variance (ULMV) optimal estimation rule, we present the two-layer SCI fusion robust steady-state Kalman filter which can reduce communication and computation burdens and save energy sources, and guarantee that the actual filtering error variances have a less-conservative upper-bound. A Lyapunov equation method for robustness analysis is proposed, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented and the robust accuracy relations of the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the global SCI fuser is higher than those of the local SCI fusers and the robust accuracies of all SCI fusers are higher than that of each local robust Kalman filter. A simulation example for a tracking system verifies the robustness and robust accuracy relations.
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.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Abrecht, David G., E-mail: david.abrecht@pnnl.gov [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); Schwantes, Jon M. [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); Kukkadapu, Ravi K. [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); McDonald, Benjamin S.; Eiden, Gregory C.; Sweet, Lucas E. [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States)
2015-02-11
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.
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.
Analogies between colored Lévy noise and random channel approach to disordered kinetics
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.
Ofek, Eran O.; Zackay, Barak
2018-04-01
Detection of templates (e.g., sources) embedded in low-number count Poisson noise is a common problem in astrophysics. Examples include source detection in X-ray images, γ-rays, UV, neutrinos, and search for clusters of galaxies and stellar streams. However, the solutions in the X-ray-related literature are sub-optimal in some cases by considerable factors. Using the lemma of Neyman–Pearson, we derive the optimal statistics for template detection in the presence of Poisson noise. We demonstrate that, for known template shape (e.g., point sources), this method provides higher completeness, for a fixed false-alarm probability value, compared with filtering the image with the point-spread function (PSF). In turn, we find that filtering by the PSF is better than filtering the image using the Mexican-hat wavelet (used by wavdetect). For some background levels, our method improves the sensitivity of source detection by more than a factor of two over the popular Mexican-hat wavelet filtering. This filtering technique can also be used for fast PSF photometry and flare detection; it is efficient and straightforward to implement. We provide an implementation in MATLAB. The development of a complete code that works on real data, including the complexities of background subtraction and PSF variations, is deferred for future publication.
International Nuclear Information System (INIS)
Dabrowski, W.; Korbel, K.
1983-01-01
The importance of the excess noise in the semiconductor detectors operating at the elevated temperature is discussed. Under the assumption of a conventional CR-RC type filtration the variancy of the noise output is determined. The new term ''second noise-corner time constant'' was proposed. The expression for relative signal-to-noise ratio as the dependence on the noise as well as circuits time constants was derived. It was also presented in a graphical form. 12 refs., 6 figs. (author)
Realistic noise-tolerant randomness amplification using finite number of devices
Brandão, Fernando G. S. L.; Ramanathan, Ravishankar; Grudka, Andrzej; Horodecki, Karol; Horodecki, Michał; Horodecki, Paweł; Szarek, Tomasz; Wojewódka, Hanna
2016-04-01
Randomness is a fundamental concept, with implications from security of modern data systems, to fundamental laws of nature and even the philosophy of science. Randomness is called certified if it describes events that cannot be pre-determined by an external adversary. It is known that weak certified randomness can be amplified to nearly ideal randomness using quantum-mechanical systems. However, so far, it was unclear whether randomness amplification is a realistic task, as the existing proposals either do not tolerate noise or require an unbounded number of different devices. Here we provide an error-tolerant protocol using a finite number of devices for amplifying arbitrary weak randomness into nearly perfect random bits, which are secure against a no-signalling adversary. The correctness of the protocol is assessed by violating a Bell inequality, with the degree of violation determining the noise tolerance threshold. An experimental realization of the protocol is within reach of current technology.
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.
Directory of Open Access Journals (Sweden)
Young-Duk Kim
2018-03-01
Full Text Available Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC and automatic emergency braking (AEB for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.
Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho
2018-01-01
Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services. PMID:29534483
Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho; Kim, Hee-Kang
2018-03-11
Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.
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
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...
Performance analysis of a low power low noise tunable band pass filter for multiband RF front end
International Nuclear Information System (INIS)
Manjula, J.; Malarvizhi, S.
2014-01-01
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. (semiconductor integrated circuits)
Theoretical model for a background noise limited laser-excited optical filter for doubled Nd lasers
Shay, Thomas M.; Garcia, Daniel F.
1990-01-01
A simple theoretical model for the calculation of the dependence of filter quantum efficiency versus laser pump power in an atomic Rb vapor laser-excited optical filter is reported. Calculations for Rb filter transitions that can be used to detect the practical and important frequency-doubled Nd lasers are presented. The results of these calculations show the filter's quantum efficiency versus the laser pump power. The required laser pump powers required range from 2.4 to 60 mW/sq cm of filter aperture.
Fast random-number generation using a diode laser's frequency noise characteristic
Takamori, Hiroki; Doi, Kohei; Maehara, Shinya; Kawakami, Kohei; Sato, Takashi; Ohkawa, Masashi; Ohdaira, Yasuo
2012-02-01
Random numbers can be classified as either pseudo- or physical-random, in character. Pseudo-random numbers are generated by definite periodicity, so, their usefulness in cryptographic applications is somewhat limited. On the other hand, naturally-generated physical-random numbers have no calculable periodicity, thereby making them ideal for the task. Diode lasers' considerable wideband noise gives them tremendous capacity for generating physical-random numbers, at a high rate of speed. We measured a diode laser's output with a fast photo detector, and evaluated the binary-numbers from the diode laser's frequency noise characteristics. We then identified and evaluated the binary-number-line's statistical properties. We also investigate the possibility that much faster physical-random number parallel-generation is possible, using separate outputs of different optical-path length and character, which we refer to as "coherence collapse".
Random matrix theory filters in portfolio optimisation: A stability and risk assessment
Daly, J.; Crane, M.; Ruskin, H. J.
2008-07-01
Random matrix theory (RMT) filters, applied to covariance matrices of financial returns, have recently been shown to offer improvements to the optimisation of stock portfolios. This paper studies the effect of three RMT filters on the realised portfolio risk, and on the stability of the filtered covariance matrix, using bootstrap analysis and out-of-sample testing. We propose an extension to an existing RMT filter, (based on Krzanowski stability), which is observed to reduce risk and increase stability, when compared to other RMT filters tested. We also study a scheme for filtering the covariance matrix directly, as opposed to the standard method of filtering correlation, where the latter is found to lower the realised risk, on average, by up to 6.7%. We consider both equally and exponentially weighted covariance matrices in our analysis, and observe that the overall best method out-of-sample was that of the exponentially weighted covariance, with our Krzanowski stability-based filter applied to the correlation matrix. We also find that the optimal out-of-sample decay factors, for both filtered and unfiltered forecasts, were higher than those suggested by Riskmetrics [J.P. Morgan, Reuters, Riskmetrics technical document, Technical Report, 1996. http://www.riskmetrics.com/techdoc.html], with those for the latter approaching a value of α=1. In conclusion, RMT filtering reduced the realised risk, on average, and in the majority of cases when tested out-of-sample, but increased the realised risk on a marked number of individual days-in some cases more than doubling it.
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.
A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image
Directory of Open Access Journals (Sweden)
Fei Wang
2017-01-01
Full Text Available An Intensified Charge-Coupled Device (ICCD image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a Different from the independent identically distributed (i.i.d. noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.
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 ...
Brain stem auditory potentials evoked by clicks in the presence of high-pass filtered noise in dogs.
Poncelet, L; Deltenre, P; Coppens, A; Michaux, C; Coussart, E
2006-04-01
This study evaluates the effects of a high-frequency hearing loss simulated by the high-pass-noise masking method, on the click-evoked brain stem-evoked potentials (BAEP) characteristics in dogs. BAEP were obtained in response to rarefaction and condensation click stimuli from 60 dB normal hearing level (NHL, corresponding to 89 dB sound pressure level) to wave V threshold, using steps of 5 dB in eleven 58 to 80-day-old Beagle puppies. Responses were added, providing an equivalent to alternate polarity clicks, and subtracted, providing the rarefaction-condensation potential (RCDP). The procedure was repeated while constant level, high-pass filtered (HPF) noise was superposed to the click. Cut-off frequencies of the successively used filters were 8, 4, 2 and 1 kHz. For each condition, wave V and RCDP thresholds, and slope of the wave V latency-intensity curve (LIC) were collected. The intensity range at which RCDP could not be recorded (pre-RCDP range) was calculated. Compared with the no noise condition, the pre-RCDP range significantly diminished and the wave V threshold significantly increased when the superposed HPF noise reached the 4 kHz area. Wave V LIC slope became significantly steeper with the 2 kHz HPF noise. In this non-invasive model of high-frequency hearing loss, impaired hearing of frequencies from 8 kHz and above escaped detection through click BAEP study in dogs. Frequencies above 13 kHz were however not specifically addressed in this study.
Identification and Filtering of Uncharacteristic Noise in the CMS Hadron Calorimeter
Chatrchyan, S; Sirunyan, A M; Adam, W; Arnold, B; Bergauer, H; Bergauer, T; Dragicevic, M; Eichberger, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hammer, J; Hänsel, S; Hoch, M; Hörmann, N; Hrubec, J; Jeitler, M; Kasieczka, G; Kastner, K; Krammer, M; Liko, D; Magrans de Abril, I; Mikulec, I; Mittermayr, F; Neuherz, B; Oberegger, M; Padrta, M; Pernicka, M; Rohringer, H; Schmid, S; Schöfbeck, R; Schreiner, T; Stark, R; Steininger, H; Strauss, J; Taurok, A; Teischinger, F; Themel, T; Uhl, D; Wagner, P; Waltenberger, W; Walzel, G; Widl, E; Wulz, C E; Chekhovsky, V; Dvornikov, O; Emeliantchik, I; Litomin, A; Makarenko, V; Marfin, I; Mossolov, V; Shumeiko, N; Solin, A; Stefanovitch, R; Suarez Gonzalez, J; Tikhonov, A; Fedorov, A; Karneyeu, A; Korzhik, M; Panov, V; Zuyeuski, R; Kuchinsky, P; Beaumont, W; Benucci, L; Cardaci, M; De Wolf, E A; Delmeire, E; Druzhkin, D; Hashemi, M; Janssen, X; Maes, T; Mucibello, L; Ochesanu, S; Rougny, R; Selvaggi, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Adler, V; Beauceron, S; Blyweert, S; D'Hondt, J; De Weirdt, S; Devroede, O; Heyninck, J; Kalogeropoulos, A; Maes, J; Maes, M; Mozer, M U; Tavernier, S; Van Doninck, W; Van Mulders, P; Villella, I; Bouhali, O; Chabert, E C; Charaf, O; Clerbaux, B; De Lentdecker, G; Dero, V; Elgammal, S; Gay, A P R; Hammad, G H; Marage, P E; Rugovac, S; Vander Velde, C; Vanlaer, P; Wickens, J; Grunewald, M; Klein, B; Marinov, A; Ryckbosch, D; Thyssen, F; Tytgat, M; Vanelderen, L; Verwilligen, P; Basegmez, S; Bruno, G; Caudron, J; Delaere, C; Demin, P; Favart, D; Giammanco, A; Grégoire, G; Lemaitre, V; Militaru, O; Ovyn, S; Piotrzkowski, K; Quertenmont, L; Schul, N; Beliy, N; Daubie, E; Alves, G A; Pol, M E; Souza, M H G; Carvalho, W; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Mundim, L; Oguri, V; Santoro, A; Silva Do Amaral, S M; Sznajder, A; Fernandez Perez Tomei, T R; Ferreira Dias, M A; Gregores, E M; Novaes, S F; Abadjiev, K; Anguelov, T; Damgov, J; Darmenov, N; Dimitrov, L; Genchev, V; Iaydjiev, P; Piperov, S; Stoykova, S; Sultanov, G; Trayanov, R; Vankov, I; Dimitrov, A; Dyulendarova, M; Kozhuharov, V; Litov, L; Marinova, E; Mateev, M; Pavlov, B; Petkov, P; Toteva, Z; Chen, G M; Chen, H S; Guan, W; Jiang, C H; Liang, D; Liu, B; Meng, X; Tao, J; Wang, J; Wang, Z; Xue, Z; Zhang, Z; Ban, Y; Cai, J; Ge, Y; Guo, S; Hu, Z; Mao, Y; Qian, S J; Teng, H; Zhu, B; Avila, C; Baquero Ruiz, M; Carrillo Montoya, C A; Gomez, A; Gomez Moreno, B; Ocampo Rios, A A; Osorio Oliveros, A F; Reyes Romero, D; Sanabria, J C; Godinovic, N; Lelas, K; Plestina, R; Polic, D; Puljak, I; Antunovic, Z; Dzelalija, M; Brigljevic, V; Duric, S; Kadija, K; Morovic, S; Fereos, R; Galanti, M; Mousa, J; Papadakis, A; Ptochos, F; Razis, P A; Tsiakkouri, D; Zinonos, Z; Hektor, A; Kadastik, M; Kannike, K; Müntel, M; Raidal, M; Rebane, L; Anttila, E; Czellar, S; Härkönen, J; Heikkinen, A; Karimäki, V; Kinnunen, R; Klem, J; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Nysten, J; Tuominen, E; Tuominiemi, J; Ungaro, D; Wendland, L; Banzuzi, K; Korpela, A; Tuuva, T; Nedelec, P; Sillou, D; Besancon, M; Chipaux, R; Dejardin, M; Denegri, D; Descamps, J; Fabbro, B; Faure, J L; Ferri, F; Ganjour, S; Gentit, F X; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Lemaire, M C; Locci, E; Malcles, J; Marionneau, M; Millischer, L; Rander, J; Rosowsky, A; Rousseau, D; Titov, M; Verrecchia, P; Baffioni, S; Bianchini, L; Bluj, M; Busson, P; Charlot, C; Dobrzynski, L; Granier de Cassagnac, R; Haguenauer, M; Miné, P; Paganini, P; Sirois, Y; Thiebaux, C; Zabi, A; Agram, J L; Besson, A; Bloch, D; Bodin, D; Brom, J M; Conte, E; Drouhin, F; Fontaine, J C; Gelé, D; Goerlach, U; Gross, L; Juillot, P; Le Bihan, A C; Patois, Y; Speck, J; Van Hove, P; Baty, C; Bedjidian, M; Blaha, J; Boudoul, G; Brun, H; Chanon, N; Chierici, R; Contardo, D; Depasse, P; Dupasquier, T; El Mamouni, H; Fassi, F; Fay, J; Gascon, S; Ille, B; Kurca, T; Le Grand, T; Lethuillier, M; Lumb, N; Mirabito, L; Perries, S; Vander Donckt, M; Verdier, P; Djaoshvili, N; Roinishvili, N; Roinishvili, V; Amaglobeli, N; Adolphi, R; Anagnostou, G; Brauer, R; Braunschweig, W; Edelhoff, M; Esser, H; Feld, L; Karpinski, W; Khomich, A; Klein, K; Mohr, N; Ostaptchouk, A; Pandoulas, D; Pierschel, G; Raupach, F; Schael, S; Schultz von Dratzig, A; Schwering, G; Sprenger, D; Thomas, M; Weber, M; Wittmer, B; Wlochal, M; Actis, O; Altenhöfer, G; Bender, W; Biallass, P; Erdmann, M; Fetchenhauer, G; Frangenheim, J; Hebbeker, T; Hilgers, G; Hinzmann, A; Hoepfner, K; Hof, C; Kirsch, M; Klimkovich, T; Kreuzer, P; Lanske, D; Merschmeyer, M; Meyer, A; Philipps, B; Pieta, H; Reithler, H; Schmitz, S A; Sonnenschein, L; Sowa, M; Steggemann, J; Szczesny, H; Teyssier, D; Zeidler, C; Bontenackels, M; Davids, M; Duda, M; Flügge, G; Geenen, H; Giffels, M; Haj Ahmad, W; Hermanns, T; Heydhausen, D; Kalinin, S; Kress, T; Linn, A; Nowack, A; Perchalla, L; Poettgens, M; Pooth, O; Sauerland, P; Stahl, A; Tornier, D; Zoeller, M H; Aldaya Martin, M; Behrens, U; Borras, K; Campbell, A; Castro, E; Dammann, D; Eckerlin, G; Flossdorf, A; Flucke, G; Geiser, A; Hatton, D; Hauk, J; Jung, H; Kasemann, M; Katkov, I; Kleinwort, C; Kluge, H; Knutsson, A; Kuznetsova, E; Lange, W; Lohmann, W; Mankel, R; Marienfeld, M; Meyer, A B; Miglioranzi, S; Mnich, J; Ohlerich, M; Olzem, J; Parenti, A; Rosemann, C; Schmidt, R; Schoerner-Sadenius, T; Volyanskyy, D; Wissing, C; Zeuner, W D; Autermann, C; Bechtel, F; Draeger, J; Eckstein, D; Gebbert, U; Kaschube, K; Kaussen, G; Klanner, R; Mura, B; Naumann-Emme, S; Nowak, F; Pein, U; Sander, C; Schleper, P; Schum, T; Stadie, H; Steinbrück, G; Thomsen, J; Wolf, R; Bauer, J; Blüm, P; Buege, V; Cakir, A; Chwalek, T; De Boer, W; Dierlamm, A; Dirkes, G; Feindt, M; Felzmann, U; Frey, M; Furgeri, A; Gruschke, J; Hackstein, C; Hartmann, F; Heier, S; Heinrich, M; Held, H; Hirschbuehl, D; Hoffmann, K H; Honc, S; Jung, C; Kuhr, T; Liamsuwan, T; Martschei, D; Mueller, S; Müller, Th; Neuland, M B; Niegel, M; Oberst, O; Oehler, A; Ott, J; Peiffer, T; Piparo, D; Quast, G; Rabbertz, K; Ratnikov, F; Ratnikova, N; Renz, M; Saout, C; Sartisohn, G; Scheurer, A; Schieferdecker, P; Schilling, F P; Schott, G; Simonis, H J; Stober, F M; Sturm, P; Troendle, D; Trunov, A; Wagner, W; Wagner-Kuhr, J; Zeise, M; Zhukov, V; Ziebarth, E B; Daskalakis, G; Geralis, T; Karafasoulis, K; Kyriakis, A; Loukas, D; Markou, A; Markou, C; Mavrommatis, C; Petrakou, E; Zachariadou, A; Gouskos, L; Katsas, P; Panagiotou, A; Evangelou, I; Kokkas, P; Manthos, N; Papadopoulos, I; Patras, V; Triantis, F A; Bencze, G; Boldizsar, L; Debreczeni, G; Hajdu, C; Hernath, S; Hidas, P; Horvath, D; Krajczar, K; Laszlo, A; Patay, G; Sikler, F; Toth, N; Vesztergombi, G; Beni, N; Christian, G; Imrek, J; Molnar, J; Novak, D; Palinkas, J; Szekely, G; Szillasi, Z; Tokesi, K; Veszpremi, V; Kapusi, A; Marian, G; Raics, P; Szabo, Z; Trocsanyi, Z L; Ujvari, B; Zilizi, G; Bansal, S; Bawa, H S; Beri, S B; Bhatnagar, V; Jindal, M; Kaur, M; Kaur, R; Kohli, J M; Mehta, M Z; Nishu, N; Saini, L K; Sharma, A; Singh, A; Singh, J B; Singh, S P; Ahuja, S; Arora, S; Bhattacharya, S; Chauhan, S; Choudhary, B C; Gupta, P; Jain, S; Jha, M; Kumar, A; Ranjan, K; Shivpuri, R K; Srivastava, A K; Choudhury, R K; Dutta, D; Kailas, S; Kataria, S K; Mohanty, A K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Guchait, M; Gurtu, A; Maity, M; Majumder, D; Majumder, G; Mazumdar, K; Nayak, A; Saha, A; Sudhakar, K; Banerjee, S; Dugad, S; Mondal, N K; Arfaei, H; Bakhshiansohi, H; Fahim, A; Jafari, A; Mohammadi Najafabadi, M; Moshaii, A; Paktinat Mehdiabadi, S; Rouhani, S; Safarzadeh, B; Zeinali, M; Felcini, M; Abbrescia, M; Barbone, L; Chiumarulo, F; Clemente, A; Colaleo, A; Creanza, D; Cuscela, G; De Filippis, N; De Palma, M; De Robertis, G; Donvito, G; Fedele, F; Fiore, L; Franco, M; Iaselli, G; Lacalamita, N; Loddo, F; Lusito, L; Maggi, G; Maggi, M; Manna, N; Marangelli, B; My, S; Natali, S; Nuzzo, S; Papagni, G; Piccolomo, S; Pierro, G A; Pinto, C; Pompili, A; Pugliese, G; Rajan, R; Ranieri, A; Romano, F; Roselli, G; Selvaggi, G; Shinde, Y; Silvestris, L; Tupputi, S; Zito, G; Abbiendi, G; Bacchi, W; Benvenuti, A C; Boldini, M; Bonacorsi, D; Braibant-Giacomelli, S; Cafaro, V D; Caiazza, S S; Capiluppi, P; Castro, A; Cavallo, F R; Codispoti, G; Cuffiani, M; D'Antone, I; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Giordano, V; Giunta, M; Grandi, C; Guerzoni, M; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Odorici, F; Pellegrini, G; Perrotta, A; Rossi, A M; Rovelli, T; Siroli, G; Torromeo, G; Travaglini, R; Albergo, S; Costa, S; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Broccolo, G; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Frosali, S; Gallo, E; Genta, C; Landi, G; Lenzi, P; Meschini, M; Paoletti, S; Sguazzoni, G; Tropiano, A; Benussi, L; Bertani, M; Bianco, S; Colafranceschi, S; Colonna, D; Fabbri, F; Giardoni, M; Passamonti, L; Piccolo, D; Pierluigi, D; Ponzio, B; Russo, A; Fabbricatore, P; Musenich, R; Benaglia, A; 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Bourilkov, D; Chen, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fu, Y; Furic, I K; Gartner, J; Holmes, D; Kim, B; Klimenko, S; Konigsberg, J; Korytov, A; Kotov, K; Kropivnitskaya, A; Kypreos, T; Madorsky, A; Matchev, K; Mitselmakher, G; Pakhotin, Y; Piedra Gomez, J; Prescott, C; Rapsevicius, V; Remington, R; Schmitt, M; Scurlock, B; Wang, D; Yelton, J; Ceron, C; Gaultney, V; Kramer, L; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, T; Askew, A; Baer, H; Bertoldi, M; Chen, J; Dharmaratna, W G D; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; Prettner, E; Prosper, H; Sekmen, S; Baarmand, M M; Guragain, S; Hohlmann, M; Kalakhety, H; Mermerkaya, H; Ralich, R; Vodopiyanov, I; Abelev, B; Adams, M R; Anghel, I M; Apanasevich, L; Bazterra, V E; Betts, R R; Callner, J; Castro, M A; Cavanaugh, R; Dragoiu, C; Garcia-Solis, E J; Gerber, C E; Hofman, D J; Khalatian, S; Mironov, C; Shabalina, E; Smoron, A; Varelas, N; Akgun, U; Albayrak, E A; Ayan, A S; Bilki, B; Briggs, R; Cankocak, K; Chung, K; Clarida, W; Debbins, P; Duru, F; Ingram, F D; Lae, C K; McCliment, E; Merlo, J P; Mestvirishvili, A; Miller, M J; Moeller, A; Nachtman, J; Newsom, C R; Norbeck, E; Olson, J; Onel, Y; Ozok, F; Parsons, J; Schmidt, I; Sen, S; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bonato, A; Chien, C Y; Fehling, D; Giurgiu, G; Gritsan, A V; Guo, Z J; Maksimovic, P; Rappoccio, S; Swartz, M; Tran, N V; Zhang, Y; Baringer, P; Bean, A; Grachov, O; Murray, M; Radicci, V; Sanders, S; Wood, J S; Zhukova, V; Bandurin, D; Bolton, T; Kaadze, K; Liu, A; Maravin, Y; Onoprienko, D; Svintradze, I; Wan, Z; Gronberg, J; Hollar, J; Lange, D; Wright, D; Baden, D; Bard, R; Boutemeur, M; Eno, S C; Ferencek, D; Hadley, N J; Kellogg, R G; Kirn, M; Kunori, S; Rossato, K; Rumerio, P; Santanastasio, F; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Toole, T; Twedt, E; Alver, B; Bauer, G; Bendavid, J; Busza, W; Butz, E; Cali, I A; Chan, M; 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.
Boukhayma, Assim; Dupret, Antoine; Rostaing, Jean-Pierre; Enz, Christian
2016-03-03
This paper presents the first low noise complementary metal oxide semiconductor (CMOS) deletedCMOS terahertz (THz) imager based on source modulation and in-pixel high-Q filtering. The 31 × 31 focal plane array has been fully integrated in a 0 . 13 μ m standard CMOS process. The sensitivity has been improved significantly by modulating the active THz source that lights the scene and performing on-chip high-Q filtering. Each pixel encompass a broadband bow tie antenna coupled to an N-type metal-oxide-semiconductor (NMOS) detector that shifts the THz radiation, a low noise adjustable gain amplifier and a high-Q filter centered at the modulation frequency. The filter is based on a passive switched-capacitor (SC) N-path filter combined with a continuous-time broad-band Gm-C filter. A simplified analysis that helps in designing and tuning the passive SC N-path filter is provided. The characterization of the readout chain shows that a Q factor of 100 has been achieved for the filter with a good matching between the analytical calculation and the measurement results. An input-referred noise of 0 . 2 μ V RMS has been measured. Characterization of the chip with different THz wavelengths confirms the broadband feature of the antenna and shows that this THz imager reaches a total noise equivalent power of 0 . 6 nW at 270 GHz and 0 . 8 nW at 600 GHz.
Energy Technology Data Exchange (ETDEWEB)
Gomez-Cardona, Daniel; Cruz-Bastida, Juan Pablo [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 (United States); Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 and Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, Madison, Wisconsin 53792 (United States); Budde, Adam; Hsieh, Jiang [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 and GE Healthcare, 3000 N Grandview Boulevard, Waukesha, Wisconsin 53188 (United States)
2016-08-15
Purpose: Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction. Methods: A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object. Results: (1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of
International Nuclear Information System (INIS)
Gomez-Cardona, Daniel; Cruz-Bastida, Juan Pablo; Li, Ke; Chen, Guang-Hong; Budde, Adam; Hsieh, Jiang
2016-01-01
Purpose: Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction. Methods: A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object. Results: (1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of
Suppression of thermal noise in a non-Markovian random velocity field
International Nuclear Information System (INIS)
Ueda, Masahiko
2016-01-01
We study the diffusion of Brownian particles in a Gaussian random velocity field with short memory. By extending the derivation of an effective Fokker–Planck equation for the Lanvegin equation with weakly colored noise to a random velocity-field problem, we find that the effect of thermal noise on particles is suppressed by the existence of memory. We also find that the renormalization effect for the relative diffusion of two particles is stronger than that for single-particle diffusion. The results are compared with those of molecular dynamics simulations. (paper: classical statistical mechanics, equilibrium and non-equilibrium)
Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui
2016-01-01
The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the
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.
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.
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].
Wan, Renzhi; Zu, Yunxiao; Shao, Lin
2018-04-01
The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.
Zhang, Qun; Yang, Yanfu; Xiang, Qian; Zhou, Zhongqing; Yao, Yong
2018-02-01
A joint compensation scheme based on cascaded Kalman filter is proposed, which can implement polarization tracking, channel equalization, frequency offset, and phase noise compensation simultaneously. The experimental results show that the proposed algorithm can not only compensate multiple channel impairments simultaneously but also improve the polarization tracking capacity and accelerate the convergence speed. The scheme has up to eight times faster convergence speed compared with radius-directed equalizer (RDE) + Max-FFT (maximum fast Fourier transform) + BPS (blind phase search) and can track up polarization rotation 60 times and 15 times faster than that of RDE + Max-FFT + BPS and CMMA (cascaded multimodulus algorithm) + Max-FFT + BPS, respectively.
International Nuclear Information System (INIS)
Gerber, M.S.; Muller, D.W.
1976-01-01
The analysis of an orthogonal strip, two-dimensional position sensitive high purity germanium gamma ray detector is discussed. Position sensitivity is obtained by connecting each electrode strip on the detector to a resistor network. Charge, entering the network, divides in relation to the resistance between its entry point and the virtual earth points of the charge sensitive preamplifiers located at the end of each resistor network. The difference of the voltage pulses at the output of each preamplifier is proportional to the position at which the charge entered the resistor network and the sum of the pulse is proportional to the energy of the detected gamma ray. The analysis and spatial noise resolution is presented for this type of position sensitive detector. The results of the analysis show that the position resolution is proportional to the square root of the filter amplifier's output pulse time constant and that for energy measurement the resolution is maximized at the filter amplifier's noise corner time constant. The design of the electronic noise filtering system for the prototype gamma ray camera was based on the mathematical energy and spatial resolution equations. For the spatial channel a Gaussian trapezoidal filtering system was developed. Gaussian filtering was used for the energy channel. The detector noise model was verified by taking rms noise measurements of the filtered energy and spatial pulses from resistive readout charge dividing detectors. These measurements were within 10% of theory. (Auth.)
An effective approach to attenuate random noise based on compressive sensing and curvelet transform
International Nuclear Information System (INIS)
Liu, Wei; Cao, Siyuan; Zu, Shaohuan; Chen, Yangkang
2016-01-01
Random noise attenuation is an important step in seismic data processing. In this paper, we propose a novel denoising approach based on compressive sensing and the curvelet transform. We formulate the random noise attenuation problem as an L _1 norm regularized optimization problem. We propose to use the curvelet transform as the sparse transform in the optimization problem to regularize the sparse coefficients in order to separate signal and noise and to use the gradient projection for sparse reconstruction (GPSR) algorithm to solve the formulated optimization problem with an easy implementation and a fast convergence. We tested the performance of our proposed approach on both synthetic and field seismic data. Numerical results show that the proposed approach can effectively suppress the distortion near the edge of seismic events during the noise attenuation process and has high computational efficiency compared with the traditional curvelet thresholding and iterative soft thresholding based denoising methods. Besides, compared with f-x deconvolution, the proposed denoising method is capable of eliminating the random noise more effectively while preserving more useful signals. (paper)
Directory of Open Access Journals (Sweden)
Dermody James J
2004-11-01
Full Text Available Abstract Background A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. Results We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. Conclusions This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups.
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....
Random attractors for stochastic lattice reversible Gray-Scott systems with additive noise
Directory of Open Access Journals (Sweden)
Hongyan Li
2015-10-01
Full Text Available In this article, we prove the existence of a random attractor of the stochastic three-component reversible Gray-Scott system on infinite lattice with additive noise. We use a transformation of addition involved with Ornstein-Uhlenbeck process, for proving the pullback absorbing property and the pullback asymptotic compactness of the reaction diffusion system with cubic nonlinearity.
Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function
Directory of Open Access Journals (Sweden)
Christofer Toumazou
2013-07-01
Full Text Available A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF, which is a derivation of Empirical Mode Decomposition (EMD, is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF, Wavelet Transform (WT, Particle Filter (PF and the averaging Intrinsic Mode Function (aIMF algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters.
Switching non-local median filter
Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji
2015-06-01
This paper describes a novel image filtering method for removal of random-valued impulse noise superimposed on grayscale images. Generally, it is well known that switching-type median filters are effective for impulse noise removal. In this paper, we propose a more sophisticated switching-type impulse noise removal method in terms of detail-preserving performance. Specifically, the noise detector of the proposed method finds out noise-corrupted pixels by focusing attention on the difference between the value of a pixel of interest (POI) and the median of its neighboring pixel values, and on the POI's isolation tendency from the surrounding pixels. Furthermore, the removal of the detected noise is performed by the newly proposed median filter based on non-local processing, which has superior detail-preservation capability compared to the conventional median filter. The effectiveness and the validity of the proposed method are verified by some experiments using natural grayscale images.
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.
Scargle, Jeffrey D.
1990-01-01
While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.
Random Access for Machine-Type Communication based on Bloom Filtering
DEFF Research Database (Denmark)
Pratas, Nuno; Stefanovic, Cedomir; Madueño, Germán Corrales
2016-01-01
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......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...... and the connection establishment cause. We instantiate the proposed method over the current LTE-A access protocol. However, the method is applicable to a more general class of random access protocols that use preambles or other reservation sequences, as expected to be the case in 5G systems. We show that our method...
Design optimisation of powers-of-two FIR filter using self-organising random immigrants GA
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.
Kalman Filtering with Real-Time Applications
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.
Institute of Scientific and Technical Information of China (English)
Li XIE; Lihua XIE
2007-01-01
We consider the stability of a random Riccati equation with a Markovian binary jump coefficient. More specifically, we are concerned with the boundedness of the solution of a random Riccati difference equation arising from Kalman filtering with measurement losses. A sufficient condition for the peak covariance stability is obtained which has a simpler form and is shown to be less conservative in some cases than a very recent result in existing literature. Furthermore, we show that a known sufficient condition is also necessary when the observability index equals one.
International Nuclear Information System (INIS)
Zhang Yu; Wang Guangyi; Lu Xinmiao; Hu Yongcai; Xu Jiangtao
2016-01-01
The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. (paper)
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
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.
A 55 nm CMOS ΔΣ fractional-N frequency synthesizer for WLAN transceivers with low noise filters
International Nuclear Information System (INIS)
Chen Mingyi; Chu Xiaojie; Yu Peng; Yan Jun; Shi Yin
2013-01-01
A fully integrated ΔΣ fractional-N frequency synthesizer fabricated in a 55 nm CMOS technology is presented for the application of IEEE 802.11b/g wireless local area network (WLAN) transceivers. A low noise filter, occupying a small die area, whose power supply is given by a high PSRR and low noise LDO regulator, is integrated on chip. The proposed synthesizer needs no off-chip components and occupies an area of 0.72 mm 2 excluding PAD. Measurement results show that in all channels, the phase noise of the synthesizer achieves −99 dBc/Hz and −119 dBc/Hz in band and out of band respectively with a reference frequency of 40 MHz and a loop bandwidth of 200 kHz. The integrated RMS phase error is no more than 0.6°. The proposed synthesizer consumes a total power of 15.6 mW. (semiconductor integrated circuits)
Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng
2018-01-01
Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).
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.
A modern mathematical method for filtering noise in low count experiments
Directory of Open Access Journals (Sweden)
Medhat Moustafa E.
2015-01-01
Full Text Available In the proposed work, a novel application of a numerical and functional analysis based on the discrete wavelet transform is discussed. The mathematics of improving signals and removing noises are described. Results obtained show that the method used in a variety of gamma spectra is superior to other techniques.
Ophem, S. van; Berkhoff, A.P.
2016-01-01
Summary For broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast-array Kalman
Hartman, Brian Davis
1995-01-01
A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal
Switching non-local vector median filter
Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji
2016-04-01
This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.
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
Composite correlation filter for O-ring detection in stationary colored noise
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.
Chuang, Jason; Ausloos, Emily C; Schwebach, Courtney A; Huang, Xin
2016-12-01
The perception of visual motion can be profoundly influenced by visual context. To gain insight into how the visual system represents motion speed, we investigated how a background stimulus that did not move in a net direction influenced the perceived speed of a center stimulus. Visual stimuli were two overlapping random-dot patterns. The center stimulus moved coherently in a fixed direction, whereas the background stimulus moved randomly. We found that human subjects perceived the speed of the center stimulus to be significantly faster than its veridical speed when the background contained motion noise. Interestingly, the perceived speed was tuned to the noise level of the background. When the speed of the center stimulus was low, the highest perceived speed was reached when the background had a low level of motion noise. As the center speed increased, the peak perceived speed was reached at a progressively higher background noise level. The effect of speed overestimation required the center stimulus to overlap with the background. Increasing the background size within a certain range enhanced the effect, suggesting spatial integration. The speed overestimation was significantly reduced or abolished when the center stimulus and the background stimulus had different colors, or when they were placed at different depths. When the center- and background-stimuli were perceptually separable, speed overestimation was correlated with perceptual similarity between the center- and background-stimuli. These results suggest that integration of motion energy from random motion noise has a significant impact on speed perception. Our findings put new constraints on models regarding the neural basis of speed perception. Copyright © 2016 the American Physiological Society.
A semi-supervised method to detect seismic random noise with fuzzy GK clustering
International Nuclear Information System (INIS)
Hashemi, Hosein; Javaherian, Abdolrahim; Babuska, Robert
2008-01-01
We present a new method to detect random noise in seismic data using fuzzy Gustafson–Kessel (GK) clustering. First, using an adaptive distance norm, a matrix is constructed from the observed seismic amplitudes. The next step is to find centres of ellipsoidal clusters and construct a partition matrix which determines the soft decision boundaries between seismic events and random noise. The GK algorithm updates the cluster centres in order to iteratively minimize the cluster variance. Multiplication of the fuzzy membership function with values of each sample yields new sections; we name them 'clustered sections'. The seismic amplitude values of the clustered sections are given in a way to decrease the level of noise in the original noisy seismic input. In pre-stack data, it is essential to study the clustered sections in a f–k domain; finding the quantitative index for weighting the post-stack data needs a similar approach. Using the knowledge of a human specialist together with the fuzzy unsupervised clustering, the method is a semi-supervised random noise detection. The efficiency of this method is investigated on synthetic and real seismic data for both pre- and post-stack data. The results show a significant improvement of the input noisy sections without harming the important amplitude and phase information of the original data. The procedure for finding the final weights of each clustered section should be carefully done in order to keep almost all the evident seismic amplitudes in the output section. The method interactively uses the knowledge of the seismic specialist in detecting the noise
Development of an electrometer/amplifier and filter set for analysis of reactor noise
International Nuclear Information System (INIS)
Strohl, Claude Emile
1996-01-01
In nuclear power reactors, the neutron detector signal is dependent on the number of fissions and the reactor power level. The detector signal can be divided into two components: a D C component, proportional to the average value and an A C component, which is the fluctuating part superimposed to the D C component. The analysis of the fluctuating part of the signal is called noise analysis and allow us to investigate phenomena occurring within the reactor vessel, such as vibrational of fuel elements and coolant density, temperature, pressure and flow changes. On the other hand, the measure of the static D C part allows us to measure the local power density. This work describes the development of a personal computer based signal conditioning card that, together with a personal computer commercial data acquisition card, can be used for noise analysis and reactivity measurements of signals coming from ionization chambers or SPD's. (author)
Reduction of Musical Noise in Spectral Subtraction Method Using Subframe Phase Randomization
Energy Technology Data Exchange (ETDEWEB)
Seok, J.W.; Bae, K.S. [Kyungpook National University, Taegu (Korea)
1999-06-01
The Subframe phase randomization method is applied to the spectral subtraction method to reduce the musical noise in nonvoicing region after speech enhancement. The musical noise in the spectral subtraction method is the result of the narrowband tonal components that appearing somewhat periodically in the spectrogram of unvoiced and silence regions. Thus each synthesis frame in nonvoicing region is divided into several subframes to broaden the narrowband spectrum, and then phases of silence and unvoiced regions are randomized to eliminate the tonal components in the spectrum while keeping the shape of the amplitude spectrum. Performance assessments based on visual inspection of spectrogram, objective measure, and informal subjective listening tests demonstrate the superiority of the proposed algorithm. (author). 7 refs., 5 figs.
Boukhayma, Assim; Dupret, Antoine; Rostaing, Jean-Pierre; Enz, Christian
2016-01-01
This paper presents the first low noise complementary metal oxide semiconductor (CMOS) terahertz (THz) imager based on source modulation and in-pixel high-Q filtering. The 31×31 focal plane array has been fully integrated in a 0.13μm standard CMOS process. The sensitivity has been improved significantly by modulating the active THz source that lights the scene and performing on-chip high-Q filtering. Each pixel encompass a broadband bow tie antenna coupled to an N-type metal-oxide-semiconductor (NMOS) detector that shifts the THz radiation, a low noise adjustable gain amplifier and a high-Q filter centered at the modulation frequency. The filter is based on a passive switched-capacitor (SC) N-path filter combined with a continuous-time broad-band Gm-C filter. A simplified analysis that helps in designing and tuning the passive SC N-path filter is provided. The characterization of the readout chain shows that a Q factor of 100 has been achieved for the filter with a good matching between the analytical calculation and the measurement results. An input-referred noise of 0.2μV RMS has been measured. Characterization of the chip with different THz wavelengths confirms the broadband feature of the antenna and shows that this THz imager reaches a total noise equivalent power of 0.6 nW at 270 GHz and 0.8 nW at 600 GHz. PMID:26950131
Wiener filter applied to a neutrongraphic system
International Nuclear Information System (INIS)
Crispim, V.R.; Lopes, R.T.; Borges, J.C.
1986-01-01
The randon characteristics of the image formation process influence the spatial image obtained in a neutrongraphy. Several methods can be used to optimize this image, though estimation of the noise added to the original signal. This work deals with the optimal filtering technique, using Wiener's filter. A simulation is made, where the signal (spatial resolution function) has a Lorentz's form, and ten kinds of random noise with increasing R.M.S. are generated and individually added to the original signal. Wiener's filter is applied to different noise amplitudes and the behaviour of the spatial resolution function for our system is also analysed. (Author) [pt
Pseudo-random arranged color filter array for controlling moiré patterns in display.
Zhou, Yangui; Fan, Hang; An, Sengzhong; Li, Juntao; Wang, Jiahui; Zhou, Jianying; Liu, Yikun
2015-11-16
Optical display quality can be degraded by the appearance of moiré pattern occurring in a display system consisting of a basic matrix superimposed with a functional structured optical layer. We propose in this paper a novel pseudo-random arranged color filter array with the table number arranged with an optimal design scenario. We show that the moiré pattern can be significantly reduced with the introduction of the special color filter array. The idea is tested with an experiment that gives rise to a substantially reduced moiré pattern in a display system. It is believed that the novel functional optical structures have significant impact to complex structured display system in general and to the autostereoscopic and integrated display systems in particular.
Kalman filtering with real-time applications
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...
International Nuclear Information System (INIS)
Rodrigues, Miesher L.; Serra, Andre da S.; He, Zhong; Zhu, Yuefeng
2009-01-01
3-D pixelated semiconductor detectors are used in radiation detection applications requiring spectroscopic and imaging information from radiation sources. Reconstruction algorithms used to determine direction and energy of incoming gamma rays can be improved by reducing electronic noise and using optimum filtering techniques. Position information can be improved by achieving sub-pixel resolution. Electronic noise is the limiting factor. Achieving sub-pixel resolution - position of the interaction better than one pixel pitch - in 3-D pixelated semiconductor detectors is a challenging task due to the fast transient characteristics of these signals. This work addresses two fundamental questions: the first is to determine the optimum filter, while the second is to estimate the achievable sub-pixel resolution using this filter. It is shown that the matched filter is the optimum filter when applying the signal-to-noise ratio criteria. Also, non-optimum filters are studied. The framework of 3-D waveform simulation using the Shockley-Ramo Theorem and the Hecht Equation for electron and hole trapping is presented in this work. This waveform simulator can be used to analyze current detectors as well as explore new ideas and concepts in future work. Numerical simulations show that assuming an electronic noise of 3.3 keV it is possible to subdivide the pixel region into 5x5 sub-pixels. After analyzing these results, it is suggested that sub-pixel information can also improve energy resolution. Current noise levels present the major drawback to both achieve sub-pixel resolution as well as improve energy resolution below the current limits. (author)
Kolhatkar, J.S.; Vandamme, L.K.J.; Salm, Cora; Wallinga, Hans
2004-01-01
The low-frequency noise power spectrum of small dimension MOSFETs is dominated by Lorentzians arising from random telegraph signals (RTS). The low-frequency noise is observed to decrease when the devices are periodically switched 'off'. The technique of determining the statistical lifetimes and
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...
CLASSIFICATION OF HYPERSPECTRAL DATA BASED ON GUIDED FILTERING AND RANDOM FOREST
Directory of Open Access Journals (Sweden)
H. Ma
2017-09-01
Full Text Available Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to “the curse of dimensionality”. In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA, guided image filtering and the random forest classifier (RF. In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.
M. O. Partala; S. Ya. Zhuk
2007-01-01
On the base of mixed Markoff process in discrete time optimal and quasioptimal algorithms is designed for adaptive filtration of speech signals in the presence of correlated noise with random variation of probabilistic characteristics.
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.
Quantum-noise randomized data encryption for wavelength-division-multiplexed fiber-optic networks
International Nuclear Information System (INIS)
Corndorf, Eric; Liang Chuang; Kanter, Gregory S.; Kumar, Prem; Yuen, Horace P.
2005-01-01
We demonstrate high-rate randomized data-encryption through optical fibers using the inherent quantum-measurement noise of coherent states of light. Specifically, we demonstrate 650 Mbit/s data encryption through a 10 Gbit/s data-bearing, in-line amplified 200-km-long line. In our protocol, legitimate users (who share a short secret key) communicate using an M-ry signal set while an attacker (who does not share the secret key) is forced to contend with the fundamental and irreducible quantum-measurement noise of coherent states. Implementations of our protocol using both polarization-encoded signal sets as well as polarization-insensitive phase-keyed signal sets are experimentally and theoretically evaluated. Different from the performance criteria for the cryptographic objective of key generation (quantum key-generation), one possible set of performance criteria for the cryptographic objective of data encryption is established and carefully considered
Dwivedi, Prashant Povel; Choi, Hee Joo; Kim, Byoung Joo; Cha, Myoungsik
2013-12-16
Random duty-cycle errors (RDE) in ferroelectric quasi-phase-matching (QPM) devices not only affect the frequency conversion efficiency, but also generate non-phase-matched parasitic noise that can be detrimental to some applications. We demonstrate an accurate but simple method for measuring the RDE in periodically poled lithium niobate. Due to the equivalence between the undepleted harmonic generation spectrum and the diffraction pattern from the QPM grating, we employed linear diffraction measurement which is much simpler than tunable harmonic generation experiments [J. S. Pelc, et al., Opt. Lett.36, 864-866 (2011)]. As a result, we could relate the RDE for the QPM device to the relative noise intensity between the diffraction orders.
Nan, Yinbo; Huo, Li; Lou, Caiyun
2005-05-20
We present a theoretical study of a supercontinuum (SC) continuous-wave (cw) optical source generation in highly nonlinear fiber and its noise properties through numerical simulations based on the nonlinear Schrödinger equation. Fluctuations of pump pulses generate substructures between the longitudinal modes that result in the generation of white noise and then in degradation of coherence and in a decrease of the modulation depths and the signal-to-noise ratio (SNR). A scheme for improvement of the SNR of a multiwavelength cw optical source based on a SC by use of the combination of a highly nonlinear fiber (HNLF), an optical bandpass filter, and a Fabry-Perot (FP) filter is presented. Numerical simulations show that the improvement in modulation depth is relative to the HNLF's length, the 3-dB bandwidth of the optical bandpass filter, and the reflection ratio of the FP filter and that the average improvement in modulation depth is 13.7 dB under specified conditions.
New high resolution Random Telegraph Noise (RTN) characterization method for resistive RAM
Maestro, M.; Diaz, J.; Crespo-Yepes, A.; Gonzalez, M. B.; Martin-Martinez, J.; Rodriguez, R.; Nafria, M.; Campabadal, F.; Aymerich, X.
2016-01-01
Random Telegraph Noise (RTN) is one of the main reliability problems of resistive switching-based memories. To understand the physics behind RTN, a complete and accurate RTN characterization is required. The standard equipment used to analyse RTN has a typical time resolution of ∼2 ms which prevents evaluating fast phenomena. In this work, a new RTN measurement procedure, which increases the measurement time resolution to 2 μs, is proposed. The experimental set-up, together with the recently proposed Weighted Time Lag (W-LT) method for the analysis of RTN signals, allows obtaining a more detailed and precise information about the RTN phenomenon.
Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc
2017-07-01
Dynamic CT perfusion (CTP) consists in repeated acquisitions of the same volume in different time steps, slightly before, during and slightly afterwards the injection of contrast media. Important functional information can be derived for each voxel, which reflect the local hemodynamic properties and hence the metabolism of the tissue. Different approaches are being investigated to exploit data redundancy and prior knowledge for noise reduction of such datasets, ranging from iterative reconstruction schemes to high dimensional filters. We propose a new spatial bilateral filter which makes use of the k-means clustering algorithm and of an optimal calculated guiding image. We named the proposed filter as k-means clustering guided bilateral filter (KMGB). In this study, the KMGB filter is compared with the partial temporal non-local means filter (PATEN), with the time-intensity profile similarity (TIPS) filter, and with a new version derived from it, by introducing the guiding image (GB-TIPS). All the filters were tested on a digital in-house developed brain CTP phantom, were noise was added to simulate 80 kV and 200 mAs (default scanning parameters), 100 mAs and 30 mAs. Moreover, the filters performances were tested on 7 noisy clinical datasets with different pathologies in different body regions. The original contribution of our work is two-fold: first we propose an efficient algorithm to calculate a guiding image to improve the results of the TIPS filter, secondly we propose the introduction of the k-means clustering step and demonstrate how this can potentially replace the TIPS part of the filter obtaining better results at lower computational efforts. As expected, in the GB-TIPS, the introduction of the guiding image limits the over-smoothing of the TIPS filter, improving spatial resolution by more than 50%. Furthermore, replacing the time-intensity profile similarity calculation with a fuzzy k-means clustering strategy (KMGB) allows to control the edge preserving
Clasen, Thomas F; Brown, Joseph; Collin, Simon; Suntura, Oscar; Cairncross, Sandy
2004-06-01
Ceramic water filters have been identified as one of the most promising and accessible technologies for treating water at the household level. In a six-month trial, water filters were distributed randomly to half of the 50 participating households in a rural community in Bolivia; the remaining households continued to use customary water handling practices and served as controls. In four rounds of sampling following distribution of the filters, 100% of the 96 water samples from the filter households were free of thermotolerant coliforms compared with 15.5% of the control household samples. Diarrheal disease risk for individuals in intervention households was 70% lower than for controls (95% confidence interval [CI] = 53-80%; P ceramic water filters enable low-income households to treat and maintain the microbiologic quality of their drinking water.
Neutron flux filtration using Kalman filter
International Nuclear Information System (INIS)
Urcikan, Marian
2005-01-01
In the course of the WWER-440 start-up procedure the time dependent reactivity is determined from the measured ionization chamber signal by inverse kinetic method. Due to the random nature of the fission process and random nature the detection process the measured ionization chamber signal contains certain noise content. To minimize the unwonted noise on measured reactivity one of the possibility method is utilization Kalman filter, based on a stochastic model of reactor system (Author)
International Nuclear Information System (INIS)
Kamezawa, H; Arimura, H; Ohki, M; Shirieda, K; Kameda, N
2014-01-01
Purpose: To investigate the possibility of exposure dose reduction of the cone-beam computed tomography (CBCT) in an image guided patient positioning system by using 6 noise suppression filters. Methods: First, a reference dose (RD) and low-dose (LD)-CBCT (X-ray volume imaging system, Elekta Co.) images were acquired with a reference dose of 86.2 mGy (weighted CT dose index: CTDIw) and various low doses of 1.4 to 43.1 mGy, respectively. Second, an automated rigid registration for three axes was performed for estimating setup errors between a planning CT image and the LD-CBCT images, which were processed by 6 noise suppression filters, i.e., averaging filter (AF), median filter (MF), Gaussian filter (GF), bilateral filter (BF), edge preserving smoothing filter (EPF) and adaptive partial median filter (AMF). Third, residual errors representing the patient positioning accuracy were calculated as an Euclidean distance between the setup error vectors estimated using the LD-CBCT image and RD-CBCT image. Finally, the relationships between the residual error and CTDIw were obtained for 6 noise suppression filters, and then the CTDIw for LD-CBCT images processed by the noise suppression filters were measured at the same residual error, which was obtained with the RD-CBCT. This approach was applied to an anthropomorphic pelvic phantom and two cancer patients. Results: For the phantom, the exposure dose could be reduced from 61% (GF) to 78% (AMF) by applying the noise suppression filters to the CBCT images. The exposure dose in a prostate cancer case could be reduced from 8% (AF) to 61% (AMF), and the exposure dose in a lung cancer case could be reduced from 9% (AF) to 37% (AMF). Conclusion: Using noise suppression filters, particularly an adaptive partial median filter, could be feasible to decrease the additional exposure dose to patients in image guided patient positioning systems
Energy Technology Data Exchange (ETDEWEB)
Kamezawa, H [Graduate School of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka (Japan); Fujimoto General Hospital, Miyakonojo, Miyazaki (Japan); Arimura, H; Ohki, M [Faculty of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka (Japan); Shirieda, K; Kameda, N [Fujimoto General Hospital, Miyakonojo, Miyazaki (Japan)
2014-06-01
Purpose: To investigate the possibility of exposure dose reduction of the cone-beam computed tomography (CBCT) in an image guided patient positioning system by using 6 noise suppression filters. Methods: First, a reference dose (RD) and low-dose (LD)-CBCT (X-ray volume imaging system, Elekta Co.) images were acquired with a reference dose of 86.2 mGy (weighted CT dose index: CTDIw) and various low doses of 1.4 to 43.1 mGy, respectively. Second, an automated rigid registration for three axes was performed for estimating setup errors between a planning CT image and the LD-CBCT images, which were processed by 6 noise suppression filters, i.e., averaging filter (AF), median filter (MF), Gaussian filter (GF), bilateral filter (BF), edge preserving smoothing filter (EPF) and adaptive partial median filter (AMF). Third, residual errors representing the patient positioning accuracy were calculated as an Euclidean distance between the setup error vectors estimated using the LD-CBCT image and RD-CBCT image. Finally, the relationships between the residual error and CTDIw were obtained for 6 noise suppression filters, and then the CTDIw for LD-CBCT images processed by the noise suppression filters were measured at the same residual error, which was obtained with the RD-CBCT. This approach was applied to an anthropomorphic pelvic phantom and two cancer patients. Results: For the phantom, the exposure dose could be reduced from 61% (GF) to 78% (AMF) by applying the noise suppression filters to the CBCT images. The exposure dose in a prostate cancer case could be reduced from 8% (AF) to 61% (AMF), and the exposure dose in a lung cancer case could be reduced from 9% (AF) to 37% (AMF). Conclusion: Using noise suppression filters, particularly an adaptive partial median filter, could be feasible to decrease the additional exposure dose to patients in image guided patient positioning systems.
Grosveld, Ferdinand W.
1990-01-01
The feasibility of predicting interior noise due to random acoustic or turbulent boundary layer excitation was investigated in experiments in which a statistical energy analysis model (VAPEPS) was used to analyze measurements of the acceleration response and sound transmission of flat aluminum, lucite, and graphite/epoxy plates exposed to random acoustic or turbulent boundary layer excitation. The noise reduction of the plate, when backed by a shallow cavity and excited by a turbulent boundary layer, was predicted using a simplified theory based on the assumption of adiabatic compression of the fluid in the cavity. The predicted plate acceleration response was used as input in the noise reduction prediction. Reasonable agreement was found between the predictions and the measured noise reduction in the frequency range 315-1000 Hz.
Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.
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.
International Nuclear Information System (INIS)
Oliveira, Alex C.H. de; Lima, Fernando R.A.; Vieira, Jose W.; Leal Neto, Viriato
2009-01-01
The anthropomorphic models used in computational dosimetry are predominantly build from scanning CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) image stacks obtained of patients or volunteers. The building of these stacks (usually called of voxel phantoms or tomography phantoms) requires computer processing to be used in an exposure computational model. Noises present in these stacks can be confused with significant structures. In a 3D image with periodic additive noise in the frequency domain, the noise is fully added to its central slice. The discrete Fourier transform is the fundamental mathematical tool that allows the switch of the spatial domain for the frequency domain, and vice versa. The FFT (fast Fourier transform) algorithm is an ideal computational tool for this switch in domain with efficiency. This paper presents a new methodology for implementation in managed C++ language (Microsoft Visual Studio R .NET) of the fast Fourier transform of 3D digital images (FFT3D) using, essentially, the trigonometric recombination. The reduction of periodic additive noise consists in filtering only the central slice of 3D image in the frequency domain and transforms it back into the spatial domain through the inverse FFT3D. An example of application of this method it is the zipper artifacts filtering in images of MRI. These processes were implemented in the software DIP (Digital Image Processing). (author)
Affectively salient meaning in random noise: a task sensitive to psychosis liability.
Galdos, Mariana; Simons, Claudia; Fernandez-Rivas, Aranzazu; Wichers, Marieke; Peralta, Concepción; Lataster, Tineke; Amer, Guillermo; Myin-Germeys, Inez; Allardyce, Judith; Gonzalez-Torres, Miguel Angel; van Os, Jim
2011-11-01
Stable differences in the tendency to attribute meaning and emotional value to experience may represent an indicator of liability to psychosis. A brief task was developed assessing variation in detecting affectively meaningful speech (speech illusion) in neutral random signals (white noise) and the degree to which this was associated with psychometric and familial vulnerability for psychosis. Thirty patients, 28 of their siblings, and 307 controls participated. The rate of speech illusion was compared between cases and controls. In controls, the association between speech illusion and interview-based positive schizotypy was assessed. The hypothesis of a dose-response increase in rate of speech illusion across increasing levels of familial vulnerability for psychosis (controls, siblings of patients, and patients) was examined. Patients were more likely to display speech illusions than controls (odds ratio [OR] = 4.0, 95% confidence interval [CI] = 1.4-11.7), also after controlling for neurocognitive variables (OR = 3.8, 95% CI = 1.04-14.1). The case-control difference was more accentuated for speech illusion perceived as affectively salient (positively or negatively appraised) than for neutrally appraised speech illusions. Speech illusion in the controls was strongly associated with positive schizotypy but not with negative schizotypy. In addition, the rate of speech illusion increased with increasing level of familial risk for psychotic disorder. The data suggest that the white noise task may be sensitive to psychometric and familial vulnerability for psychosis associated with alterations in top-down processing and/or salience attribution.
Random noise can help to improve synchronization of excimer laser pulses.
Mingesz, Róbert; Barna, Angéla; Gingl, Zoltán; Mellár, János
2016-02-01
Recently, we have reported on a compact microcontroller-based unit developed to accurately synchronize excimer laser pulses (Mingesz et al. 2012 Fluct. Noise Lett. 11, 1240007 (doi:10.1142/S021947751240007X)). We have shown that dithering based on random jitter noise plus pseudorandom numbers can be used in the digital control system to radically reduce the long-term drift of the laser pulse from the trigger and to improve the accuracy of the synchronization. In this update paper, we present our new experimental results obtained by the use of the delay-controller unit to tune the timing of a KrF excimer laser as an addition to our previous numerical simulation results. The hardware was interfaced to the laser using optical signal paths in order to reduce sensitivity to electromagnetic interference and the control algorithm tested by simulations was applied in the experiments. We have found that the system is able to reduce the delay uncertainty very close to the theoretical limit and performs well in real applications. The simple, compact and flexible system is universal enough to also be used in various multidisciplinary applications.
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.
Robust non-local median filter
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.
Human tracking in thermal images using adaptive particle filters with online random forest learning
Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal
2013-11-01
This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.
Discrete stochastic processes and optimal filtering
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
Brown, Joe; Sobsey, Mark D; Loomis, Dana
2008-09-01
A randomized, controlled intervention trial of two household-scale drinking water filters was conducted in a rural village in Cambodia. After collecting four weeks of baseline data on household water quality, diarrheal disease, and other data related to water use and handling practices, households were randomly assigned to one of three groups of 60 households: those receiving a ceramic water purifier (CWP), those receiving a second filter employing an iron-rich ceramic (CWP-Fe), and a control group receiving no intervention. Households were followed for 18 weeks post-baseline with biweekly follow-up. Households using either filter reported significantly less diarrheal disease during the study compared with a control group of households without filters as indicated by longitudinal prevalence ratios CWP: 0.51 (95% confidence interval [CI]: 0.41-0.63); CWP-Fe: 0.58 (95% CI: 0.47-0.71), an effect that was observed in all age groups and both sexes after controlling for clustering within households and within individuals over time.
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.
Physical-layer security analysis of PSK quantum-noise randomized cipher in optically amplified links
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.
Surface detection performance evaluation of pseudo-random noise continuous wave laser radar
Mitev, Valentin; Matthey, Renaud; Pereira do Carmo, Joao
2017-11-01
A number of space missions (including in the ESA Exploration Programme) foreseen a use of laser radar sensor (or lidar) for determination of range between spacecrafts or between spacecraft and ground surface (altimetry). Such sensors need to be compact, robust and power efficient, at the same time with high detection performance. These requirements can be achieved with a Pseudo-Random Noise continuous wave lidar (PRN cw lidar). Previous studies have pointed to the advantages of this lidar with respect to space missions, but they also identified its limitations in high optical background. The progress of the lasers and the detectors in the near IR spectral range requires a re-evaluation of the PRN cw lidar potential. Here we address the performances of this lidar for surface detection (altimetry) in planetary missions. The evaluation is based on the following system configuration: (i) A cw fiber amplifier as lidar transmitter. The seeding laser exhibits a single-frequency spectral line, with subsequent amplitude modulation. The fiber amplifier allows high output power level, keeping the spectral characteristics and the modulation of the seeding light input. (ii) An avalanche photodiode in photon counting detection; (iii) Measurement scenarios representative for Earth, Mercury and Mars.
Directory of Open Access Journals (Sweden)
Siva Kotipalli
2014-01-01
(SCA resistance. These designs are based on a delay-insensitive (DI logic paradigm known as null convention logic (NCL, which supports useful properties for resisting SCAs including dual-rail encoding, clock-free operation, and monotonic transitions. Potential benefits include reduced and more uniform switching activities and reduced signal-to-noise (SNR ratio. A novel method to further augment NCL AES hardware with random voltage scaling technique is also presented for additional security. Thereby, the proposed components leak significantly less side-channel information than conventional clocked approaches. To quantitatively verify such improvements, functional verification and WASSO (weighted average simultaneous switching output analysis have been carried out on both conventional synchronous approach and the proposed NCL based approach using Mentor Graphics ModelSim and Xilinx simulation tools. Hardware implementation has been carried out on both designs exploiting a specified side-channel attack standard evaluation FPGA board, called SASEBO-GII, and the corresponding power waveforms for both designs have been collected. Along with the results of software simulations, we have analyzed the collected waveforms to validate the claims related to benefits of the proposed cryptohardware design approach.
International Nuclear Information System (INIS)
Adzhemyan, L.Ts.; Vasil'ev, A.N.; Pis'mak, Yu.M.
1988-01-01
The investigation of the infrared behavior of the propagator of a light wave in a randomly inhomogeneous medium with massless Gaussian noise is continued. The infrared representation of the propagator for correlation function D varphi (k)∼k -2 is generalized to the case of an arbitrary power-law noise correlation function is rigorously established in the first two orders of the infrared asymptotic behavior by construction of a suitable R operation. As a consequence, the results are generalized to the case of critical opalescence, when D varphi (k)∼k -2+η , where η ∼ 0.03 is the Fisher index
Lee, Sangwoo; Miller, David O.; Schwemmer, Geary; Wilkerson, Thomas D.; Andrus, Ionio; Egbert, Cameron; Anderson, Mark; Starr, David OC. (Technical Monitor)
2002-01-01
Background noise reduction of War signals is one of the most important factors in achieving better signal to noise ratio and precise atmospheric data from Mar measurements. Fahey Perot etalons have been used in several lidar systems as narrow band pass filters in the reduction of scattered sunlight. An slalom with spectral bandwidth, (Delta)v=0.23/cm, free spectral range, FSR=6.7/cm, and diameter, d=24mm was installed in a fiber coupled box which included a 500 pm bandwidth interference Filter. The slalom box couples the telescope and detector with 200 pm core fibers and 21 mm focal length collimators. The angular magnification is M=48. The etalon box was inserted into the Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) system and tested during the HARGLO-2 intercomparison campaign conducted in November 2001 at Wallops Island, Virginia. This paper presents the preliminary test results of the slalom and a complete analysis will be presented at the conference.
Filtering Photogrammetric Point Clouds Using Standard LIDAR Filters Towards DTM Generation
Zhang, Z.; Gerke, M.; Vosselman, G.; Yang, M. Y.
2018-05-01
Digital Terrain Models (DTMs) can be generated from point clouds acquired by laser scanning or photogrammetric dense matching. During the last two decades, much effort has been paid to developing robust filtering algorithms for the airborne laser scanning (ALS) data. With the point cloud quality from dense image matching (DIM) getting better and better, the research question that arises is whether those standard Lidar filters can be used to filter photogrammetric point clouds as well. Experiments are implemented to filter two dense matching point clouds with different noise levels. Results show that the standard Lidar filter is robust to random noise. However, artefacts and blunders in the DIM points often appear due to low contrast or poor texture in the images. Filtering will be erroneous in these locations. Filtering the DIM points pre-processed by a ranking filter will bring higher Type II error (i.e. non-ground points actually labelled as ground points) but much lower Type I error (i.e. bare ground points labelled as non-ground points). Finally, the potential DTM accuracy that can be achieved by DIM points is evaluated. Two DIM point clouds derived by Pix4Dmapper and SURE are compared. On grassland dense matching generates points higher than the true terrain surface, which will result in incorrectly elevated DTMs. The application of the ranking filter leads to a reduced bias in the DTM height, but a slightly increased noise level.
Discriminality of statistically independent Gaussian noise tokens and random tone-burst complexes
Goossens, T.L.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.; Kollmeier, B.; Klump, G.; Hohmann, V.; Langemann, U.; Mauermann, M.; Uppenkamp, S.; Verhey, J.
2007-01-01
Hanna (1984) has shown that noise tokens with a duration of 400 ms are harder to discriminate than noise tokens of 100 ms. This is remarkable because a 400-ms stimulus potentially contains four times as much information for judging dissimilarity than the 100-ms stimulus. Apparently, the ability to
On the ability to discriminate Gaussian-noise tokens or random tone-burst complexes
Goossens, T.L.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.
2008-01-01
This study investigated factors that influence a listeners' ability to discriminate Gaussian-noise stimuli in a same-different discrimination paradigm. The first experiment showed that discrimination ability increased with bandwidth for noise durations up to 100 ms. Duration had a nonmonotonic
Arevalo-Lopez, H. S.; Levin, S. A.
2016-12-01
The vertical component of seismic wave reflections is contaminated by surface noise such as ground roll and secondary scattering from near surface inhomogeneities. A common method for attenuating these, unfortunately often aliased, arrivals is via velocity filtering and/or multichannel stacking. 3D-3C acquisition technology provides two additional sources of information about the surface wave noise that we exploit here: (1) areal receiver coverage, and (2) a pair of horizontal components recorded at the same location as the vertical component. Areal coverage allows us to segregate arrivals at each individual receiver or group of receivers by direction. The horizontal components, having much less compressional reflection body wave energy than the vertical component, provide a template of where to focus our energies on attenuating the surface wave arrivals. (In the simplest setting, the vertical component is a scaled 90 degree phase rotated version of the radial horizontal arrival, a potential third possible lever we have not yet tried to integrate.) The key to our approach is to use the magnitude of the horizontal components to outline a data-adaptive "velocity" filter region in the w-Kx-Ky domain. The big advantage for us is that even in the presence of uneven receiver geometries, the filter automatically tracks through aliasing without manual sculpting and a priori velocity and dispersion estimation. The method was applied to an aliased synthetic dataset based on a five layer earth model which also included shallow scatterers to simulate near-surface inhomogeneities and successfully removed both the ground roll and scatterers from the vertical component (Figure 1).
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.
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.
A 14-bit 30-MS/s 38-mW SAR ADC using noise filter gear shifting
Kramer, Martin; Janssen, Erwin; Doris, Kostas; Murmann, Boris
2017-01-01
We present a successive approximation register analog-to-digital converter (ADC) that employs a comparator with time-varying noise performance, realized by changing the integration time of a Gm-C preamplifier. This approach allows us to relax precision and enhance speed during noncritical decisions,
The benefits of noise and nonlinearity: Extracting energy from random vibrations
Energy Technology Data Exchange (ETDEWEB)
Gammaitoni, Luca, E-mail: luca.gammaitoni@pg.infn.it [NiPS Laboratory, Universita di Perugia, I-06100 Perugia (Italy); Neri, Igor; Vocca, Helios [NiPS Laboratory, Universita di Perugia, I-06100 Perugia (Italy)
2010-10-05
Nonlinear behavior is the ordinary feature of the vast majority of dynamical systems and noise is commonly present in any finite temperature physical and chemical system. In this article we briefly review the potentially beneficial outcome of the interplay of noise and nonlinearity by addressing the novel field of vibration energy harvesting. The role of nonlinearity in a piezoelectric harvester oscillator dynamics is modeled with nonlinear stochastic differential equation.
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
Thomas, Evan A; Tellez-Sanchez, Sarita; Wick, Carson; Kirby, Miles; Zambrano, Laura; Abadie Rosa, Ghislaine; Clasen, Thomas F; Nagel, Corey
2016-04-05
Subject reactivity--when research participants change their behavior in response to being observed--has been documented showing the effect of human observers. Electronics sensors are increasingly used to monitor environmental health interventions, but the effect of sensors on behavior has not been assessed. We conducted a cluster randomized controlled trial in Rwanda among 170 households (70 blinded to the presence of the sensor, 100 open) testing whether awareness of an electronic monitor would result in a difference in weekly use of household water filters and improved cookstoves over a four-week surveillance period. A 63% increase in number of uses of the water filter per week between the groups was observed in week 1, an average of 4.4 times in the open group and 2.83 times in the blind group, declining in week 4 to an insignificant 55% difference of 2.82 uses in the open, and 1.93 in the blind. There were no significant differences in the number of stove uses per week between the two groups. For both filters and stoves, use decreased in both groups over four-week installation periods. This study suggests behavioral monitoring should attempt to account for reactivity to awareness of electronic monitors that persists for weeks or more.
International Nuclear Information System (INIS)
Vani, V C; Chatterjee, S
2010-01-01
The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r 0 /Λ)≥0.11, where r 0 is the coherence length of light on scattering from the rough part and Λ is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a=0 to small finite values of a. We thus address the importance of the following quantities: '(a/λ)', which scales the amplitude of the periodic part with the wavelength of light, and (r 0 /Λ), in determining the detectability of the intensity peaks.
Reducing the random seed effect on segmentation by applying an edge-preserving filter
Addink, E.A.
2012-01-01
In region-growing segmentation algorithms random seed locations are used (reference). To ensure that repeating the segmentation will produce the same result, the seed locations are following a fixed random pattern. Empirical studies show that when the image that is subjected to the segmentation is
International Nuclear Information System (INIS)
Steinbrecher, Gyoergy; Weyssow, B.
2004-01-01
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 β 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
Discriminality of statistically independent Gaussian noise tokens and random tone-burst complexes
Goossens, T.L.J.; Par, van de, S.L.J.D.E.; Kohlrausch, A.G.; Kollmeier, B.; Klump, G.; Hohmann, V.; Langemann, U.; Mauermann, M.; Uppenkamp, S.; Verhey, J.
2007-01-01
Hanna (1984) has shown that noise tokens with a duration of 400 ms are harder to discriminate than noise tokens of 100 ms. This is remarkable because a 400-ms stimulus potentially contains four times as much information for judging dissimilarity than the 100-ms stimulus. Apparently, the ability to use all information in a stimulus is impaired by some kind of limitation, e.g. a memory limitation (cf. Cowan 2000) or a limitation in the ability to allocate attentional resources (cf. Kidd and Wat...
A random-parametric reactor model with direct feedback and non-white noise
International Nuclear Information System (INIS)
Sako, O.; Taniguchi, A.; Kuroda, Y.
1982-01-01
The effects of multiplicative direct power feedback and non-white reactivity noise on the fluctuations of the neutron density are studied, based on the master equation using the cumulant expansion and the system-size expansion. The results obtained are the following: non-whiteness of reactivity noise reduces the variance of neutron density, as well as the level of the power spectral density. The nonlinear effect of power feedback gives rise to at least a pair of corner frequencies, in contrast to the single corner frequency in linearized case. (author)
Ramachandra, Ranjan; Bouwer, James C; Mackey, Mason R; Bushong, Eric; Peltier, Steven T; Xuong, Nguyen-Huu; Ellisman, Mark H
2014-06-01
Energy filtered transmission electron microscopy techniques are regularly used to build elemental maps of spatially distributed nanoparticles in materials and biological specimens. When working with thick biological sections, electron energy loss spectroscopy techniques involving core-loss electrons often require exposures exceeding several minutes to provide sufficient signal to noise. Image quality with these long exposures is often compromised by specimen drift, which results in blurring and reduced resolution. To mitigate drift artifacts, a series of short exposure images can be acquired, aligned, and merged to form a single image. For samples where the target elements have extremely low signal yields, the use of charge coupled device (CCD)-based detectors for this purpose can be problematic. At short acquisition times, the images produced by CCDs can be noisy and may contain fixed pattern artifacts that impact subsequent correlative alignment. Here we report on the use of direct electron detection devices (DDD's) to increase the signal to noise as compared with CCD's. A 3× improvement in signal is reported with a DDD versus a comparably formatted CCD, with equivalent dose on each detector. With the fast rolling-readout design of the DDD, the duty cycle provides a major benefit, as there is no dead time between successive frames.
Selection vector filter framework
Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.
2003-10-01
We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.
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.
SPDEs with α-Stable Lévy Noise: A Random Field Approach
Directory of Open Access Journals (Sweden)
Raluca M. Balan
2014-01-01
Full Text Available This paper is dedicated to the study of a nonlinear SPDE on a bounded domain in Rd, with zero initial conditions and Dirichlet boundary, driven by an α-stable Lévy noise Z with α∈(0,2, α≠1, and possibly nonsymmetric tails. To give a meaning to the concept of solution, we develop a theory of stochastic integration with respect to this noise. The idea is to first solve the equation with “truncated” noise (obtained by removing from Z the jumps which exceed a fixed value K, yielding a solution uK, and then show that the solutions uL,L>K coincide on the event t≤τK, for some stopping times τK converging to infinity. A similar idea was used in the setting of Hilbert-space valued processes. A major step is to show that the stochastic integral with respect to ZK satisfies a pth moment inequality. This inequality plays the same role as the Burkholder-Davis-Gundy inequality in the theory of integration with respect to continuous martingales.
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.
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.
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.
Data Assimilation by Conditioning of Driving Noise on Future Observations
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.
An application of reactor noise techniques to neutron transport problems in a random medium
International Nuclear Information System (INIS)
Sahni, D.C.
1989-01-01
Neutron transport problems in a random medium are considered by defining a joint Markov process describing the fluctuations of one neutron population and the random changes in the medium. Backward Chapman-Kolmogorov equations are derived which yield an adjoint transport equation for the average neutron density. It is shown that this average density also satisfied the direct transport equation as given by the phenomenological model. (author)
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 state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....
International Nuclear Information System (INIS)
Akram, N.
1999-01-01
In this report we describe the concept of adaptive noise canceling, an alternative method of estimating signals corrupted by additive noise of interference. The method uses 'primary' input containing the corrupted signal and a 'reference' input containing noise correlated in some unknown way with the primary noise, the reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. When the reference input is free of signal and certain other conditions are met then noise in the primary input can be essentially eliminated without signal distortion. It is further shown that the adaptive filter also acts as notch filter. Simulated results illustrate the usefulness of the adaptive noise canceling technique. (author)
Jousselme, Chloé; Vialet, Renaud; Jouve, Elisabeth; Lagier, Pierre; Martin, Claude; Michel, Fabrice
2011-03-01
To determine whether a sound-activated light-alarm device could reduce the noise in the central area of our pediatric intensive care unit and to determine whether this reduction was significant enough to decrease the noise that could be perceived by a patient located in a nearby room. The secondary objective was to determine the mode of action of the device. In a 16-bed pediatric and neonatal intensive care unit, a large and clearly noticeable sound-activated light device was set in the noisiest part of the central area of our unit, and noise measurements were made in the central area and in a nearby room. In a prospective, quasi-experimental design, sound levels were compared across three different situations--no device present, device present and turned on, and device present but turned off--and noise level measurements were made over a total of 18 days. None. Setting a sound-activated light device on or off. When the device was present, the noise was about 2 dB lower in the central area and in a nearby room, but there was no difference in noise level with the device turned on vs. turned off. The noise decrease in the central area was of limited importance but was translated in a nearby room. The sound-activated light device did not directly decrease noise when turned on, but repetition of the visual signal throughout the day raised staff awareness of noise levels over time.
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
Investigation of reactivity change and neutron noise due to random absorber vibrations. 2
International Nuclear Information System (INIS)
Barthel, R.
1984-01-01
Perturbations of the neutron flux due to stochastically excited vibrations of absorbers have been investigated using a one-dimensional core model with N pointlike absorbers. Taking into account the flux depressions near the absorbers, pronounced peaks in the spectral power densities of the flux fluctuations have been found at multiples of the resonance frequencies in addition to the direct imaging of the resonances of absorber vibrations. Investigation of the space dependence of the corresponding transfer functions has shown that a localization is possible by means of the double frequency effect and that the dispersion of absorber vibrations can be determined by using the triple frequency effect. The conclusions of the paper are qualitatively compared with results of noise measurements at a pressurized water reactor. (author)
Random noise effects in pulse-mode digital multilayer neural networks.
Kim, Y C; Shanblatt, M A
1995-01-01
A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.
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....
Image pre-filtering for measurement error reduction in digital image correlation
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
International Nuclear Information System (INIS)
Okura, Yuki; Futamase, Toshifumi
2013-01-01
This is the third paper on the improvement of systematic errors in weak lensing analysis using an elliptical weight function, referred to as E-HOLICs. In previous papers, we succeeded in avoiding errors that depend on the ellipticity of the background image. In this paper, we investigate the systematic error that depends on the signal-to-noise ratio of the background image. We find that the origin of this error is the random count noise that comes from the Poisson noise of sky counts. The random count noise makes additional moments and centroid shift error, and those first-order effects are canceled in averaging, but the second-order effects are not canceled. We derive the formulae that correct this systematic error due to the random count noise in measuring the moments and ellipticity of the background image. The correction formulae obtained are expressed as combinations of complex moments of the image, and thus can correct the systematic errors caused by each object. We test their validity using a simulated image and find that the systematic error becomes less than 1% in the measured ellipticity for objects with an IMCAT significance threshold of ν ∼ 11.7.
Maximizing noise energy for noise-masking studies.
Jules Étienne, Cédric; Arleo, Angelo; Allard, Rémy
2017-08-01
Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100 %. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.
Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering
Institute of Scientific and Technical Information of China (English)
LI Shuo; TAO Ran
2006-01-01
We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.
Experimental use of iteratively designed rotation invariant correlation filters
International Nuclear Information System (INIS)
Sweeney, D.W.; Ochoa, E.; Schils, G.F.
1987-01-01
Iteratively designed filters are incorporated into an optical correlator for position, rotation, and intensity invariant recognition of target images. The filters exhibit excellent discrimination because they are designed to contain full information about the target image. Numerical simulations and experiments demonstrate detection of targets that are corrupted with random noise (SNR≅0.5) and also partially obscured by other objects. The complex valued filters are encoded in a computer generated hologram and fabricated directly using an electron-beam system. Experimental results using a liquid crystal spatial light modulator for real-time input show excellent agreement with analytical and numerical computations
Random genetic drift, natural selection, and noise in human cranial evolution.
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.
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.
Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.
2018-05-01
The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.
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
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.
Directory of Open Access Journals (Sweden)
Leila eChaieb
2015-04-01
Full Text Available Background: Application of transcranial random noise stimulation (tRNS between 0.1 and 640 Hz of the primary motor cortex (M1 for 10 minutes induces a persistent excitability increase lasting for at least 60 minutes. However, the mechanism of tRNS-induced cortical excitability alterations is not yet fully understood. Objective: The main aim of this study was to get first efficacy data with regard to the possible neuronal effect of tRNS. Methods: Single-pulse transcranial magnetic stimulation (TMS was used to measure levels of cortical excitability before and after combined application of tRNS at an intensity of 1mA for 10mins stimulation duration and a pharmacological agent (or sham on 8 healthy male participants. Results: The sodium channel blocker carbamazepine showed a tendency towards inhibiting MEPs 5-60 mins poststimulation. The GABAA agonist lorazepam suppressed tRNS-induced cortical excitability increases at 0-20 and 60 min time points. The partial NMDA receptor agonist D-cycloserine, the NMDA receptor antagonist dextromethorphan and the D2/D3 receptor agonist ropinirole had no significant effects on the excitability increases seen with tRNS.Conclusions: In contrast to transcranial direct current stimulation (tDCS, aftereffects of tRNS are seem to be not NMDA receptor dependent and can be suppressed by benzodiazepines suggesting that tDCS and tRNS depend upon different mechanisms.
Ganguly, Anshuman; Krishna Vemuri, Sri Hari; Panahi, Issa
2014-01-01
This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27 dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.
Susuki, I.
1981-11-01
The results of an analysis of the irregularity factors of stationary and Gaussian random processes which are generated by filtering the output of a pure or a band-limited white noise are presented. An ideal band pass filter, a trapezoidal filter, and a Butterworth type band pass filter were examined. It was found that the values of the irregularity factors were approximately equal among these filters if only the end-slopes were the same rates. As the band width of filters increases, irregularity factors increase monotonically and approach the respective constant values depending on the end-slopes. This implies that the noise characteristics relevant to the fatigue damage such as statistical aspects of the height of the rise and fall or the distribution of the peak values are not changed for a broad band random time history. It was also found that the effect of band limitation of input white noise on irregularity factors is negligibly small.
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
Niël-Weise, Barbara S; Stijnen, Theo; van den Broek, Peterhans J
2010-06-01
In this systematic review, we assessed the effect of in-line filters on infusion-related phlebitis associated with peripheral IV catheters. The study was designed as a systematic review and meta-analysis of randomized controlled trials. We used MEDLINE and the Cochrane Controlled Trial Register up to August 10, 2009. Two reviewers independently assessed trial quality and extracted data. Data on phlebitis were combined when appropriate, using a random-effects model. The impact of the risk of phlebitis in the control group (baseline risk) on the effect of in-line filters was studied by using meta-regression based on the bivariate meta-analysis model. The quality of the evidence was determined by using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) method. Eleven trials (1633 peripheral catheters) were included in this review to compare the effect of in-line filters on the incidence of phlebitis in hospitalized patients. Baseline risks across trials ranged from 23% to 96%. Meta-analysis of all trials showed that in-line filters reduced the risk of infusion-related phlebitis (relative risk, 0.66; 95% confidence interval, 0.43-1.00). This benefit, however, is very uncertain, because the trials had serious methodological shortcomings and meta-analysis revealed marked unexplained statistical heterogeneity (P < 0.0000, I(2) = 90.4%). The estimated benefit did not depend on baseline risk. In-line filters in peripheral IV catheters cannot be recommended routinely, because evidence of their benefit is uncertain.
Faraday anomalous dispersion optical filters
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.
Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.
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.
Rajasekhar, Anita; Lottenberg, Lawrence; Lottenberg, Richard; Feezor, Robert J; Armen, Scott B; Liu, Huazhi; Efron, Philip A; Crowther, Mark; Ang, Darwin
2011-08-01
Placement of prophylactic inferior vena cava filters (pIVCFs) for the prevention of pulmonary embolism (PE) in high-risk trauma patients (HRTPs) are widely practiced despite the lack of Level I data supporting this use. We report the 2-year interim analysis of the Filters in Trauma pilot study. This is a single institution, prospective randomized controlled pilot feasibility study in a Level I trauma center. HRTPs were identified for pIVCF placement by the Eastern Association for the Surgery of Trauma guidelines. From November 2008 to November 2010, HRTPs were enrolled and randomized to either pIVCF or no pIVCF. All patients received pharmacologic prophylaxis when safe. Primary outcomes included feasibility objectives and secondary outcomes were incidence of PE, deep vein thrombosis (DVT), and death. Thirty-four of 38 enrolled patients were eligible for analysis. The baseline sociodemographic characteristics were balanced between the both groups. Results of the feasibility objectives included: time from admission to enrollment (mean, 47.4 hours ± 22.0 hours), time from enrollment to randomization (mean, 4.8 hours ± 9.1 hours), time from randomization to IVCF placement (mean, 16.9 hours ± 9.2 hours), adherence to weekly compression ultrasound within first month (IVCF group = 44.4%; non-IVCF group = 62.5%), and 1-month clinical follow-up (IVCF group = 83.3%; non-IVCF group = 100%). At 6-month follow-up, one PE in the nonfilter group and one DVT in the filter group had occurred. One non-PE-related death occurred in the filter group. Barriers to enrollment included inability to obtain informed consent due to patient refusal or no next of kin identified and delayed notification of eligibility status. Our pilot study demonstrates for the first time that a randomized controlled trial evaluating the efficacy of pIVCFs in trauma patients is feasible. This pilot data will be used to inform the design of a multicenter randomized controlled trial to determine the incidence
Clasen, Thomas; Garcia Parra, Gloria; Boisson, Sophie; Collin, Simon
2005-10-01
Household water treatment is increasingly recognized as an effective means of reducing the burden of diarrheal disease among low-income populations without access to safe water. Oxfam GB undertook a pilot project to explore the use of household-based ceramic water filters in three remote communities in Colombia. In a randomized, controlled trial over a period of six months, the filters were associated with a 75.3% reduction in arithmetic mean thermotolerant coliforms (TTCs) (P Health Organization limits for low risk (1-10 TTCs/100 mL), respectively, compared with 0.9% and 7.3% for control group samples. Overall, prevalence of diarrhea was 60% less among households using filters than among control households (odds ratio = 0.40, 95% confidence interval = 0.25, 0.63, P < 0.0001). However, the microbiologic performance and protective effect of the filters was not uniform throughout the study communities, suggesting the need to consider the circumstances of the particular setting before implementing this intervention.
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
Hong, Jiasheng; Medina, Francisco; Martiacuten, Ferran
2018-01-01
This book presents and discusses strategies for the design and implementation of common-mode suppressed balanced microwave filters, including, narrowband, wideband, and ultra-wideband filters This book examines differential-mode, or balanced, microwave filters by discussing several implementations of practical realizations of these passive components. Topics covered include selective mode suppression, designs based on distributed and semi-lumped approaches, multilayer technologies, defect ground structures, coupled resonators, metamaterials, interference techniques, and substrate integrated waveguides, among others. Divided into five parts, Balanced Microwave Filters begins with an introduction that presents the fundamentals of balanced lines, circuits, and networks. Part 2 covers balanced transmission lines with common-mode noise suppression, including several types of common-mode filters and the application of such filters to enhance common-mode suppression in balanced bandpass filters. Next, Part 3 exa...
Institute of Scientific and Technical Information of China (English)
孙会敏; 庄纯清; 许胜中
2015-01-01
To address the satellite autonomous celestial navigation system based-on star sensor/optical camera, traditional square-root unscented Kalman filter can not well solve the nonlinear filtering problem with colored noise, which leads to the navigation system accuracy decreased. So a square-root unscented Kalman filter (CSRUKF) applied to measurement system with colored noise is proposed in this paper. In addition, in order to avoid destructing the positive and symmetry of covariance matrix caused by the errors of numerical calculation during the filtering procedure, the square-root of covariance matrix is adopted throughout recursive calculation, which improves the stability of filter. The square-root of covariance matrix update is calculated by cholesky decomposition and qr decomposition. The method was applied to satellite autonomous navigation systems. The simulation results show that, compared to traditional SRUKF, this proposed SRUKF can well solve the problem of poor estimation accuracy in measurement system with colored noise.%针对由星敏感器和光学导航相机组成的卫星天文自主导航系统, 传统的平方根 UKF 不能很好地解决测量噪声为有色噪声情况下的非线性滤波问题, 导致导航系统的精度下降. 为此, 提出了一种有色噪声情况下的平方根 UKF 方法. 同时, 为了避免在数值计算的过程中, 由于舍入误差而破坏误差协方差矩阵的正定性和对称性,在整个递推计算过程中, 借鉴平方根 Kalman 滤波理论, 采用协方差矩阵平方根进行递推计算, 改善滤波算法的稳定性, 协方差矩阵的平方根更新用cholesky分解和qr分解来计算. 将该方法应用于卫星天文自主导航系统中,实验仿真结果表明, 相对于传统的平方根UKF算法, 所设计的平方根UKF算法能够很好地解决测量噪声为有色噪声情况下估计精度低问题.
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.
Vilar, J. M. G. (José M. G.), 1972-; 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.
Morris, Jamae Fontain; Murphy, Jennifer; Fagerli, Kirsten; Schneeberger, Chandra; Jaron, Peter; Moke, Fenny; Juma, Jane; Ochieng, J Ben; Omore, Richard; Roellig, Dawn; Xiao, Lihua; Priest, Jeffrey W; Narayanan, Jothikumar; Montgomery, Joel; Hill, Vince; Mintz, Eric; Ayers, Tracy L; O'Reilly, Ciara E
2018-04-02
Cryptosporidium is a leading cause of diarrhea among Kenyan infants. Ceramic water filters (CWFs) are used for household water treatment. We assessed the impact of CWFs on diarrhea, cryptosporidiosis prevention, and water quality in rural western Kenya. A randomized, controlled intervention trial was conducted in 240 households with infants 4-10 months old. Twenty-six weekly household surveys assessed infant diarrhea and health facility visits. Stool specimens from infants with diarrhea were examined for Cryptosporidium . Source water, filtered water, and filter retentate were tested for Cryptosporidium and/or microbial indicators. To estimate the effect of CWFs on health outcomes, logistic regression models using generalized estimating equations were performed; odds ratios (ORs) and 95% confidence intervals (CIs) are reported. Households reported using surface water (36%), public taps (29%), or rainwater (17%) as their primary drinking water sources, with no differences in treatment groups. Intervention households reported less diarrhea (7.6% versus 8.9%; OR: 0.86 [0.64-1.16]) and significantly fewer health facility visits for diarrhea (1.0% versus 1.9%; OR: 0.50 [0.30-0.83]). In total, 15% of intervention and 12% of control stools yielded Cryptosporidium ( P = 0.26). Escherichia coli was detected in 93% of source water samples; 71% of filtered water samples met World Health Organization recommendations of filter rinses following passage of large volumes of source water. Water quality was improved among CWF users; however, the short study duration and small sample size limited our ability to observe reductions in cryptosporidiosis.
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.
Variable Span Filters for Speech Enhancement
DEFF Research Database (Denmark)
Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll
2016-01-01
In this work, we consider enhancement of multichannel speech recordings. Linear filtering and subspace approaches have been considered previously for solving the problem. The current linear filtering methods, although many variants exist, have limited control of noise reduction and speech...
Nagel, Corey L; Kirby, Miles A; Zambrano, Laura D; Rosa, Ghislane; Barstow, Christina K; Thomas, Evan A; Clasen, Thomas F
2016-12-15
In Rwanda, pneumonia and diarrhea are the first and second leading causes of death, respectively, among children under five. Household air pollution (HAP) resultant from cooking indoors with biomass fuels on traditional stoves is a significant risk factor for pneumonia, while consumption of contaminated drinking water is a primary cause of diarrheal disease. To date, there have been no large-scale effectiveness trials of programmatic efforts to provide either improved cookstoves or household water filters at scale in a low-income country. In this paper we describe the design of a cluster-randomized trial to evaluate the impact of a national-level program to distribute and promote the use of improved cookstoves and advanced water filters to the poorest quarter of households in Rwanda. We randomly allocated 72 sectors (administratively defined units) in Western Province to the intervention, with the remaining 24 sectors in the province serving as controls. In the intervention sectors, roughly 100,000 households received improved cookstoves and household water filters through a government-sponsored program targeting the poorest quarter of households nationally. The primary outcome measures are the incidence of acute respiratory infection (ARI) and diarrhea among children under five years of age. Over a one-year surveillance period, all cases of acute respiratory infection (ARI) and diarrhea identified by health workers in the study area will be extracted from records maintained at health facilities and by community health workers (CHW). In addition, we are conducting intensive, longitudinal data collection among a random sample of households in the study area for in-depth assessment of coverage, use, environmental exposures, and additional health measures. Although previous research has examined the impact of providing household water treatment and improved cookstoves on child health, there have been no studies of national-level programs to deliver these interventions
Stochastic filtering of quantitative data from STR DNA analysis
DEFF Research Database (Denmark)
Tvedebrink, Torben; Eriksen, Poul Svante; Mogensen, Helle Smidt
due to the apparatus used for measurements). Pull-up effects (more systematic increase caused by overlap in the spectrum) Stutters (peaks located four basepairs before the true peak). We present filtering techniques for all three technical artifacts based on statistical analysis of data from......The quantitative data observed from analysing STR DNA is a mixture of contributions from various sources. Apart from the true allelic peaks, the observed signal consists of at least three components resulting from the measurement technique and the PCR amplification: Background noise (random noise...... controlled experiments conducted at The Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health Sciences, Universityof Copenhagen, Denmark....
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...
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.
Quantized dissipation and random telegraph voltage noise in epitaxial BiSrCaCuO thin films
International Nuclear Information System (INIS)
Jung, G.; Savo, B.; Vecchione, A.
1993-01-01
In this paper we report on the observation of correlated multiple-voltage RTN switching in high quality epitaxial BiSrCaCuO thin film. We ascribe the correlated noise to the quantization of flux flow dissipation in the film. (orig.)
Fristedt, B; Krylov, N
2007-01-01
Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the errors and extracting from the observations the most precise information about the object, which itself may or may not be moving in a somewhat random fashion. Next comes the prediction step where, using information about the past behavior of the object, one tries to predict its future path. The first three chapters of the book deal with discrete probability spaces, random variables, conditioning, Markov chains, and filtering of discrete Markov chains. The next three chapters deal with the more sophisticated notions of conditioning in nondiscrete situations, filtering of continuous-space Markov chains, and of Wiener process. Filtering and prediction of stationary sequences is discussed in the last two chapters. The authors believe that they have succeeded in presenting necessary ideas in an elementary manner without sacrificing the rigor too much. Such rig...
Yousefi-Nooraie, Reza; Irani, Shirin; Mortaz-Hedjri, Soroush; Shakiba, Behnam
2013-10-01
The aim of this study was to compare the performance of three search methods in the retrieval of relevant clinical trials from PubMed to answer specific clinical questions. Included studies of a sample of 100 Cochrane reviews which recorded in PubMed were considered as the reference standard. The search queries were formulated based on the systematic review titles. Precision, recall and number of retrieved records for limiting the results to clinical trial publication type, and using sensitive and specific clinical queries filters were compared. The number of keywords, presence of specific names of intervention and syndrome in the search keywords were used in a model to predict the recalls and precisions. The Clinical queries-sensitive search strategy retrieved the largest number of records (33) and had the highest recall (41.6%) and lowest precision (4.8%). The presence of specific intervention name was the only significant predictor of all recalls and precisions (P = 0.016). The recall and precision of combination of simple clinical search queries and methodological search filters to find clinical trials in various subjects were considerably low. The limit field strategy yielded in higher precision and fewer retrieved records and approximately similar recall, compared with the clinical queries-sensitive strategy. Presence of specific intervention name in the search keywords increased both recall and precision. © 2010 John Wiley & Sons Ltd.
International Nuclear Information System (INIS)
Ahmed, A.; Barfeh, M.A.G.
2001-01-01
In air-conditioning system the noise generated by supply fan is carried by conditioned air through the ductwork. The noise created in ductwork run may be transmission, regenerative and ductborne. Transmission noise is fan noise, regenerative noise is due to turbulence in flow and ductborne noise is the noise radiating from duct to surroundings. Some noise is attenuated in ducts also but if noise level is high then it needs to be attenuated. A simple mitre bend can attenuate-noise. This principle is extended to V and M-shape ducts with inside lining of fibreglass, which gave maximum attenuation of 77 dB and 62 dB respectively corresponding to 8 kHz frequency as compared to mitre, bend giving maximum 18 dB attenuation. Sound level meter measured sound levels with octave band filter and tests were conducted in anechoic room. A V-shape attenuator can be used at fan outlet and high frequency noise can be minimized greatly. (author)
Filtering of SPECT reconstructions made using Bellini's attenuation correction method
International Nuclear Information System (INIS)
Glick, S.J.; Penney, B.C.; King, M.A.
1991-01-01
This paper evaluates a three-dimensional (3D) Wiener filter which is used to restore SPECT reconstructions which were made using Bellini's method of attenuation correction. Its performance is compared to that of several pre-reconstruction filers: the one-dimensional (1D) Butterworth, the two-dimensional (2D) Butterworth, and a 2D Wiener filer. A simulation study is used to compare the four filtering methods. An approximation to a clinical liver spleen study was used as the source distribution and algorithm which accounts for the depth and distance dependent blurring in SPECT was used to compute noise free projections. To study the effect of filtering method on tumor detection accuracy, a 2 cm diameter, cool spherical tumor (40% contrast) was placed at a known, but random, location with the liver. Projection sets for ten tumor locations were computed and five noise realizations of each set were obtained by introducing Poisson noise. The simulated projections were either: filtered with the 1D or 2D Butterworth or the 2D Wiener and then reconstructed using Bellini's intrinsic attenuation correction, or reconstructed first, then filtered with the 3D Wiener. The criteria used for comparison were: normalized mean square error (NMSE), cold spot contrast, and accuracy of tumor detection with an automated numerical method. Results indicate that restorations obtained with 3D Wiener filtering yielded significantly higher lesion contrast and lower NMSE values compared to the other methods of processing. The Wiener restoration filters and the 2D Butterworth all provided similar measures of detectability, which were noticeably higher than that obtained with 1D Butterworth smoothing
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.
Large window median filtering on Clip7
Energy Technology Data Exchange (ETDEWEB)
Mathews, K N
1983-07-01
Median filtering has been found to be a useful operation to perform on images in order to reduce random noise while preserving edges of objects. However, in some cases, as the resolution of the image increases, so too does the required window size of the filter. For parallel array processors, this leads to problems when dealing with the large amount of data involved. That is to say that there tend to be problems over slow access of data from pixels over a large neighbourhood, lack of available storage of this data during the operation and long computational times for finding the median. An algorithm for finding the median, designed for use on byte wide architecture parallel array processors is presented together with its implementation on Clip7, a scanning array of such processors. 6 references.
Fabiszewski de Aceituno, Anna M.; Stauber, Christine E.; Walters, Adam R.; Meza Sanchez, Rony E.; Sobsey, Mark D.
2012-01-01
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. PMID:22665593
Energy Technology Data Exchange (ETDEWEB)
Benda, J [Commissariat a l' Energie Atomique, 91 - Saclay (France). Centre d' Etudes Nucleaires
1967-05-01
The purpose of nuclear spectrometry is the precise measurement of particles energy. The resolving power of a spectrometer design is an important factor. Two main phenomena are involved in the limitation of this resolving power: The statistical fluctuations of the detector itself, and the background noise. For a given noise, the theory of filters enables the calculation of networks specially designed for the improvement of signal to noise ratio. The proposed system should lead to an improvement of 10.5 per cent of this ratio. Experiments have confirmed this theoretical estimation. The predictor device also makes possible the obtaining of shortened pulses. (author) [French] Les mesures en spectrometrie nucleaire ont pour but la determination precise de l'energie des particules. Le pouvoir de resolution d'une chaine de spectrometrie est une caracteristique importante. Deux phenomenes principaux concourent a limiter ce pouvoir de resolution: les fluctuations statistiques du detecteur et le bruit de fond. Pour un bruit de fond donne, la theorie des filtres permet de calculer des reseaux susceptibles de modifier le rapport signal sur bruit. Le systeme propose permet d'ameliorer de 10.5 pour cent ce rapport lorsqu'on se place dans les conditions optimales. Les resultats experimentaux confirment les previsions. Le dispositif predicteur permet aussi un raccourcissement de l'impulsion dans le temps. (auteur)
Chopped filter for nuclear spectroscopy
International Nuclear Information System (INIS)
Koyama, J.
1980-12-01
Some of the theoretical and practical factors affecting the energy resolution of a spectrometry system are considered, specially those related to t he signal-to-noise ratio, and a time-variant filter with the transfer function of the theoretical optimum filter, during its active time, is proposed. A prototype has been tested and experimental results are presented. (Author) [pt
Visibility of wavelet quantization noise
Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.
1997-01-01
The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Independent component analysis based filtering for penumbral imaging
International Nuclear Information System (INIS)
Chen Yenwei; Han Xianhua; Nozaki, Shinya
2004-01-01
We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters
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.
Design of a flat-top fiber Bragg filter via quasi-random modulation of the refractive index.
Derevyanko, Stanislav
2008-10-15
The statistics of the reflection spectrum of a short-correlated disordered fiber Bragg grating are studied. The averaged spectrum appears to be flat inside the bandgap and has significantly suppressed sidelobes compared to the uniform grating of the same bandwidth. This is due to the Anderson localization of the modes of a disordered grating. This observation prompts a new algorithm for designing passband reflection gratings. Using the stochastic invariant imbedding approach it is possible to obtain the probability distribution function for the random reflection coefficient inside the bandgap and obtain both the variance of the averaged reflectivity as well as the distribution of the time delay of the grating.
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.
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.
Correlation of Spatially Filtered Dynamic Speckles in Distance Measurement Application
International Nuclear Information System (INIS)
Semenov, Dmitry V.; Nippolainen, Ervin; Kamshilin, Alexei A.; Miridonov, Serguei V.
2008-01-01
In this paper statistical properties of spatially filtered dynamic speckles are considered. This phenomenon was not sufficiently studied yet while spatial filtering is an important instrument for speckles velocity measurements. In case of spatial filtering speckle velocity information is derived from the modulation frequency of filtered light power which is measured by photodetector. Typical photodetector output is represented by a narrow-band random noise signal which includes non-informative intervals. Therefore more or less precious frequency measurement requires averaging. In its turn averaging implies uncorrelated samples. However, conducting research we found that correlation is typical property not only of dynamic speckle patterns but also of spatially filtered speckles. Using spatial filtering the correlation is observed as a response of measurements provided to the same part of the object surface or in case of simultaneously using several adjacent photodetectors. Found correlations can not be explained using just properties of unfiltered dynamic speckles. As we demonstrate the subject of this paper is important not only from pure theoretical point but also from the point of applied speckle metrology. E.g. using single spatial filter and an array of photodetector can greatly improve accuracy of speckle velocity measurements
Approximations to camera sensor noise
Jin, Xiaodan; Hirakawa, Keigo
2013-02-01
Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.
Zhang, Hua; Yang, Hui; Li, Hongxing; Huang, Guangnan; Ding, Zheyi
2018-04-01
The attenuation of random noise is important for improving the signal to noise ratio (SNR). However, the precondition for most conventional denoising methods is that the noisy data must be sampled on a uniform grid, making the conventional methods unsuitable for non-uniformly sampled data. In this paper, a denoising method capable of regularizing the noisy data from a non-uniform grid to a specified uniform grid is proposed. Firstly, the denoising method is performed for every time slice extracted from the 3D noisy data along the source and receiver directions, then the 2D non-equispaced fast Fourier transform (NFFT) is introduced in the conventional fast discrete curvelet transform (FDCT). The non-equispaced fast discrete curvelet transform (NFDCT) can be achieved based on the regularized inversion of an operator that links the uniformly sampled curvelet coefficients to the non-uniformly sampled noisy data. The uniform curvelet coefficients can be calculated by using the inversion algorithm of the spectral projected-gradient for ℓ1-norm problems. Then local threshold factors are chosen for the uniform curvelet coefficients for each decomposition scale, and effective curvelet coefficients are obtained respectively for each scale. Finally, the conventional inverse FDCT is applied to the effective curvelet coefficients. This completes the proposed 3D denoising method using the non-equispaced curvelet transform in the source-receiver domain. The examples for synthetic data and real data reveal the effectiveness of the proposed approach in applications to noise attenuation for non-uniformly sampled data compared with the conventional FDCT method and wavelet transformation.
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
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
Perspectives on Nonlinear Filtering
Law, Kody
2015-01-01
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).
Perspectives on Nonlinear Filtering
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).
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...
Signal enhancement with variable span linear filters
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 ...
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)
Page, Ralph H.; Doty, Patrick F.
2017-08-01
The various technologies presented herein relate to a tiled filter array that can be used in connection with performance of spatial sampling of optical signals. The filter array comprises filter tiles, wherein a first plurality of filter tiles are formed from a first material, the first material being configured such that only photons having wavelengths in a first wavelength band pass therethrough. A second plurality of filter tiles is formed from a second material, the second material being configured such that only photons having wavelengths in a second wavelength band pass therethrough. The first plurality of filter tiles and the second plurality of filter tiles can be interspersed to form the filter array comprising an alternating arrangement of first filter tiles and second filter tiles.
A Stochastic Approach to Noise Modeling for Barometric Altimeters
Directory of Open Access Journals (Sweden)
Angelo Maria Sabatini
2013-11-01
Full Text Available The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes, we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component. M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.
Noise generator for tinnitus treatment based on look-up tables
Uriz, Alejandro J.; Agüero, Pablo; Tulli, Juan C.; Castiñeira Moreira, Jorge; González, Esteban; Hidalgo, Roberto; Casadei, Manuel
2016-04-01
Treatment of tinnitus by means of masking sounds allows to obtain a significant improve of the quality of life of the individual that suffer that condition. In view of that, it is possible to develop noise synthesizers based on random number generators in digital signal processors (DSP), which are used in almost any digital hearing aid devices. DSP architecture have limitations to implement a pseudo random number generator, due to it, the noise statistics can be not as good as expectations. In this paper, a technique to generate additive white gaussian noise (AWGN) or other types of filtered noise using coefficients stored in program memory of the DSP is proposed. Also, an implementation of the technique is carried out on a dsPIC from Microchip®. Objective experiments and experimental measurements are performed to analyze the proposed technique.
Naseri, H; Homaeinezhad, M R; Pourkhajeh, H
2013-09-01
The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments. Copyright © 2013 Elsevier Ltd. All rights reserved.
Alexander fractional differential window filter for ECG denoising.
Verma, Atul Kumar; Saini, Indu; Saini, Barjinder Singh
2018-06-01
The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AFDW) filter is proposed for ECG signal denoising. The designed filter is based on the concept of generalized Alexander polynomial and the R-L differential equation of fractional calculus. This concept is utilized to formulate a window that acts as a forward filter. Thereafter, the backward filter is constructed by reversing the coefficients of the forward filter. The proposed AFDW filter is then obtained by averaging of the forward and backward filter coefficients. The performance of the designed AFDW filter is validated by adding the various type of noise to the original ECG signal obtained from MIT-BIH arrhythmia database. The two non-diagnostic measure, i.e., SNR, MSE, and one diagnostic measure, i.e., wavelet energy based diagnostic distortion (WEDD) have been employed for the quantitative evaluation of the designed filter. Extensive experimentations on all the 48-records of MIT-BIH arrhythmia database resulted in average SNR of 22.014 ± 3.806365, 14.703 ± 3.790275, 13.3183 ± 3.748230; average MSE of 0.001458 ± 0.00028, 0.0078 ± 0.000319, 0.01061 ± 0.000472; and average WEDD value of 0.020169 ± 0.01306, 0.1207 ± 0.061272, 0.1432 ± 0.073588, for ECG signal contaminated by the power line, random, and the white Gaussian noise respectively. A new metric named as morphological power preservation measure (MPPM) is also proposed that account for the power preservance (as indicated by PSD plots) and the QRS morphology. The proposed AFDW filter retained much of the original (clean) signal power without any significant morphological distortion as validated by MPPM measure that were 0
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.
Noise simulation in cone beam CT imaging with parallel computing
International Nuclear Information System (INIS)
Tu, S.-J.; Shaw, Chris C; Chen, Lingyun
2006-01-01
We developed a computer noise simulation model for cone beam computed tomography imaging using a general purpose PC cluster. This model uses a mono-energetic x-ray approximation and allows us to investigate three primary performance components, specifically quantum noise, detector blurring and additive system noise. A parallel random number generator based on the Weyl sequence was implemented in the noise simulation and a visualization technique was accordingly developed to validate the quality of the parallel random number generator. In our computer simulation model, three-dimensional (3D) phantoms were mathematically modelled and used to create 450 analytical projections, which were then sampled into digital image data. Quantum noise was simulated and added to the analytical projection image data, which were then filtered to incorporate flat panel detector blurring. Additive system noise was generated and added to form the final projection images. The Feldkamp algorithm was implemented and used to reconstruct the 3D images of the phantoms. A 24 dual-Xeon PC cluster was used to compute the projections and reconstructed images in parallel with each CPU processing 10 projection views for a total of 450 views. Based on this computer simulation system, simulated cone beam CT images were generated for various phantoms and technique settings. Noise power spectra for the flat panel x-ray detector and reconstructed images were then computed to characterize the noise properties. As an example among the potential applications of our noise simulation model, we showed that images of low contrast objects can be produced and used for image quality evaluation
Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA.
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.
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.
The Signal Importance of Noise
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…
Filtering and deconvolution for bioluminescence imaging of small animals
International Nuclear Information System (INIS)
Akkoul, S.
2010-01-01
This thesis is devoted to analysis of bioluminescence images applied to the small animal. This kind of imaging modality is used in cancerology studies. Nevertheless, some problems are related to the diffusion and the absorption of the tissues of the light of internal bioluminescent sources. In addition, system noise and the cosmic rays noise are present. This influences the quality of the images and makes it difficult to analyze. The purpose of this thesis is to overcome these disturbing effects. We first have proposed an image formation model for the bioluminescence images. The processing chain is constituted by a filtering stage followed by a deconvolution stage. We have proposed a new median filter to suppress the random value impulsive noise which corrupts the acquired images; this filter represents the first block of the proposed chain. For the deconvolution stage, we have performed a comparative study of various deconvolution algorithms. It allowed us to choose a blind deconvolution algorithm initialized with the estimated point spread function of the acquisition system. At first, we have validated our global approach by comparing our obtained results with the ground truth. Through various clinical tests, we have shown that the processing chain allows a significant improvement of the spatial resolution and a better distinction of very close tumor sources, what represents considerable contribution for the users of bioluminescence images. (author)
Noise estimation for remote sensing image data analysis
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.
Does the central limit theorem always apply to phase noise? Some implications for radar problems
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.
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...
Cascaded analysis of signal and noise propagation through a heterogeneous breast model
International Nuclear Information System (INIS)
Mainprize, James G.; Yaffe, Martin J.
2010-01-01
Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.
International Nuclear Information System (INIS)
Arnal, R.S.; Martin, G.V.; Gonzalez, J.L.M.-C.
1988-01-01
This paper studies the local vibrations of reactor components driven by Gaussian coloured and white forces, when nonlinear vibrations arise. We study also the important problem of noise sources, modelization and the noise propagation through the neutron field using the discrete ordinates transport theory. Finally, we study the effect of the neutron field upon the PSD (power spectral density) of the noise source and we analyse the problem of fitting neutron noise experimental data to perform pattern recognition analysis. (author)
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.
Design and construction of electronic filters
International Nuclear Information System (INIS)
Becerril Z, E.R.; Moreno P, C.; Salinas B, E.
1979-01-01
The design and construction of very low frequencies electronic filters which will be used for carrying out analysis of pile noise at Mexico's Nuclear Center Triga Mark III Reactor, in order to realize measurements of its parameters is presented. NIM norms and active filters with lineal integrated circuits were used: a. Band pass filter from 10 to 500 hertz, band width 50. b. Low pass filter from 0.001 to 10 hertz in 3 steps. c. Kalman Bucy filter, an analogical simulation of this filter was undertaken, obtained from a mathematical model of a Zero power experimental reactor, with the purpose to establish a control searching. (author)
Directory of Open Access Journals (Sweden)
Y. A. Bladyko
2010-01-01
Full Text Available The paper contains definition of a smoothing factor which is suitable for any rectifier filter. The formulae of complex smoothing factors have been developed for simple and complex passive filters. The paper shows conditions for application of calculation formulae and filters.
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.
A Method of Reducing Random Drift in the Combined Signal of an Array of Inertial Sensors
2015-09-30
stability of the collective output, Bayard et al, US Patent 6,882,964. The prior art methods rely upon the use of Kalman filtering and averaging...including scale-factor errors, quantization effects, temperature effects, random drift, and additive noise. A comprehensive account of all of these
Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M
2007-01-01
Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampal CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampal CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance.
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...... 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....
Partial removal of correlated noise in thermal imagery
International Nuclear Information System (INIS)
Borel, C.C.; Cooke, B.J.; Laubscher, B.E.
1996-01-01
Correlated noise occurs in many imaging systems such as scanners and push-broom imagers. The sources of correlated noise can be from the detectors, pre-amplifiers and sampling circuits. Correlated noise appears as streaking along the scan direction of a scanner or in the along track direction of a push-broom imager. We have developed algorithms to simulate correlated noise and pre-filter to reduce the amount of streaking while not destroying the scene content. The pre- filter in the Fourier domain consists of the product of two filters. One filter models the correlated noise spectrum, the other is a windowing function e.g. Gaussian or Hanning window with variable width to block high frequency noise away from the origin of the Fourier Transform of the image data. We have optimized the filter parameters for various scenes and find improvements of the RMS error of the original minus the pre-filtered noisy image
Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil
2011-01-01
Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.
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.
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.
Design and application of finite impulse response digital filters
International Nuclear Information System (INIS)
Miller, T.R.; Sampathkumaran, K.S.
1982-01-01
The finite impulse response (FIR) digital filter is a spatial domain filter with a frequency domain representation. The theory of the FIR filter is presented and techniques are described for designing FIR filters with known frequency response characteristics. Rational design principles are emphasized based on characterization of the imaging system using the modulation transfer function and physical properties of the imaged objects. Bandpass, Wiener, and low-pass filters were designed and applied to 201 Tl myocardial images. The bandpass filter eliminates low-frequency image components that represent background activity and high-frequency components due to noise. The Wiener, or minimum mean square error filter 'sharpens' the image while also reducing noise. The Wiener filter illustrates the power of the FIR technique to design filters with any desired frequency reponse. The low-pass filter, while of relative limited use, is presented to compare it with a popular elementary 'smoothing' filter. (orig.)
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.
International Nuclear Information System (INIS)
Spagnolo, B.; Agudov, N.V.; Dubkov, A.A.
2004-01-01
The noise can stabilize a fluctuating or a periodically driven metastable state in such a way that the system remains in this state for a longer time than in the absence of white noise. This is the noise enhanced stability phenomenon, observed experimentally and numerically in different physical systems. After shortly reviewing all the physical systems where the phenomenon was observed, the theoretical approaches used to explain the effect are presented. Specifically the conditions to observe the effect in systems: (a) with periodical driving force, and (b) with random dichotomous driving force, are discussed. In case (b) we review the analytical results concerning the mean first passage time and the nonlinear relaxation time as a function of the white noise intensity, the parameters of the potential barrier, and of the dichotomous noise. (author)
Active microphonic noise cancellation in radiation detectors
International Nuclear Information System (INIS)
Zimmermann, Sergio
2013-01-01
A new adaptive filtering technique to reduce microphonic noise in radiation detectors is presented. The technique is based on system identification that actively cancels the microphonic noise. A sensor is used to measures mechanical disturbances that cause vibration on the detector assembly, and the digital adaptive filtering estimates the impact of these disturbances on the microphonic noise. The noise then can be subtracted from the actual detector measurement. In this paper the technique is presented and simulations are used to support this approach. -- Highlights: •A sensor is used to measures mechanical disturbances that cause vibration on the detector assembly. •Digital adaptive filtering estimates the impact of these disturbances on the microphonic noise. •The noise is then subtracted from the actual detector measurement. •We use simulations to demonstrate the performance of this approach. •After cancellation, we recover most of the original energy resolution
Noise sensitivity of portfolio selection in constant conditional correlation GARCH models
Varga-Haszonits, I.; Kondor, I.
2007-11-01
This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.
Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior
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.
Optimization of Butterworth filter for brain SPECT imaging
International Nuclear Information System (INIS)
Minoshima, Satoshi; Maruno, Hirotaka; Yui, Nobuharu
1993-01-01
A method has been described to optimize the cutoff frequency of the Butterworth filter for brain SPECT imaging. Since a computer simulation study has demonstrated that separation between an object signal and the random noise in projection images in a spatial-frequency domain is influenced by the total number of counts, the cutoff frequency of the Butterworth filter should be optimized for individual subjects according to total counts in a study. To reveal the relationship between the optimal cutoff frequencies and total counts in brain SPECT study, we used a normal volunteer and 99m Tc hexamethyl-propyleneamine oxime (HMPAO) to obtain projection sets with different total counts. High quality images were created from a projection set with an acquisition time of 300-seconds per projection. The filter was optimized by calculating mean square errors from high quality images visually inspecting filtered reconstructed images. Dependence between total counts and optimal cutoff frequencies was clearly demonstrated in a nomogram. Using this nomogram, the optimal cutoff frequency for each study can be estimated from total counts, maximizing visual image quality. The results suggest that the cutoff frequency of Butterworth filter should be determined by referring to total counts in each study. (author)
Tungsten anode tubes with K-edge filters for mammography
Energy Technology Data Exchange (ETDEWEB)
Beaman, S.; Lillicrap, S.C. (Wessex Regional Medical Physics Service, Bath (UK)); Price, J.L. (Jarvis Screening Centre, Guildford (UK))
1983-10-01
Optimum X-ray energies for mammography have previously been calculated using the maximum signal to noise ratio (SNR) per unit dose to the breast, or the minimum exposure for constant SNR. Filters having absorption edges at appropriate energy positions have been used to modify the shape of tungsten anode spectra towards the calculated optimum. The suitability of such spectra for practical use has been assessed by comparing the film image quality and the incident breast dose obtained using a K-edge filtered tungsten anode tube with that obtained using a molybdenum anode. Image quality has been assessed by using a 'random' phantom and by comparing mammograms where one breast was radiographed using a filtered tungsten anode tube and the other using a standard molybdenum anode unit. Relative breast doses were estimated from both ionisation chamber measurements with a phantom and thermoluminescent dosimetry measurements on the breast. Film image quality assessment indicated that the filtered tungsten anode tube gave results not significantly different from those obtained with a molybdenum anode tube for a tissue thickness of about 4 cm and which were better for larger breast thicknesses. Doses could be reduced to between one-half and one-third with the filtered tungsten anode tube.
Tungsten anode tubes with K-edge filters for mammography
International Nuclear Information System (INIS)
Beaman, S.; Lillicrap, S.C.; Price, J.L.
1983-01-01
Optimum X-ray energies for mammography have previously been calculated using the maximum signal to noise ratio (SNR) per unit dose to the breast, or the minimum exposure for constant SNR. Filters having absorption edges at appropriate energy positions have been used to modify the shape of tungsten anode spectra towards the calculated optimum. The suitability of such spectra for practical use has been assessed by comparing the film image quality and the incident breast dose obtained using a K-edge filtered tungsten anode tube with that obtained using a molybdenum anode. Image quality has been assessed by using a 'random' phantom and by comparing mammograms where one breast was radiographed using a filtered tungsten anode tube and the other using a standard molybdenum anode unit. Relative breast doses were estimated from both ionisation chamber measurements with a phantom and thermoluminescent dosimetry measurements on the breast. Film image quality assessment indicated that the filtered tungsten anode tube gave results not significantly different from those obtained with a molybdenum anode tube for a tissue thickness of abut 4 cm and which were better for larger breast thicknesses. Doses could be reduced to between one-half and one-third with the filtered tungsten anode tube. (U.K.)
On the optimum area-balanced filters for nuclear spectroscopy
International Nuclear Information System (INIS)
Ripamonti, G.; Pullia, A.
1996-01-01
The minimum noise area-balanced (A-B) filters for nuclear spectroscopy are disentangled in the sum of two optimized individual filters. The former is the unipolar finite cusp filter, used for pulse amplitude estimation but affected by baseline shift errors, the latter is a specific filter used for baseline estimation. Each of them is optimized so as to give the minimum noise in the estimation of the pulse amplitude or of its baseline level. It is shown that double optimisation produces an overall optimum filter exhibiting a total noise V 2 n equal to the sum of the noises V 2 n1 and V 2 n2 exhibited by each filter individually. This is a consequence of the orthogonality of the individual filter weight-functions in a function space where the norm is defined as √(V 2 n ). (orig.)
Adaptive Noise Canceling Menggunakan Algoritma Least Mean Square (Lms)
Nardiana, Anita; Sumaryono, Sari Sujoko
2011-01-01
Noise is inevitable in communication system. In some cases, noise can disturb signal. It is veryannoying as the received signal is jumbled with the noise itself. To reduce or remove noise, filter lowpass,highpass or bandpass can solve the problems, but this method cannot reach a maximum standard. One ofthe alternatives to solve the problem is by using adaptive filter. Adaptive algorithm frequently used is LeastMean Square (LMS) Algorithm which is compatible to Finite Impulse Response (FIR). T...
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.
Improving Filtered Backprojection Reconstruction by Data-Dependent Filtering
D.M. Pelt (Daniël); K.J. Batenburg (Joost)
2014-01-01
htmlabstractFiltered backprojection, one of the most widely used reconstruction methods in tomography, requires a large number of low-noise projections to yield accurate reconstructions. In many applications of tomography, complete projection data of high quality cannot be obtained, because of
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.
Seo, Min-Woong; Kawahito, Shoji
2017-12-01
A large full well capacity (FWC) for wide signal detection range and low temporal random noise for high sensitivity lock-in pixel CMOS image sensor (CIS) embedded with two in-pixel storage diodes (SDs) has been developed and presented in this paper. For fast charge transfer from photodiode to SDs, a lateral electric field charge modulator (LEFM) is used for the developed lock-in pixel. As a result, the time-resolved CIS achieves a very large SD-FWC of approximately 7ke-, low temporal random noise of 1.2e-rms at 20 fps with true correlated double sampling operation and fast intrinsic response less than 500 ps at 635 nm. The proposed imager has an effective pixel array of and a pixel size of . The sensor chip is fabricated by Dongbu HiTek 1P4M 0.11 CIS process.
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.
... Regulated by EPA EPA or a designated Federal agency regulates noise sources, such as rail and motor carriers, low noise emission products, construction equipment, transport equipment, trucks, motorcycles, and the labeling of hearing ...
Daróczi, Lajos; Piros, Eszter; Tóth, László Z.; Beke, Dezső L.
2017-07-01
Jerky magnetic and acoustic noises were evoked in a single variant martensitic Ni2MnGa single crystal (produced by uniaxial compression) by application of an external magnetic field along the hard magnetization direction. It is shown that after reaching the detwinning threshold, spontaneous reorientation of martensite variants (twins) leads not only to acoustic emission but magnetic two-directional noises as well. At small magnetic fields, below the above threshold, unidirectional magnetic emission is also observed and attributed to a Barkhausen-type noise due to magnetic domain wall motions during magnetization along the hard direction. After the above first run, in cycles of decreasing and increasing magnetic field, at low-field values, weak, unidirectional Barkhausen noise is detected and attributed to the discontinuous motion of domain walls during magnetization along the easy magnetization direction. The magnetic noise is also measured by constraining the sample in the same initial variant state along the hard direction and, after the unidirectional noise (as obtained also in the first run), a two-directional noise package is developed and it is attributed to domain rotations. From the statistical analysis of the above noises, the critical exponents, characterizing the power-law behavior, are calculated and compared with each other and with the literature data. Time correlations within the magnetic as well as acoustic signals lead to a common scaled power function (with β =-1.25 exponent) for both types of signals.
International Nuclear Information System (INIS)
Butterworth, D.J.
1980-01-01
This invention relates to liquid filters, precoated by replaceable powders, which are used in the production of ultra pure water required for steam generation of electricity. The filter elements are capable of being installed and removed by remote control so that they can be used in nuclear power reactors. (UK)
Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions
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
Bragdon, C. R.
Airport and community land use planning as they relate to airport noise reduction are discussed. Legislation, community relations, and the physiological effect of airport noise are considered. Noise at the Logan, Los Angeles, and Minneapolis/St. Paul airports is discussed.
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; preduced the particulate concentration from 325±31 to 25±6μg/m(3), and was associated with an increase in VO2 (10.4±3.8ml/kg/min; preduce the adverse effects 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.
Gaussian shaping filter for nuclear spectrometry
International Nuclear Information System (INIS)
Menezes, A.S.C. de.
1980-01-01
A theorical study of a gaussian shaping filter, using Pade approximation, for using in gamma spectroscopy is presented. This approximation has proved superior to the classical cascade RC integrators approximation in therms of signal-to-noise ratio and pulse simmetry. An experimental filter was designed, simulated in computer, constructed, and tested in the laboratory. (author) [pt
Filtering microphonics in dark matter germanium experiments
International Nuclear Information System (INIS)
Morales, J.; Garcia, E.; Ortiz de Solorzano, A.; Morales, A.; Nunz-Lagos, R.; Puimedon, J.; Saenz, C.; Villar, J.A.
1992-01-01
A technique for reducing the microphonic noise in a germanium spectrometer used in dark matter particles searches is described. Filtered energy spectra, corresponding to 48.5 kg day of data in a running experiment in the Canfranc tunnel are presented. Improvements of this filtering procedure with respect to the method of rejecting those events not distributed evenly in time are also discussed. (orig.)
Oracle Wiener filtering of a Gaussian signal
Babenko, A.; Belitser, E.
2011-01-01
We study the problem of filtering a Gaussian process whose trajectories, in some sense, have an unknown smoothness ß0 from the white noise of small intensity e. If we knew the parameter ß0, we would use the Wiener filter which has the meaning of oracle. Our goal is now to mimic the oracle, i.e.,
Oracle Wiener filtering of a Gaussian signal
Babenko, A.; Belitser, E.N.
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.,
Improved Kalman Filter-Based Speech Enhancement with Perceptual Post-Filtering
Institute of Scientific and Technical Information of China (English)
WEIJianqiang; DULimin; YANZhaoli; ZENGHui
2004-01-01
In this paper, a Kalman filter-based speech enhancement algorithm with some improvements of previous work is presented. A new technique based on spectral subtraction is used for separation speech and noise characteristics from noisy speech and for the computation of speech and noise Autoregressive (AR) parameters. In order to obtain a Kalman filter output with high audible quality, a perceptual post-filter is placed at the output of the Kalman filter to smooth the enhanced speech spectra.Extensive experiments indicate that this newly proposed method works well.
International Nuclear Information System (INIS)
Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu
2016-01-01
In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.
Institute of Scientific and Technical Information of China (English)
Changyun Liu; Penglang Shui; Gang Wei; Song Li
2014-01-01
To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneu-vers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is pre-sented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter (UKF) via predicted variance Pk|k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneu-vering target compared with the standard UKF.
Human observer detection experiments with mammograms and power-law noise
International Nuclear Information System (INIS)
Burgess, Arthur E.; Jacobson, Francine L.; Judy, Philip F.
2001-01-01
We determined contrast thresholds for lesion detection as a function of lesion size in both mammograms and filtered noise backgrounds with the same average power spectrum, P(f )=B/f 3 . Experiments were done using hybrid images with digital images of tumors added to digitized normal backgrounds, displayed on a monochrome monitor. Four tumors were extracted from digitized specimen radiographs. The lesion sizes were varied by digital rescaling to cover the range from 0.5 to 16 mm. Amplitudes were varied to determine the value required for 92% correct detection in two-alternative forced-choice (2AFC) and 90% for search experiments. Three observers participated, two physicists and a radiologist. The 2AFC mammographic results demonstrated a novel contrast-detail (CD) diagram with threshold amplitudes that increased steadily (with slope of 0.3) with increasing size for lesions larger than 1 mm. The slopes for prewhitening model observers were about 0.4. Human efficiency relative to these models was as high as 90%. The CD diagram slopes for the 2AFC experiments with filtered noise were 0.44 for humans and 0.5 for models. Human efficiency relative to the ideal observer was about 40%. The difference in efficiencies for the two types of backgrounds indicates that breast structure cannot be considered to be pure random noise for 2AFC experiments. Instead, 2AFC human detection with mammographic backgrounds is limited by a combination of noise and deterministic masking effects. The search experiments also gave thresholds that increased with lesion size. However, there was no difference in human results for mammographic and filtered noise backgrounds, suggesting that breast structure can be considered to be pure random noise for this task. Our conclusion is that, in spite of the fact that mammographic backgrounds have nonstationary statistics, models based on statistical decision theory can still be applied successfully to estimate human performance
Dynamic beam filtering for miscentered patients.
Mao, Andrew; Shyr, William; Gang, Grace J; Stayman, J Webster
2018-02-01
Accurate centering of the patient within the bore of a CT scanner takes time and is often difficult to achieve precisely. Patient miscentering can result in significant dose and image noise penalties with the use of traditional bowtie filters. This work describes a system to dynamically position an x-ray beam filter during image acquisition to enable more consistent image performance and potentially lower dose needed for CT imaging. We propose a new approach in which two orthogonal low-dose scout images are used to estimate a parametric model of the object describing its shape, size, and location within the field of view (FOV). This model is then used to compute an optimal filter motion profile by minimizing the variance of the expected detector fluence for each projection. Dynamic filtration was implemented on a cone-beam CT (CBCT) test bench using two different physical filters: 1) an aluminum bowtie and 2) a structured binary filter called a multiple aperture device (MAD). Dynamic filtration performance was compared to a static filter in studies of dose and reconstruction noise as a function of the degree of miscentering of a homogeneous water phantom. Estimated filter trajectories were found to be largely sinusoidal with an amplitude proportional to the amount of miscentering. Dynamic filtration demonstrated an improved ability to keep the spatial distribution of dose and reconstruction noise at baseline levels across varying levels of miscentering, reducing the maximum noise and dose deviation from 53% to 15% and 42% to 14% respectively for the bowtie filter, and 25% to 8% and 24% to 15% respectively for the MAD filter. Dynamic positioning of beam filters during acquisition improves dose utilization and image quality over static filters for miscentered patients. Such dynamic filters relax positioning requirements and have the potential to reduce set-up time and lower dose requirements.
A Novel SFG Structure for C-T Highpass Filters
Nielsen, Ivan Riis
1992-01-01
This paper presents the design of a sixth order elliptic highpass filter having a passband frequency of 3.0KHz, a passband ripple of 1.0dB and a stopband attenuation of 50dB. The filter is based on a novel integrator based SFG describing a passive prototype filter; this SFG is simulated using 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 ...
A quantum extended Kalman filter
International Nuclear Information System (INIS)
Emzir, Muhammad F; Woolley, Matthew J; Petersen, Ian R
2017-01-01
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. (paper)
A quantum extended Kalman filter
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.
Improving the quality of brain CT image from Wavelet filters
International Nuclear Information System (INIS)
Pita Machado, Reinaldo; Perez Diaz, Marlen; Bravo Pino, Rolando
2012-01-01
An algorithm to reduce Poisson noise is described using Wavelet filters. Five tomographic images of patients and a head anthropomorphic phantom were used. They were acquired with two different CT machines. Due to the original images contain the acquisition noise; some simulated free noise lesions were added to the images and after that the whole images were contaminated with noise. Contaminated images were filtered with 9 Wavelet filters at different decomposition levels and thresholds. Image quality of filtered and unfiltered images was graded using the Signal to Noise ratio, Normalized Mean Square Error and the Structural Similarity Index, as well as, by the subjective JAFROC methods with 5 observers. Some filters as Bior 3.7 and dB45 improved in a significant way head CT image quality (p<0.05) producing an increment in SNR without visible structural distortions
Adaptive EMG noise reduction in ECG signals using noise level approximation
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.
International Nuclear Information System (INIS)
Vanin, V.R.
1990-01-01
The multidetector systems for high resolution gamma spectroscopy are presented. The observable parameters for identifying nuclides produced simultaneously in the reaction are analysed discussing the efficiency of filter systems. (M.C.K.)
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.
Reduction method for residual stress of welded joint using random vibration
International Nuclear Information System (INIS)
Aoki, Shigeru; Nishimura, Tadashi; Hiroi, Tetsumaro
2005-01-01
Welded joints are used for construction of many structures. Residual stress is induced near the bead caused by locally given heat. Tensile residual stress on the surface may reduce fatigue strength. In this paper, a new method for reduction of residual stress using vibration during welding is proposed. As vibrational load, random vibration, white noise and filtered white noise are used. Two thin plates are butt-welded. Residual stress is measured with a paralleled beam X-ray diffractometer with scintillation counter after removing quenched scale chemically. It is concluded that tensile residual stress near the bead is reduced by using random vibration during welding
Combination of Wiener filtering and singular value decomposition filtering for volume imaging PET
International Nuclear Information System (INIS)
Shao, L.; Lewitt, R.M.; Karp, J.S.
1995-01-01
Although the three-dimensional (3D) multi-slice rebinning (MSRB) algorithm in PET is fast and practical, and provides an accurate reconstruction, the MSRB image, in general, suffers from the noise amplified by its singular value decomposition (SVD) filtering operation in the axial direction. Their aim in this study is to combine the use of the Wiener filter (WF) with the SVD to decrease the noise and improve the image quality. The SVD filtering ''deconvolves'' the spatially variant axial response function while the WF suppresses the noise and reduces the blurring not modeled by the axial SVD filter but included in the system modulation transfer function. Therefore, the synthesis of these two techniques combines the advantages of both filters. The authors applied this approach to the volume imaging HEAD PENN-PET brain scanner with an axial extent of 256 mm. This combined filter was evaluated in terms of spatial resolution, image contrast, and signal-to-noise ratio with several phantoms, such as a cold sphere phantom and 3D brain phantom. Specifically, the authors studied both the SVD filter with an axial Wiener filter and the SVD filter with a 3D Wiener filter, and compared the filtered images to those from the 3D reprojection (3DRP) reconstruction algorithm. Their results indicate that the Wiener filter increases the signal-to-noise ratio and also improves the contrast. For the MSRB images of the 3D brain phantom, after 3D WF, both the Gray/White and Gray/Ventricle ratios were improved from 1.8 to 2.8 and 2.1 to 4.1, respectively. In addition, the image quality with the MSRB algorithm is close to that of the 3DRP algorithm with 3D WF applied to both image reconstructions
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
Calibration of an audio frequency noise generator
DEFF Research Database (Denmark)
Diamond, Joseph M.
1966-01-01
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...... 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...
Adaptive filtering primer with Matlab
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...
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...
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 over...
Noise reduction by support vector regression with a Ricker wavelet kernel
International Nuclear Information System (INIS)
Deng, Xiaoying; Yang, Dinghui; Xie, Jing
2009-01-01
We propose a noise filtering technology based on the least-squares support vector regression (LS-SVR), to improve the signal-to-noise ratio (SNR) of seismic data. We modified it by using an admissible support vector (SV) kernel, namely the Ricker wavelet kernel, to replace the conventional radial basis function (RBF) kernel in seismic data processing. We investigated the selection of the regularization parameter for the LS-SVR and derived a concise selecting formula directly from the noisy data. We used the proposed method for choosing the regularization parameter which not only had the advantage of high speed but could also obtain almost the same effectiveness as an optimal parameter method. We conducted experiments using synthetic data corrupted by the random noise of different types and levels, and found that our method was superior to the wavelet transform-based approach and the Wiener filtering. We also applied the method to two field seismic data sets and concluded that it was able to effectively suppress the random noise and improve the data quality in terms of SNR
Noise reduction by support vector regression with a Ricker wavelet kernel
Deng, Xiaoying; Yang, Dinghui; Xie, Jing
2009-06-01
We propose a noise filtering technology based on the least-squares support vector regression (LS-SVR), to improve the signal-to-noise ratio (SNR) of seismic data. We modified it by using an admissible support vector (SV) kernel, namely the Ricker wavelet kernel, to replace the conventional radial basis function (RBF) kernel in seismic data processing. We investigated the selection of the regularization parameter for the LS-SVR and derived a concise selecting formula directly from the noisy data. We used the proposed method for choosing the regularization parameter which not only had the advantage of high speed but could also obtain almost the same effectiveness as an optimal parameter method. We conducted experiments using synthetic data corrupted by the random noise of different types and levels, and found that our method was superior to the wavelet transform-based approach and the Wiener filtering. We also applied the method to two field seismic data sets and concluded that it was able to effectively suppress the random noise and improve the data quality in terms of SNR.
Analysis on Influence Factors of Adaptive Filter Acting on ANC
Zhang, Xiuqun; Zou, Liang; Ni, Guangkui; Wang, Xiaojun; Han, Tao; Zhao, Quanfu
The noise problem has become more and more serious in recent years. The adaptive filter theory which is applied in ANC [1] (active noise control) has also attracted more and more attention. In this article, the basic principle and algorithm of adaptive theory are both researched. And then the influence factor that affects its covergence rate and noise reduction is also simulated.
Quantum noise and stochastic reduction
International Nuclear Information System (INIS)
Brody, Dorje C; Hughston, Lane P
2006-01-01
In standard nonrelativistic quantum mechanics the expectation of the energy is a conserved quantity. It is possible to extend the dynamical law associated with the evolution of a quantum state consistently to include a nonlinear stochastic component, while respecting the conservation law. According to the dynamics thus obtained, referred to as the energy-based stochastic Schroedinger equation, an arbitrary initial state collapses spontaneously to one of the energy eigenstates, thus describing the phenomenon of quantum state reduction. In this paper, two such models are investigated: one that achieves state reduction in infinite time and the other in finite time. The properties of the associated energy expectation process and the energy variance process are worked out in detail. By use of a novel application of a nonlinear filtering method, closed-form solutions-algebraic in character and involving no integration-are obtained of both these models. In each case, the solution is expressed in terms of a random variable representing the terminal energy of the system and an independent noise process. With these solutions at hand it is possible to simulate explicitly the dynamics of the quantum states of complicated physical systems
Institute of Scientific and Technical Information of China (English)
孙永辉; 高振阳; 卫志农; 孙国强
2016-01-01
Based on the measurement noise as the non-Gaussian L ´evy noise, a novel Kalman filter for the discrete linear stochastic fractional order system is proposed. By eliminating the maximum, the approximated Gaussian white noise can be obtained. Based on the principle of least square, an improved Kalman filter can be developed for the discrete linear stochastic fractional order system with measurement L´evy noise. Compared to the traditional method, the proposed method gets better performance. Finally, simulation results show the effectiveness and usefulness of the proposed algorithm.%针对量测噪声模型为非高斯L ´evy噪声，研究离散线性随机分数阶系统的卡尔曼滤波设计问题。通过剔除极大值的方法得到近似高斯白噪声的L´evy噪声，基于最小二乘原理，提出一种考虑非高斯L´evy量测噪声下的改进分数阶卡尔曼滤波算法。与传统的分数阶卡尔曼滤波相比，改进的分数阶卡尔曼滤波对非高斯L´evy噪声具有更好的滤波效果。最后，通过模拟仿真验证了所提出算法的正确性和有效性。
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...... simulations using a speech signal corrupted by car noise, and the results confirm that the output signal-to-noise ratio and speech distortion index both increase when more eigenvectors are included in the filter design....
Analog Electronic Filters Theory, Design and Synthesis
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...
Bunches of random cross-correlated sequences
International Nuclear Information System (INIS)
Maystrenko, A A; Melnik, S S; Pritula, G M; Usatenko, O V
2013-01-01
The statistical properties of random cross-correlated sequences constructed by the convolution method (likewise referred to as the Rice or the inverse Fourier transformation) are examined. We clarify the meaning of the filtering function—the kernel of the convolution operator—and show that it is the value of the cross-correlation function which describes correlations between the initial white noise and constructed correlated sequences. The matrix generalization of this method for constructing a bunch of N cross-correlated sequences is presented. Algorithms for their generation are reduced to solving the problem of decomposition of the Fourier transform of the correlation matrix into a product of two mutually conjugate matrices. Different decompositions are considered. The limits of weak and strong correlations for the one-point probability and pair correlation functions of sequences generated by the method under consideration are studied. Special cases of heavy-tailed distributions of the generated sequences are analyzed. We show that, if the filtering function is rather smooth, the distribution function of generated variables has the Gaussian or Lévy form depending on the analytical properties of the distribution (or characteristic) functions of the initial white noise. Anisotropic properties of statistically homogeneous random sequences related to the asymmetry of a filtering function are revealed and studied. These asymmetry properties are expressed in terms of the third- or fourth-order correlation functions. Several examples of the construction of correlated chains with a predefined correlation matrix are given. (paper)
Comparison of robust H∞ filter and Kalman filter for initial alignment of inertial navigation system
Institute of Scientific and Technical Information of China (English)
HAO Yan-ling; CHEN Ming-hui; LI Liang-jun; XU Bo
2008-01-01
There are many filtering methods that can be used for the initial alignment of an integrated inertial navigation system.This paper discussed the use of GPS,but focused on two kinds of filters for the initial alignment of an integrated strapdown inertial navigation system (SINS).One method is based on the Kalman filter (KF),and the other is based on the robust filter.Simulation results showed that the filter provides a quick transient response and a little more accurate estimate than KF,given substantial process noise or unknown noise statistics.So the robust filter is an effective and useful method for initial alignment of SINS.This research should make the use of SINS more popular,and is also a step for further research.
Optimization of the reconstruction and anti-aliasing filter in a Wiener filter system
Wesselink, J.M.; Berkhoff, Arthur P.
2006-01-01
This paper discusses the influence of the reconstruction and anti-aliasing filters on the performance of a digital implementation of a Wiener filter for active noise control. The overall impact will be studied in combination with a multi-rate system approach. A reconstruction and anti-aliasing
Optimal filter bandwidth for pulse oximetry
Stuban, Norbert; Niwayama, Masatsugu
2012-10-01
Pulse oximeters contain one or more signal filtering stages between the photodiode and microcontroller. These filters are responsible for removing the noise while retaining the useful frequency components of the signal, thus improving the signal-to-noise ratio. The corner frequencies of these filters affect not only the noise level, but also the shape of the pulse signal. Narrow filter bandwidth effectively suppresses the noise; however, at the same time, it distorts the useful signal components by decreasing the harmonic content. In this paper, we investigated the influence of the filter bandwidth on the accuracy of pulse oximeters. We used a pulse oximeter tester device to produce stable, repetitive pulse waves with digitally adjustable R ratio and heart rate. We built a pulse oximeter and attached it to the tester device. The pulse oximeter digitized the current of its photodiode directly, without any analog signal conditioning. We varied the corner frequency of the low-pass filter in the pulse oximeter in the range of 0.66-15 Hz by software. For the tester device, the R ratio was set to R = 1.00, and the R ratio deviation measured by the pulse oximeter was monitored as a function of the corner frequency of the low-pass filter. The results revealed that lowering the corner frequency of the low-pass filter did not decrease the accuracy of the oxygen level measurements. The lowest possible value of the corner frequency of the low-pass filter is the fundamental frequency of the pulse signal. We concluded that the harmonics of the pulse signal do not contribute to the accuracy of pulse oximetry. The results achieved by the pulse oximeter tester were verified by human experiments, performed on five healthy subjects. The results of the human measurements confirmed that filtering out the harmonics of the pulse signal does not degrade the accuracy of pulse oximetry.
MR angiography with a matched filter
International Nuclear Information System (INIS)
De Castro, J.B.; Riederer, S.J.; Lee, J.N.
1987-01-01
The technique of matched filtering was applied to a series of cine MR images. The filter was devised to yield a subtraction angiographic image in which direct current components present in the cine series are removed and the signal-to-noise ratio (S/N) of the vascular structures is optimized. The S/N of a matched filter was compared with that of a simple subtraction, in which an image with high flow is subtracted from one with low flow. Experimentally, a range of results from minimal improvement to significant (60%) improvement in S/N was seen in the comparisons of matched filtered subtraction with simple subtraction
Classroom Noise and Teachers' Voice Production
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…
Kraaijenga, Véronique J C; van Munster, J J C M; van Zanten, G A
2018-06-01
To date, factors associated with noise-induced hearing loss at music festivals have not yet been analyzed in a single comprehensive data set. In addition, little is known about the hearing loss-associated behavior of music festival attendees. To assess which factors are associated with the occurrence of a temporary threshold shift (TTS) after music exposure and to investigate the behavior of music festival attendees. This prospective post hoc analysis gathered data from a randomized, single-blind clinical trial conducted on September 5, 2015, at an outdoor music festival in Amsterdam, the Netherlands. Adult volunteers with normal hearing were recruited via social media from August 26 through September 3, 2015. Intention to use earplugs was an exclusion criterion. Of 86 volunteers assessed, 51 were included. This post hoc analysis was performed from October 3, 2016, through February 27, 2017. Music festival visit for 4.5 hours. The primary outcome was a TTS on a standard audiogram for the frequencies 3.0- and 4.0-kHz. Multivariable linear regression was performed to determine which factors are associated with a TTS. A questionnaire on behavior, hearing, and tinnitus was distributed to the participants before and after the festival visit. A total of 51 participants were included (18 men [35%] and 33 women [65%]) with a mean (SD) age of 27 (6) years. Mean (SD) threshold change across 3.0 and 4.0 kHz was 5.4 (5.7) dB for the right ear and 4.0 (6.1) dB for the left ear. Earplug use (absolute difference in the left ear, -6.0 dB [95% CI, -8.7 to -3.2 dB]; in the right ear, -6.4 dB [95% CI, -8.8 to -4.1 dB]), quantity of alcohol use (absolute difference per unit in the left ear, 1.1 dB [95% CI, 0.5 to 1.7 dB]; in the right ear, 0.7 dB [95% CI, 0.1 to 1.4 dB]), drug use (absolute difference in the right ear, 6.0 dB [95% CI, 0.9 to 11.1 dB]), and male sex (absolute difference in the right ear, 4.1 dB [95% CI, 0.3 to 5.9 dB]) were independently associated with hearing loss
Directory of Open Access Journals (Sweden)
Karl Friston
2010-01-01
Full Text Available We describe a Bayesian filtering scheme for nonlinear state-space models in continuous time. This scheme is called Generalised Filtering and furnishes posterior (conditional densities on hidden states and unknown parameters generating observed data. Crucially, the scheme operates online, assimilating data to optimize the conditional density on time-varying states and time-invariant parameters. In contrast to Kalman and Particle smoothing, Generalised Filtering does not require a backwards pass. In contrast to variational schemes, it does not assume conditional independence between the states and parameters. Generalised Filtering optimises the conditional density with respect to a free-energy bound on the model's log-evidence. This optimisation uses the generalised motion of hidden states and parameters, under the prior assumption that the motion of the parameters is small. We describe the scheme, present comparative evaluations with a fixed-form variational version, and conclude with an illustrative application to a nonlinear state-space model of brain imaging time-series.
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. [...
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.
Adaptive Filtering Using Recurrent Neural Networks
Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.
2005-01-01
A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.
International Nuclear Information System (INIS)
Vieira, Fabio P.B.; Bevilacqua, Joyce S.
2014-01-01
The use of electron paramagnetic resonance spectrometers - EPR - in radiation dosimetry is known for more than four decades. It is an important tool in the retrospective determination of doses absorbed. To estimate the dose absorbed by the sample, it is necessary to know the amplitude of the peak to peak signature of the substance in its EPR spectrum. This information can be compromised by the presence of spurious information: noise - of random and low intensity nature; and the behavior of the baseline - coming from the coupling between the resonator tube and the sample analyzed. Due to the intrinsic characteristics of the three main components of the signal, i.e. signature, noise, and baseline - the analysis in the frequency domain allows, through post-processing techniques to filter spurious information. In this work, an algorithm that retrieves the signature of a substance has been implemented. The Discrete Fourier Transform is applied to the signal and without user intervention, the noise is filtered. From the filtered signal, recovers the signature by Inverse Discrete Fourier Transform. The peak to peak amplitude, and the absorbed dose is calculated with an error of less than 1% for signals wherein the base line is linearized. Some more general cases are under investigation and with little user intervention, you can get the same error
Noise in strong laser-atom interactions: Phase telegraph noise
International Nuclear Information System (INIS)
Eberly, J.H.; Wodkiewicz, K.; Shore, B.W.
1984-01-01
We discuss strong laser-atom interactions that are subjected to jump-type (random telegraph) random-phase noise. Physically, the jumps may arise from laser fluctuations, from collisions of various kinds, or from other external forces. Our discussion is carried out in two stages. First, direct and partially heuristic calculations determine the laser spectrum and also give a third-order differential equation for the average inversion of a two-level atom on resonance. At this stage a number of general features of the interaction are able to be studied easily. The optical analog of motional narrowing, for example, is clearly predicted. Second, we show that the theory of generalized Poisson processes allows laser-atom interactions in the presence of random telegraph noise of all kinds (not only phase noise) to be treated systematically, by means of a master equation first used in the context of quantum optics by Burshtein. We use the Burshtein equation to obtain an exact expression for the two-level atom's steady-state resonance fluorescence spectrum, when the exciting laser exhibits phase telegraph noise. Some comparisons are made with results obtained from other noise models. Detailed treatments of the effects ofmly jumps, or as a model of finite laser bandwidth effects, in which the laser frequency exhibits random jumps. We show that these two types of frequency noise can be distinguished in light-scattering spectra. We also discuss examples which demonstrate both temporal and spectral motional narrowing, nonexponential correlations, and non-Lorentzian spectra. Its exact solubility in finite terms makes the frequency-telegraph noise model an attractive alternative to the white-noise Ornstein-Uhlenbeck frequency noise model which has been previously applied to laser-atom interactions
Directory of Open Access Journals (Sweden)
Rahmadhi Prihandono
2017-01-01
Full Text Available Frekuensi sebesar 50 Hz harus dijaga agar memberikan kualitas energi listrik yang baik. Pengaruh dari switching pada sisi beban akan membuat frekuensi energi listrik menjadi fluktuatif. Nilai frekuensi yang fluktuatif akan membuat fungsi derivatif pada kontroler Proportional Integral Derivative (PID menjadi sangat besar, sehingga akan mempengaruhi sinyal kontrol. Nilai tersebut memaksa aktuator bekerja sangat cepat dan akan mengurangi masa pemakaian aktuator. Penambahan filter pada kontroler PID untuk sistem pengaturan pembangkitan energi listrik mampu meredam noise yang timbul akibat fluktuasi beban. Penambahan Low Pass Filter (LPF pada sisi derivatif memberikan redaman noise begitu pula menggunakan fungsi Averaged Derivative (AD. Dengan beban acak yang dimodelkan dengan Pseudo Random Binary Sequences (PRBS, nilai kesalahan dengan perhitungan Integral Absolute Error (IAE terkecil dimiliki oleh PID dengan averaged derivative sebesar 110,246 Hz dan PID dengan low pass filter sebesar 110,486 Hz
Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J
2011-10-07
Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning
Institute of Scientific and Technical Information of China (English)
XIAO Kun; FANG Shao-ji; PANG Yong-jie
2007-01-01
To improve underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.
Implementation of non-linear filters for iterative penalized maximum likelihood image reconstruction
International Nuclear Information System (INIS)
Liang, Z.; Gilland, D.; Jaszczak, R.; Coleman, R.
1990-01-01
In this paper, the authors report on the implementation of six edge-preserving, noise-smoothing, non-linear filters applied in image space for iterative penalized maximum-likelihood (ML) SPECT image reconstruction. The non-linear smoothing filters implemented were the median filter, the E 6 filter, the sigma filter, the edge-line filter, the gradient-inverse filter, and the 3-point edge filter with gradient-inverse filter, and the 3-point edge filter with gradient-inverse weight. A 3 x 3 window was used for all these filters. The best image obtained, by viewing the profiles through the image in terms of noise-smoothing, edge-sharpening, and contrast, was the one smoothed with the 3-point edge filter. The computation time for the smoothing was less than 1% of one iteration, and the memory space for the smoothing was negligible. These images were compared with the results obtained using Bayesian analysis
Volcano monitoring using the Global Positioning System: Filtering strategies
Larson, K.M.; Cervelli, Peter; Lisowski, M.; Miklius, Asta; Segall, P.; Owen, S.
2001-01-01
Permanent Global Positioning System (GPS) networks are routinely used for producing improved orbits and monitoring secular tectonic deformation. For these applications, data are transferred to an analysis center each day and routinely processed in 24-hour segments. To use GPS for monitoring volcanic events, which may last only a few hours, real-time or near real-time data processing and subdaily position estimates are valuable. Strategies have been researched for obtaining station coordinates every 15 min using a Kalman filter; these strategies have been tested on data collected by a GPS network on Kilauea Volcano. Data from this network are tracked continuously, recorded every 30 s, and telemetered hourly to the Hawaiian Volcano Observatory. A white noise model is heavily impacted by data outages and poor satellite geometry, but a properly constrained random walk model fits the data well. Using a borehole tiltmeter at Kilauea's summit as ground-truth, solutions using different random walk constraints were compared. This study indicates that signals on the order of 5 mm/h are resolvable using a random walk standard deviation of 0.45 cm/???h. Values lower than this suppress small signals, and values greater than this have significantly higher noise at periods of 1-6 hours. Copyright 2001 by the American Geophysical Union.
Filtering in Hybrid Dynamic Bayesian Networks
Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin
2000-01-01
We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).
Better Faster Noise with the GPU
DEFF Research Database (Denmark)
Wyvill, Geoff; Frisvad, Jeppe Revall
Filtered noise [Perlin 1985] has, for twenty years, been a fundamental tool for creating functional texture and it has many other applications; for example, animating water waves or the motion of grass waving in the wind. Perlin noise suffers from a number of defects and there have been many atte...... attempts to create better or faster noise but Perlin’s ‘Gradient Noise’ has consistently proved to be the best compromise between speed and quality. Our objective was to create a better noise cheaply by use of the GPU....
Noise reduction in the beam current monitor
International Nuclear Information System (INIS)
Arai, Shigeaki.
1982-02-01
A simple noise reduction system using a pulse transformer and a pair of L C low pass filters has been introduced to the beam current monitor of a current transformer type at the INS electron linac. With this system, the pick-up noise has been reduced to be 1% of the noise without noise reduction. Signal deformation caused by this system is relatively small and the beam current pulse down to 20 mA is successfully monitored in the actual accelerator operation. (author)
Directory of Open Access Journals (Sweden)
Lee Sangkyu
2016-01-01
Full Text Available In this paper, we present a new algorithm that improves muon-based generated tomography images with increased precision and reduced image noise applicable to the detection of nuclear materials. Cosmic muon tomography is an interrogation-based imaging technique that, over the last decade, has been frequently employed for the detection of high-Z materials. This technique exploits a magnitude of cosmic muon scattering angles in order to construct an image. The scattering angles of the muons striking the geometry of interest are non-uniform, as cosmic muons vary in energy. The randomness of the scattering angles leads to significant noise in the muon tomography image. GEANT4 is used to numerically create data on the momenta and positions of scattered muons in a predefined geometry that includes high-Z materials. The numerically generated information is then processed with the point of closest approach reconstruction method to construct a muon tomography image; statistical filters are then developed to refine the point of closest approach reconstructed images. The filtered images exhibit reduced noise and enhanced precision when attempting to identify the presence of high-Z materials. The average precision from the point of closest approach reconstruction method is 13 %; for the integrated method, 88 %. The filtered image, therefore, results in a seven-fold improvement in precision compared to the point of closest approach reconstructed image.
Energy Technology Data Exchange (ETDEWEB)
Khawaja, Ranish Deedar Ali, E-mail: rkhawaja@mgh.harvard.edu [Division of Thoracic Radiology, MGH Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States); Singh, Sarabjeet [Division of Thoracic Radiology, MGH Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States); Madan, Rachna [Division of Thoracic Radiology, Brigham and Women' s Hospital and Harvard Medical School, Boston (United States); Sharma, Amita; Padole, Atul; Pourjabbar, Sarvenaz; Digumarthy, Subba; Shepard, Jo-Anne; Kalra, Mannudeep K. [Division of Thoracic Radiology, MGH Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States)
2014-10-15
Highlights: • Filtered back projection technique enables acceptable image quality for chest CT examinations at 0.9 mGy (estimated effective dose of 0.5 mSv) for selected sizes of patients. • Lesion detection (such as solid non-calcified lung nodules) in lung parenchyma is optimal at 0.9 mGy, with limited visualization of thyroid nodules in FBP images. • Further dose reduction down to 0.4 mGy is possible for most patients undergoing follow-up chest CT for evaluation of larger lung nodules and GGOs. • Our results may help set the reference ALARA dose for chest CT examinations reconstructed with filtered back projection technique using the minimum possible radiation dose with acceptable image quality and lesion detection. - Abstract: Purpose: To assess lesion detection and diagnostic image quality of filtered back projection (FBP) reconstruction technique in ultra low-dose chest CT examinations. Methods and materials: In this IRB-approved ongoing prospective clinical study, 116 CT-image-series at four different radiation-doses were performed for 29 patients (age, 57–87 years; F:M – 15:12; BMI 16–32 kg/m{sup 2}). All patients provided written-informed-consent for the acquisitions of additional ultra low-dose (ULD) series on a 256-slice MDCT (iCT, Philips Healthcare). In-addition to their clinical standard-dose chest CT (SD, 120 kV mean CTDI{sub vol}, 6 ± 1 mGy), ULD-CT was subsequently performed at three-dose-levels (0.9 mGy [120 kV]; 0.5 mGy [100 kV] and 0.2 mGy [80 kV]). Images were reconstructed with FBP (2.5 mm * 1.25 mm) resulting into four-stacks: SD-FBP (reference-standard), FBP{sub 0.9}, FBP{sub 0.5}, and FBP{sub 0.2}. Four thoracic-radiologists from two-teaching-hospitals independently-evaluated data for lesion-detection and visibility-of-small-structures. Friedman's-non-parametric-test with post hoc Dunn's-test was used for data-analysis. Results: Interobserver-agreement was substantial between radiologists (k = 0.6–0.8). With
Locally-adaptive Myriad Filters for Processing ECG Signals in Real Time
Directory of Open Access Journals (Sweden)
Nataliya Tulyakova
2017-03-01
Full Text Available The locally adaptive myriad filters to suppress noise in electrocardiographic (ECG signals in almost in real time are proposed. Statistical estimates of efficiency according to integral values of such criteria as mean square error (MSE and signal-to-noise ratio (SNR for the test ECG signals sampled at 400 Hz embedded in additive Gaussian noise with different values of variance are obtained. Comparative analysis of adaptive filters is carried out. High efficiency of ECG filtering and high quality of signal preservation are demonstrated. It is shown that locally adaptive myriad filters provide higher degree of suppressing additive Gaussian noise with possibility of real time implementation.
Noise characteristics of neutron images obtained by cooled CCD device
International Nuclear Information System (INIS)
Taniguchi, Ryoichi; Sasaki, Ryoya; Okuda, Shuichi; Okamoto, Ken-Ichi; Ogawa, Yoshihiro; Tsujimoto, Tadashi
2009-01-01
The noise characteristics of a cooled CCD device induced by neutron and gamma ray irradiation have been investigated. In the cooled CCD images, characteristic white spot noises (CCD noise) frequently appeared, which have a shape like a pixel in most cases and their brightness is extremely high compared with that of the image pattern. They could be divided into the two groups, fixed pattern noise (FPN) and random noise. The former always appeared in the same position in the image and the latter appeared at any position. In the background image, nearly all of the CCD noises were found to be the FPN, while many of them were the random noise during the irradiation. The random CCD noises increased with irradiation and decreased soon after the irradiation. In the case of large irradiation, a part of the CCD noise remained as the FPN. These facts suggest that the CCD noise is a phenomenon strongly relating to radiation damage of the CCD device.
Restoration of nuclear medicine images using adaptive Wiener filters
International Nuclear Information System (INIS)
Meinel, G.
1989-01-01
An adaptive Wiener filter implementation for restoration of nuclear medicine images is described. These are considerably disturbed both deterministically (definition) and stochastically (Poisson's quantum noise). After introduction of an image model, description of necessary parameter approximations and information on optimum design methods the implementation is described. The filter operates adaptively as concerns the local signal-to-noise ratio and is based on a filter band concept. To verify the restoration effect size numbers are introduced and the filter is tested against these numbers. (author)
Ren, Zhong; Liu, Guodong; Huang, Zhen
2012-11-01
The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.
An optimal filter for short photoplethysmogram signals
Liang, Yongbo; Elgendi, Mohamed; Chen, Zhencheng; Ward, Rabab
2018-01-01
A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4th order. PMID:29714722
A passive inverse filter for Green's function retrieval.
Gallot, Thomas; Catheline, Stefan; Roux, Philippe; Campillo, Michel
2012-01-01
Passive methods for the recovery of Green's functions from ambient noise require strong hypotheses, including isotropic distribution of the noise sources. Very often, this distribution is nonisotropic, which introduces bias in the Green's function reconstruction. To minimize this bias, a spatiotemporal inverse filter is proposed. The method is tested on a directive noise field computed from an experimental active seismic data set. The results indicate that the passive inverse filter allows the manipulation of the spatiotemporal degrees of freedom of a complex wave field, and it can efficiently compensate for the noise wavefield directivity. © 2012 Acoustical Society of America.
High level white noise generator
International Nuclear Information System (INIS)
Borkowski, C.J.; Blalock, T.V.
1979-01-01
A wide band, stable, random noise source with a high and well-defined output power spectral density is provided which may be used for accurate calibration of Johnson Noise Power Thermometers (JNPT) and other applications requiring a stable, wide band, well-defined noise power spectral density. The noise source is based on the fact that the open-circuit thermal noise voltage of a feedback resistor, connecting the output to the input of a special inverting amplifier, is available at the amplifier output from an equivalent low output impedance caused by the feedback mechanism. The noise power spectral density level at the noise source output is equivalent to the density of the open-circuit thermal noise or a 100 ohm resistor at a temperature of approximately 64,000 Kelvins. The noise source has an output power spectral density that is flat to within 0.1% (0.0043 db) in the frequency range of from 1 KHz to 100 KHz which brackets typical passbands of the signal-processing channels of JNPT's. Two embodiments, one of higher accuracy that is suitable for use as a standards instrument and another that is particularly adapted for ambient temperature operation, are illustrated in this application
Adjusting phenotypes by noise control.
Directory of Open Access Journals (Sweden)
Kyung H Kim
2012-01-01
Full Text Available Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks.
High level white noise generator
Borkowski, Casimer J.; Blalock, Theron V.
1979-01-01
A wide band, stable, random noise source with a high and well-defined output power spectral density is provided which may be used for accurate calibration of Johnson Noise Power Thermometers (JNPT) and other applications requiring a stable, wide band, well-defined noise power spectral density. The noise source is based on the fact that the open-circuit thermal noise voltage of a feedback resistor, connecting the output to the input of a special inverting amplifier, is available at the amplifier output from an equivalent low output impedance caused by the feedback mechanism. The noise power spectral density level at the noise source output is equivalent to the density of the open-circuit thermal noise or a 100 ohm resistor at a temperature of approximately 64,000 Kelvins. The noise source has an output power spectral density that is flat to within 0.1% (0.0043 db) in the frequency range of from 1 KHz to 100 KHz which brackets typical passbands of the signal-processing channels of JNPT's. Two embodiments, one of higher accuracy that is suitable for use as a standards instrument and another that is particularly adapted for ambient temperature operation, are illustrated in this application.
Tinney, Charles; Sirohi, Jayant; University of Texas at Austin Team
2017-11-01
A basic understanding of the noise produced by single and multirotor drones operating at static thrust conditions is presented. This work acts as an extension to previous efforts conducted at The University of Texas at Austin (Tinney et al. 2017, AHS Forum 73). Propeller diameters ranging from 8 inch to 12 inch are examined for configurations comprising an isolated rotor, a quadcopter configuration and a hexacopter configuration, and with a constant drone pitch of 2.25. An azimuthal array of half-inch microphones, placed between 2 and 3 hub-center diameters from the drone center, are used to assess the acoustic near-field. Thrust levels, acquired using a six degree-of-freedom load cell, are then used to correlate acoustic noise levels to aerodynamic performance for each drone configuration. The findings reveal a nearly logarithmic increase in noise with increasing thrust. However, for the same thrust condition, considerable noise reduction is achieved by increasing the number of propeller blades thereby reducing the blade passage frequency and both the thickness and loading noise sources that accompany it.
Comparison of Deconvolution Filters for Photoacoustic Tomography.
Directory of Open Access Journals (Sweden)
Dominique Van de Sompel
Full Text Available In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT. We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method's robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM and contrast-to-noise ratio (CNR of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum, achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov
Poisson filtering of laser ranging data
Ricklefs, Randall L.; Shelus, Peter J.
1993-01-01
The filtering of data in a high noise, low signal strength environment is a situation encountered routinely in lunar laser ranging (LLR) and, to a lesser extent, in artificial satellite laser ranging (SLR). The use of Poisson statistics as one of the tools for filtering LLR data is described first in a historical context. The more recent application of this statistical technique to noisy SLR data is also described.
Algoritma Filter Kalman untuk Menghaluskan Data Pengukuran
Rudiyanto; Setiawan, Budi Indra; Saptomo, Satyanto Krido
2006-01-01
The objective of this paper is to apply a simple algorithm of Kalman Filter, wich is know as noise data filtering. The computer program was written in Macro Visual Basic in MS Exel. Testings were carried out on available temperature, Water level and force data and then were comared with the mooving average method. The result shows that the algorithm performed better and lesser deviation than the mooving average.
Algoritma Filter Kalman untuk Menghaluskan Data Pengukuran
Directory of Open Access Journals (Sweden)
Rudiyanto
2006-12-01
Full Text Available The objective of this paper is to apply a simple algorithm of Kalman Filter, wich is know as noise data filtering. The computer program was written in Macro Visual Basic in MS Exel. Testings were carried out on available temperature, Water level and force data and then were comared with the mooving average method. The result shows that the algorithm performed better and lesser deviation than the mooving average.
A filter bank for rotationally invariant image recognition
African Journals Online (AJOL)
2005-07-18
Jul 18, 2005 ... random noise as well as an interesting, less known impact of noise ..... IEEE Transactions on Pattern Analysis and Machine Intelligence, ... [23] Thuillard M, 2001, Wavelets in Soft Computing, World scientific series in robotics.
GEKF, GUKF and GGPF based prediction of chaotic time-series with additive and multiplicative noises
International Nuclear Information System (INIS)
Wu Xuedong; Song Zhihuan
2008-01-01
On the assumption that random interruptions in the observation process are modelled by a sequence of independent Bernoulli random variables, this paper generalize the extended Kalman filtering (EKF), the unscented Kalman filtering (UKF) and the Gaussian particle filtering (GPF) to the case in which there is a positive probability that the observation in each time consists of noise alone and does not contain the chaotic signal (These generalized novel algorithms are referred to as GEKF, GUKF and GGPF correspondingly in this paper). Using weights and network output of neural networks to constitute state equation and observation equation for chaotic time-series prediction to obtain the linear system state transition equation with continuous update scheme in an online fashion, and the prediction results of chaotic time series represented by the predicted observation value, these proposed novel algorithms are applied to the prediction of Mackey–Glass time-series with additive and multiplicative noises. Simulation results prove that the GGPF provides a relatively better prediction performance in comparison with GEKF and GUKF. (general)
Multichannel Signal Enhancement using Non-Causal, Time-Domain Filters
DEFF Research Database (Denmark)
Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob
2013-01-01
In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. W......In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non......-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality....
Fractals in Power Reactor Noise
International Nuclear Information System (INIS)
Aguilar Martinez, O.
1994-01-01
In this work the non- lineal dynamic problem of power reactor is analyzed using classic concepts of fractal analysis as: attractors, Hausdorff-Besikovics dimension, phase space, etc. A new non-linear problem is also analyzed: the discrimination of chaotic signals from random neutron noise signals and processing for diagnosis purposes. The advantages of a fractal analysis approach in the power reactor noise are commented in details