Generation of Long Waves using Non-Linear Digital Filters
DEFF Research Database (Denmark)
Høgedal, Michael; Frigaard, Peter; Christensen, Morten
1994-01-01
transform of the 1st order surface elevation and subsequently inverse Fourier transformed. Hence, the methods are unsuitable for real-time applications, for example where white noise are filtered digitally to obtain a wave spectrum with built-in stochastic variabillity. In the present paper an approximative...... method for including the correct 2nd order bound terms in such applications is presented. The technique utilizes non-liner digital filters fitted to the appropriate transfer function is derived only for bounded 2nd order subharmonics, as they laboratory experiments generally are considered the most...
A 3-D nonlinear recursive digital filter for video image processing
Bauer, P. H.; Qian, W.
1991-01-01
This paper introduces a recursive 3-D nonlinear digital filter, which is capable of performing noise suppression without degrading important image information such as edges in space or time. It also has the property of unnoticeable bandwidth reduction immediately after a scene change, which makes the filter an attractive preprocessor to many interframe compression algorithms. The filter consists of a nonlinear 2-D spatial subfilter and a 1-D temporal filter. In order to achieve the required computational speed and increase the flexibility of the filter, all of the linear shift-variant filter modules are of the IIR type.
Nonlinear temporal filtering of time-resolved digital particle image velocimetry data
Energy Technology Data Exchange (ETDEWEB)
Fore, L.B.; Tung, A.T.; Buchanan, J.R.; Welch, J.W. [Bechtel Bettis Inc., West Mifflin, PA (United States)
2005-07-01
Nonlinear filtering methods have been developed to identify and replace outlying data points in velocity time series obtained with time-resolved digital particle image velocimetry (PIV) of the flow around a surface-mounted cube at a Reynolds number of 20,000. Nuances associated with the spectral computation of the cross-correlation are highlighted, including the requirement of zero-padding an image interrogation area to eliminate the circular components of the cross-correlation. Three nonlinear filtering methods for the replacement of outliers are applied to the velocity time series sampled at 1,000 Hz: a median filter, a decision-based Hampel filter, and a PIV-specific Hampel filter. The particular benefit of the PIV-specific Hampel filter is that it allows the retention of actual measured data, sometimes derived from alternate peaks in the cross-correlation function, while still providing for the removal of outliers when a consistent, nonoutlying measurement is not available. (orig.)
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
Chaotic keyed hash function based on feedforward feedback nonlinear digital filter
Zhang, Jiashu; Wang, Xiaomin; Zhang, Wenfang
2007-03-01
In this Letter, we firstly construct an n-dimensional chaotic dynamic system named feedforward feedback nonlinear filter (FFNF), and then propose a novel chaotic keyed hash algorithm using FFNF. In hashing process, the original message is modulated into FFNF's chaotic trajectory by chaotic shift keying (CSK) mode, and the final hash value is obtained by the coarse-graining quantization of chaotic trajectory. To expedite the avalanche effect of hash algorithm, a cipher block chaining (CBC) mode is introduced. Theoretic analysis and numerical simulations show that the proposed hash algorithm satisfies the requirement of keyed hash function, and it is easy to implement by the filter structure.
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).
Kovačević, Branko; Milosavljević, Milan
2013-01-01
“Adaptive Digital Filters” presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in m...
Knapp, R.W.; Anderson, N.L.
1994-01-01
Data may be overprinted by a steady-state cyclical noise (hum). Steady-state indicates that the noise is invariant with time; its attributes, frequency, amplitude, and phase, do not change with time. Hum recorded on seismic data usually is powerline noise and associated higher harmonics; leakage from full-waveform rectified cathodic protection devices that contain the odd higher harmonics of powerline frequencies; or vibrational noise from mechanical devices. The fundamental frequency of powerline hum may be removed during data acquisition with the use of notch filters. Unfortunately, notch filters do not discriminate signal and noise, attenuating both. They also distort adjacent frequencies by phase shifting. Finally, they attenuate only the fundamental mode of the powerline noise; higher harmonics and frequencies other than that of powerlines are not removed. Digital notch filters, applied during processing, have many of the same problems as analog filters applied in the field. The method described here removes hum of a particular frequency. Hum attributes are measured by discrete Fourier analysis, and the hum is canceled from the data by subtraction. Errors are slight and the result of the presence of (random) noise in the window or asynchrony of the hum and data sampling. Error is minimized by increasing window size or by resampling to a finer interval. Errors affect the degree of hum attenuation, not the signal. The residual is steady-state hum of the same frequency. ?? 1994.
Digital filter synthesis computer program
Moyer, R. A.; Munoz, R. M.
1968-01-01
Digital filter synthesis computer program expresses any continuous function of a complex variable in approximate form as a computational algorithm or difference equation. Once the difference equation has been developed, digital filtering can be performed by the program on any input data list.
Digital filtering: background and tutorial for psychophysiologists.
Cook, E W; Miller, G A
1992-05-01
Digital filtering offers more to psychophysiologists than is commonly appreciated. An introduction is offered here to foster the explicit design and use of digital filters. Because of considerable confusion in the literature about terminology important to both analog and digital filtering, basic concepts are reviewed and clarified. Because some time series concepts are fundamental to digital filtering, these are also presented. Examples of filters commonly used in psychophysiology are given, and procedures are presented for the design and use of one type of digital filter. Properties of some types of digital filters are described, and the relative advantages of simple analog and digital filters are discussed.
Digital Filters Using Identical Blocks
Directory of Open Access Journals (Sweden)
S. C. Dutta
1985-07-01
Full Text Available Improved response of non-recursive digital filters is achieved using Amplitude Change Functions (ACFs on a prototype filter. A generalized ACF with interesting properties is suggested. Methods for achieving variable cut-off frequency and frequency transformation are explained. A modular hardware implementation is also presented.
Nanophotonic filters for digital imaging
Walls, Kirsty
There has been an increasing demand for low cost, portable CMOS image sensors because of increased integration, and new applications in the automotive, mobile communication and medical industries, amongst others. Colour reproduction remains imperfect in conventional digital image sensors, due to the limitations of the dye-based filters. Further improvement is required if the full potential of digital imaging is to be realised. In alternative systems, where accurate colour reproduction is a priority, existing equipment is too bulky for anything but specialist use. In this work both these issues are addressed by exploiting nanophotonic techniques to create enhanced trichromatic filters, and multispectral filters, all of which can be fabricated on-chip, i.e. integrated into a conventional digital image sensor, to create compact, low cost, mass produceable imaging systems with accurate colour reproduction. The trichromatic filters are based on plasmonic structures. They exploit the excitation of surface plasmon resonances in arrays of subwavelength holes in metal films to filter light. The currently-known analytical expressions are inadequate for optimising all relevant parameters of a plasmonic structure. In order to obtain arbitrary filter characteristics, an automated design procedure was developed that integrated a genetic algorithm and 3D finite-difference time-domain tool. The optimisation procedure's efficacy is demonstrated by designing a set of plasmonic filters that replicate the CIE (1931) colour matching functions, which themselves mimic the human eye's daytime colour response.
Digital Filters for Low Frequency Equalization
DEFF Research Database (Denmark)
Tyril, Marni; Abildgaard, J.; Rubak, Per
2001-01-01
Digital filters with high resolution in the low-frequency range are studied. Specifically, for a given computational power, traditional IIR filters are compared with warped FIR filters, warped IIR filters, and modified warped FIR filters termed warped individual z FIR filters (WizFIR). The results...... indicate that IIR filters are the most effective in a number of situations....
Digital Filters for Low Frequency Equalization
DEFF Research Database (Denmark)
Tyril, Marni; Abildgaard, J.; Rubak, Per
2001-01-01
Digital filters with high resolution in the low-frequency range are studied. Specifically, for a given computational power, traditional IIR filters are compared with warped FIR filters, warped IIR filters, and modified warped FIR filters termed warped individual z FIR filters (WizFIR). The results...
Nonlinear filtering for LIDAR signal processing
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.
Approximately liner phase IIR digital filter banks
J. D. Ćertić; M. D. Lutovac; L. D. Milić
2013-01-01
In this paper, uniform and nonuniform digital filter banks based on approximately linear phase IIR filters and frequency response masking technique (FRM) are presented. Both filter banks are realized as a connection of an interpolated half-band approximately linear phase IIR filter as a first stage of the FRM design and an appropriate number of masking filters. The masking filters are half-band IIR filters with an approximately linear phase. The resulting IIR filter banks are compared with li...
From Microwave Filter to Digital Filter and Back Again
DEFF Research Database (Denmark)
Dalby, Arne Brejning
1989-01-01
A new very simple state variable flow graph representation for interdigital transmission line bandpass filters is presented, which has led to two important results: 1) A new type of digital filter with properties, that surpass the properties of most other (all pole) digital filtertypes. 2......) The study of the new digital filtertype has led to design formulas for interdigital transmission line filters that are very simple compared to the hitherto known formulas. The accuracy is the same or better....
Euclidean Quantum Mechanics and Universal Nonlinear Filtering
Directory of Open Access Journals (Sweden)
Bhashyam Balaji
2009-02-01
Full Text Available An important problem in applied science is the continuous nonlinear filtering problem, i.e., the estimation of a Langevin state that is observed indirectly. In this paper, it is shown that Euclidean quantum mechanics is closely related to the continuous nonlinear filtering problem. The key is the configuration space Feynman path integral representation of the fundamental solution of a Fokker-Planck type of equation termed the Yau Equation of continuous-continuous filtering. A corollary is the equivalence between nonlinear filtering problem and a time-varying Schr¨odinger equation.
Nonlinear Attitude Filtering: A Comparison Study
Zamani, M.; Trumpf, J.; Mahony, R.
2015-01-01
This paper contains a concise comparison of a number of nonlinear attitude filtering methods that have attracted attention in the robotics and aviation literature. With the help of previously published surveys and comparison studies, the vast literature on the subject is narrowed down to a small pool of competitive attitude filters. Amongst these filters is a second-order optimal minimum-energy filter recently proposed by the authors. Easily comparable discretized unit quaternion implementati...
Design and Implementation of Wave Digital Filters
Directory of Open Access Journals (Sweden)
V. Davidek
2001-09-01
Full Text Available One of possibilities of the Wave Digital Filters (WDF design isusing the classical LC-filters theory. The aim of this paper is todemonstrate the design of WDF from the LC filter and the implementationof WDF on the fixed-point digital signal processor. The theory of wavedigital filter has been developed by using the classical scatteringparameter theory. The theory of ladder filters is well-known, and soour present problem can thus be reduced to a problem how to replace theL and C elements of the filters by adaptors and delay elements, addersand multipliers.
Particle Kalman Filtering: A Nonlinear Framework for Ensemble Kalman Filters
Hoteit, Ibrahim
2010-09-19
Optimal nonlinear filtering consists of sequentially determining the conditional probability distribution functions (pdf) of the system state, given the information of the dynamical and measurement processes and the previous measurements. Once the pdfs are obtained, one can determine different estimates, for instance, the minimum variance estimate, or the maximum a posteriori estimate, of the system state. It can be shown that, many filters, including the Kalman filter (KF) and the particle filter (PF), can be derived based on this sequential Bayesian estimation framework. In this contribution, we present a Gaussian mixture‐based framework, called the particle Kalman filter (PKF), and discuss how the different EnKF methods can be derived as simplified variants of the PKF. We also discuss approaches to reducing the computational burden of the PKF in order to make it suitable for complex geosciences applications. We use the strongly nonlinear Lorenz‐96 model to illustrate the performance of the PKF.
Nonlinear Filter Based Image Denoising Using AMF Approach
Thivakaran, T K
2010-01-01
This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly e...
Interpolation and Iteration for Nonlinear Filters
Chorin, Alexandre J
2009-01-01
We present a general form of the iteration and interpolation process used in implicit particle filters. Implicit filters are based on a pseudo-Gaussian representation of posterior densities, and are designed to focus the particle paths so as to reduce the number of particles needed in nonlinear data assimilation. Examples are given.
Satisfactory Optimization Design of IIR Digital Filters
Institute of Scientific and Technical Information of China (English)
Jin Weidong; Zhang Gexiang; Zhao Duo
2005-01-01
A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.
Gradient based filtering of digital elevation models
DEFF Research Database (Denmark)
Knudsen, Thomas; Andersen, Rune Carbuhn
We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based on ...... in the landscape are washed out and misrepresented....
Gradient based filtering of digital elevation models
DEFF Research Database (Denmark)
Knudsen, Thomas; Andersen, Rune Carbuhn
We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...
Digital filters principles and applications with MATLAB
Taylor, Fred J
2012-01-01
"The proposed book is not an exposition on digital signal processing (DSP) but rather a treatise on digital filters. The material and coverage is comprehensive, presented in a consistent style that first develops topics and subtopics in terms it their purpose, relationship to other core ideas, theoretical and conceptual framework, and finally instruction in the implementation of digital filter devices. Each major study is supported by Matlab-enabled activities and examples, with each Chapter culminating in a comprehensive design case study"--
Nonlinear Filtering and Approximation Techniques
1988-10-01
e par des iquations de dimension finie, les 6quations du filtre de Kalman : X +h~pklk Xk=(1 + bAt).kk..I + e2+h2 pl_(k - h( + b~t)Xk-... (6 -kIj (1...Equation. 3. Piecewise Linear Filtering with Small Observation Noise. 4. Filtres Approches pour un Probleme de Fitrage Nonlineaire Discretise avec Petit...finite dimensional solution, namely the Kalman filter (which is the extended Kalman filter for (0.1) ). The above considerations tend to indicate that
An Adaptive Nonlinear Filter for System Identification
Directory of Open Access Journals (Sweden)
Tokunbo Ogunfunmi
2009-01-01
Full Text Available The primary difficulty in the identification of Hammerstein nonlinear systems (a static memoryless nonlinear system in series with a dynamic linear system is that the output of the nonlinear system (input to the linear system is unknown. By employing the theory of affine projection, we propose a gradient-based adaptive Hammerstein algorithm with variable step-size which estimates the Hammerstein nonlinear system parameters. The adaptive Hammerstein nonlinear system parameter estimation algorithm proposed is accomplished without linearizing the systems nonlinearity. To reduce the effects of eigenvalue spread as a result of the Hammerstein system nonlinearity, a new criterion that provides a measure of how close the Hammerstein filter is to optimum performance was used to update the step-size. Experimental results are presented to validate our proposed variable step-size adaptive Hammerstein algorithm given a real life system and a hypothetical case.
FORTRAN IV Digital Filter Design Programs. Digital Systems Education Project.
Reuss, E.; And Others
The goals of the Digital Systems Education Project (DISE) include the development and distribution of educational/instructional materials in the digital systems area. Toward that end, this document contains three reports: (1) A FORTRAN IV Design Program for Low-Pass Butterworth and Chebychev Digital Filters; (2) A FORTRAN IV Design Program for…
Numerical discretization for nonlinear diffusion filter
Mustaffa, I.; Mizuar, I.; Aminuddin, M. M. M.; Dasril, Y.
2015-05-01
Nonlinear diffusion filters are famously used in machine vision for image denoising and restoration. This paper presents a study on the effects of different numerical discretization of nonlinear diffusion filter. Several numerical discretization schemes are presented; namely semi-implicit, AOS, and fully implicit schemes. The results of these schemes are compared by visual results, objective measurement e.g. PSNR and MSE. The results are also compared to a Daubechies wavelet denoising method. It is acknowledged that the two preceding scheme have already been discussed in literature, however comparison to the latter scheme has not been made. The semi-implicit scheme uses an additive operator splitting (AOS) developed to overcome the shortcoming of the explicit scheme i.e., stability for very small time steps. Although AOS has proven to be efficient, from the nonlinear diffusion filter results with different discretization schemes, examples shows that implicit schemes are worth pursuing.
Testing of Nonlinear Filters For Coloured Noise
Macek, Wieslaw M.; Redaelli, Stefano; Plewczynski, Dariusz
We focus on nonlinearity and deterministic behaviour of classical model systems cor- rupted by white or coloured noise. Therefore, we use nonlinear filters to give a faith- ful representation of nonlinear behaviour of the systems. We also analyse time series of a real system, namely, we study velocities of of the solar wind plasma including Alfvénic fluctuations measured in situ by the Helios spacecraft in the inner helio- sphere. We demonstrate that the influence of white and coloured noise in the data records can be efficiently reduced by a nonlinear filter. We show that due to this non- linear noise reduction we get with much reliability estimates of the largest Lyapunov exponent and the Kolmogorov entropy.
Nonlinear projective filtering in a data stream
Schreiber, T; Schreiber, Thomas; Richter, Marcus
1998-01-01
We introduce a modified algorithm to perform nonlinear filtering of a time series by locally linear phase space projections. Unlike previous implementations, the algorithm can be used not only for a posteriori processing but includes the possibility to perform real time filtering in a data stream. The data base that represents the phase space structure generated by the data is updated dynamically. This also allows filtering of non-stationary signals and dynamic parameter adjustment. We discuss exemplary applications, including the real time extraction of the fetal electrocardiogram from abdominal recordings.
Digital signal processing for fiber nonlinearities [Invited
DEFF Research Database (Denmark)
Cartledge, John C.; Guiomar, Fernando P.; Kschischang, Frank R.
2017-01-01
This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems......This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems...
Comparison between analog and digital filters
Directory of Open Access Journals (Sweden)
Zoltan Erdei
2010-12-01
Full Text Available Digital signal processing(DSP is one of the most powerful technologies and will model science and engineering in the 21st century. Revolutionary changes have already been made in different areas of research such as communications, medical imaging, radar and sonar technology, high fidelity audio signal reproducing etc. Each of these fields developed a different signal processing technology with its own algorithms, mathematics and technology, Digital filters are used in two general directions: to separate mixed signals and to restore signals that were compromised in different modes. The objective of this paper is to compare some basic digital filters versus analog filters such as low-pass, high-pass, band-pass filters. Scientists and engineers comprehend that, in comparison with analog filters, digital filters can process the same signal in real-time with broader flexibility. This understanding is considered important to instill incentive for engineers to become interested in the field of DSP. The analysis of the results will be made using dedicated libraries in MATLAB and Simulink software, such as the Signal Processing Toolbox.
Noise Shaping Filter Compensating PWM Distortion for Fully Digital Amplifier
Yoneya, Akihiko
The full-digital audio amplifiers have several merits such as a high power enabling a small size of the amplifier and digital implementation of the signal processing which allows desired precision of the processing except for the final stage switching amplifiers. Unfortunately, the pulse width modulation (PWM) causes signal distortions because of the non-linearity of the modulation from the viewpoint of the transient response. This paper proposes a compensation method of the PWM distortion with feedback approach. In the noise-shaping filter of the delta-sigma modulator to calculate the pulse codes for the PWM, the distortion caused by the PWM is evaluated and fed it back to compensate the distortion. Eventually the filter is implemented as a state-variable filter with non-linear feedback from the quantizer. The calculation of the filter elements is also described. By using proposed filters, PWM signals with small distortions and small floor noise can be obtained to realize high-fidelity audio amplifiers.
Nonlinear Kalman Filtering in Affine Term Structure Models
DEFF Research Database (Denmark)
Christoffersen, Peter; Dorion, Christian; Jacobs, Kris;
2014-01-01
The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed-income applications. We investigate whether the unscented Kalman filter should be used to capture nonlinearities and compare the performance of the Kalman filter...... with that of the particle filter. We analyze the cross section of swap rates, which are mildly nonlinear in the states, and cap prices, which are highly nonlinear. When caps are used to filter the states, the unscented Kalman filter significantly outperforms its extended counterpart. The unscented Kalman filter also...
Modified nonlinear complex diffusion filter (MNCDF).
Saini, Kalpana; Dewal, M L; Rohit, Manojkumar
2012-06-01
Speckle noise removal is the most important step in the processing of echocardiographic images. A speckle-free image produces useful information to diagnose heart-related diseases. Images which contain low noise and sharp edges are more easily analyzed by the clinicians. This noise removal stage is also a preprocessing stage in segmentation techniques. A new formulation has been proposed for a well-known nonlinear complex diffusion filter (NCDF). Its diffusion coefficient and the time step size are modified to give fast processing and better results. An investigation has been performed among nine patients suffering from mitral regurgitation. Images have been taken with 2D echo in apical and parasternal views. The peak signal-to-noise ratio (PSNR), universal quality index (Qi), mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) have been calculated, and the results show that the proposed method is much better than the previous filters for echocardiographic images. The proposed method, modified nonlinear complex diffusion filter (MNCDF), smooths the homogeneous area and enhances the fine details.
Optimized digital filtering techniques for radiation detection with HPGe detectors
Salathe, Marco; Kihm, Thomas
2016-02-01
This paper describes state-of-the-art digital filtering techniques that are part of GEANA, an automatic data analysis software used for the GERDA experiment. The discussed filters include a novel, nonlinear correction method for ballistic deficits, which is combined with one of three shaping filters: a pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The performance of the filters is demonstrated with a 762 g Broad Energy Germanium (BEGe) detector, produced by Canberra, that measures γ-ray lines from radioactive sources in an energy range between 59.5 and 2614.5 keV. At 1332.5 keV, together with the ballistic deficit correction method, all filters produce a comparable energy resolution of ~1.61 keV FWHM. This value is superior to those measured by the manufacturer and those found in publications with detectors of a similar design and mass. At 59.5 keV, the modified cusp filter without a ballistic deficit correction produced the best result, with an energy resolution of 0.46 keV. It is observed that the loss in resolution by using a constant shaping time over the entire energy range is small when using the ballistic deficit correction method.
Optimized digital filtering techniques for radiation detection with HPGe detectors
Salathe, M
2015-01-01
This paper describes state-of-the-art digital filtering techniques that are part of the tool kit GEANA which is used as a fast automatic data validation tool for the GERDA experiment. The discussed filters include a novel, nonlinear correction method for ballistic deficits, which is combined with one of three shaping filters: the pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The performance of the filters is demonstrated using a 762 g high purity germanium detector that measures gamma-ray lines from radioactive sources in an energy range between 59 and 2615 keV. The modified cusp filter was found to be most optimal for individual gamma-ray lines. Furthermore, it was observed, that even though, the shaping time that minimizes the energy resolution is energy dependent, the loss in resolution by using a constant shaping time over the entire energy range is small, i.e. less than 32 eV for the pseudo-Gaussian filter. This together with good energy resolutions, e.g. 1.59 keV at 1333 keV, this ...
Nonlinear optical properties of induced transmission filters.
Owens, Daniel T; Fuentes-Hernandez, Canek; Hales, Joel M; Perry, Joseph W; Kippelen, Bernard
2010-08-30
The nonlinear optical (NLO) properties of induced transmission filters (ITFs) based on Ag are experimentally determined using white light continuum pump-probe measurements. The experimental results are supported using simulations based on the matrix transfer method. The magnitude of the NLO response is shown to be 30 times that of an isolated Ag film of comparable thickness. The impacts of design variations on the linear and NLO response are simulated. It is shown that the design can be modified to enhance the NLO response of an ITF by a factor of 2 or more over a perfectly matched ITF structure.
Digital Backpropagation in the Nonlinear Fourier Domain
Wahls, Sander; Prilepsky, Jaroslaw E; Poor, H Vincent; Turitsyn, Sergei K
2015-01-01
Nonlinear and dispersive transmission impairments in coherent fiber-optic communication systems are often compensated by reverting the nonlinear Schr\\"odinger equation, which describes the evolution of the signal in the link, numerically. This technique is known as digital backpropagation. Typical digital backpropagation algorithms are based on split-step Fourier methods in which the signal has to be discretized in time and space. The need to discretize in both time and space however makes the real-time implementation of digital backpropagation a challenging problem. In this paper, a new fast algorithm for digital backpropagation based on nonlinear Fourier transforms is presented. Aiming at a proof of concept, the main emphasis will be put on fibers with normal dispersion in order to avoid the issue of solitonic components in the signal. However, it is demonstrated that the algorithm also works for anomalous dispersion if the signal power is low enough. Since the spatial evolution of a signal governed by the ...
Nonlinear Filtering Preserves Chaotic Synchronization via Master-Slave System
Directory of Open Access Journals (Sweden)
J. S. González-Salas
2013-01-01
Full Text Available We present a study on a class of interconnected nonlinear systems and give some criteria for them to behave like a filter. Some chaotic systems present this kind of interconnected nonlinear structure, which enables the synchronization of a master-slave system. Interconnected nonlinear filters have been defined in terms of interconnected nonlinear systems. Furthermore, their behaviors have been studied numerically and theoretically on different input signals.
Filtering Non-Linear Transfer Functions on Surfaces.
Heitz, Eric; Nowrouzezahrai, Derek; Poulin, Pierre; Neyret, Fabrice
2014-07-01
Applying non-linear transfer functions and look-up tables to procedural functions (such as noise), surface attributes, or even surface geometry are common strategies used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient transfer function filtering remains an open problem for several reasons: transfer functions are complex and non-linear, especially when mapped through procedural noise and/or geometry-dependent functions, and the effects of perspective and masking further complicate the filtering over a pixel's footprint. We accurately solve this problem by computing and sampling from specialized filtering distributions on the fly, yielding very fast performance. We investigate the case where the transfer function to filter is a color map applied to (macroscale) surface textures (like noise), as well as color maps applied according to (microscale) geometric details. We introduce a novel representation of a (potentially modulated) color map's distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our approach can be generalized to filter other physical-based rendering quantities. We propose an application to shading with irradiance environment maps over large terrains. Our framework is also compatible with the case of transfer functions used to warp surface geometry, as long as the transformations can be represented with Gaussian statistics, leading to proper view- and light-dependent filtering results. Our results match ground truth and our solution is well suited to real-time applications, requires only a few
Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters
Hoteit, Ibrahim; Pham, Dinh-Tuan
2011-01-01
This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that, the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. We show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an "ensemble of Kalman filters" operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, we consider the construction of the PKF through an "ensemble" of ensemble Kalman filters (EnKFs) instead, ...
Nonlinear filtering properties of detrended fluctuation analysis
Kiyono, Ken; Tsujimoto, Yutaka
2016-11-01
Detrended fluctuation analysis (DFA) has been widely used for quantifying long-range correlation and fractal scaling behavior. In DFA, to avoid spurious detection of scaling behavior caused by a nonstationary trend embedded in the analyzed time series, a detrending procedure using piecewise least-squares fitting has been applied. However, it has been pointed out that the nonlinear filtering properties involved with detrending may induce instabilities in the scaling exponent estimation. To understand this issue, we investigate the adverse effects of the DFA detrending procedure on the statistical estimation. We show that the detrending procedure using piecewise least-squares fitting results in the nonuniformly weighted estimation of the root-mean-square deviation and that this property could induce an increase in the estimation error. In addition, for comparison purposes, we investigate the performance of a centered detrending moving average analysis with a linear detrending filter and sliding window DFA and show that these methods have better performance than the standard DFA.
A new extended H∞ filter for discrete nonlinear systems
Institute of Scientific and Technical Information of China (English)
张永安; 周荻; 段广仁
2004-01-01
Nonlinear estimation problem is investigated in this paper. By extension of a linear H∞ estimation with corrector-predictor form to nonlinear cases, a new extended H∞ filter is proposed for time-varying discretetime nonlinear systems. The new filter has a simple observer structure based on a local linearization model, and can be viewed as a general case of the extended Kalman filter (EKF). An example demonstrates that the new filter with a suitable-chosen prescribed H∞ bound performs better than the EKF.
Double-sideband filter for digital holography
Ramírez, Claudio; Lizana, Angel; Iemmi, Claudio; Campos, Juan
2017-02-01
Nowadays, digital holographic systems are based on two main optical schemes: off-axis (OA) and inline (IL) holographic systems. In OA set-ups, the reference and the object beams present a relative angle at the registration plane. Thus, a real image of the object can be obtained without the influence of conjugated images by performing a spatial filtering at the reconstructed plane. IL configurations are less sensitive to vibrations and air flows than OA configurations, but the undesired influence of conjugated images in the final hologram is not avoided. To overcome this limitation, a number of IL based methods have been proposed. One interesting approach is the phase-shifting technique, which leads to efficient holograms for IL applications. However, due to the time-sequential nature of this technique, it is somewhat inappropriate for dynamic processes. We present a new method, for IL digital holography, based on a doublesideband (DSB) filter. This method not only removes the conjugate images in the reconstruction process but also reduces the distortions that usually appear when using single-sideband filters. Moreover, it is only time-limited by the acquisition time of the CCD camera. The appropriateness of the technique to be applied in dynamic processes was tested for the tracking of micro-particles. To this aim, particle holographic images were obtained by using the DSB method and afterwards processed with digital picture recognition methods, this allowing us to accurately track the spatial position of the particles. By using this approach, the instantaneous trajectory and velocity described by glass microspheres in movement were experimentally determined
Digital filtering of plume emission spectra
Madzsar, George C.
1990-01-01
Fourier transformation and digital filtering techniques were used to separate the superpositioned spectral phenomena observed in the exhaust plumes of liquid propellant rocket engines. Space shuttle main engine (SSME) spectral data were used to show that extraction of spectral lines in the spatial frequency domain does not introduce error, and extraction of the background continuum introduces only minimal error. Error introduced during band extraction could not be quantified due to poor spectrometer resolution. Based on the atomic and molecular species found in the SSME plume, it was determined that spectrometer resolution must be 0.03 nm for SSME plume spectral monitoring.
A digital filter optimization method for low power digital wireless communication system
Tarumi, Kousuke; Tsujimoto, Taizo; Yasuura, Hiroto
2003-01-01
In this paper, we introduce a design method for a low power digital baseband processing circuit. In particular, we focus on a digital FIR(Finite Impulse Response) filter that is a part of the digital baseband processing. Because the digital filter contains large power consuming components, such as adders and multipliers. We propose a design method to reduce power consumption of the digital FIR filter circuit by optimizing bitwidth of inputs of the mutipliers and the adders. We found that the ...
Significance-aware filtering for nonlinear acoustic echo cancellation
Hofmann, Christian; Huemmer, Christian; Guenther, Michael; Kellermann, Walter
2016-12-01
This article summarizes and extends the recently proposed concept of Significance-Aware (SA) filtering for nonlinear acoustic echo cancellation. The core idea of SA filtering is to decompose the estimation of the nonlinear echo path into beneficially interacting subsystems, each of which can be adapted with high computational efficiency. The previously proposed SA Hammerstein Group Models (SA-HGMs) decompose the nonlinear acoustic echo path into a direct-path part, modeled by a Hammerstein Group Model (HGM) and a complementary part, modeled by a very efficient Hammerstein model. In this article, we furthermore propose a novel Equalization-based SA (ESA) structure, where the echo path is equalized by a linear filter to allow for an estimation of the loudspeaker nonlinearities by very small and efficient models. Additionally, we provide a novel in-depth analysis of the computational complexity of the previously proposed SA and the novel ESA filters and compare both SA filtering approaches to each other, to adaptive HGMs, and to linear filters, where fast partitioned-block frequency-domain realizations of the competing filter structures are considered. Finally, the echo reduction performance of the proposed SA filtering approaches is verified using real recordings from a commercially available smartphone. Beyond the scope of previous publications on SA-HGMs, the ability of the SA filters to generalize for double-talk situations is explicitly considered as well. The low complexity as well as the good echo reduction performance of both SA filters illustrate the potential of SA filtering in practice.
Optimal Nonlinear Filter for INS Alignment
Institute of Scientific and Technical Information of China (English)
赵瑞; 顾启泰
2002-01-01
All the methods to handle the inertial navigation system (INS) alignment were sub-optimal in the past. In this paper, particle filtering (PF) as an optimal method is used for solving the problem of INS alignment. A sub-optimal two-step filtering algorithm is presented to improve the real-time performance of PF. The approach combines particle filtering with Kalman filtering (KF). Simulation results illustrate the superior performance of these approaches when compared with extended Kalman filtering (EKF).
The power spectral density of digital modulations transmitted over nonlinear channels
Divsalar, D.; Simon, M. K.
1982-01-01
This paper examines by analytical methods the power spectral densities of digital modulations (in particular, staggered and unstaggered quadrature modulations) passed through band-limited nonlinear channels. Previously observed (by computer simulation or hardware measurement) behavior of such spectra with regard to the suppression or restoration of its sidelobes after passing through the nonlinearity is verified analytically. Several examples corresponding to specific quadrature modulations and filter-nonlinearity combinations are presented as illustrations of the general results.
IMAGE RESTORATION: DESIGN OF NON-LINEAR FILTER (LR
Directory of Open Access Journals (Sweden)
Shenbagarajan Anantharajan
2012-11-01
Full Text Available In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.
Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter
Directory of Open Access Journals (Sweden)
Fariz Outamazirt
2014-09-01
Full Text Available Although nonlinear H∞ (NH∞ filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞ filter is proposed for the Unmanned Aerial Vehicle (UAV localization problem. Based on a real-time Fuzzy Inference System (FIS, the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter.
Nikitin, Alexei V.; Epard, Marc; Lancaster, John B.; Lutes, Robert L.; Shumaker, Eric A.
2012-12-01
A strong digital communication transmitter in close physical proximity to a receiver of a weak signal can noticeably interfere with the latter even when the respective channels are tens or hundreds of megahertz apart. When time domain observations are made in the signal chain of the receiver between the first mixer and the baseband, this interference is likely to appear impulsive. The impulsive nature of this interference provides an opportunity to reduce its power by nonlinear filtering, improving the quality of the receiver channel. This article describes the mitigation, by a particular nonlinear filter, of the impulsive out-of-band (OOB) interference induced in High Speed Downlink Packet Access (HSDPA) by WiFi transmissions, protocols which coexist in many 3G smartphones and mobile hotspots. Our measurements show a decrease in the maximum error-free bit rate of a 1.95 GHz HSDPA receiver caused by the impulsive interference from an OOB 2.4 GHz WiFi transmission, sometimes down to a small fraction of the rate observed in the absence of the interference. We apply a nonlinear SPART filter to recover a noticeable portion of the lost rate and maintain an error-free connection under much higher levels of the WiFi interference than a receiver that does not contain such a filter. These measurements support our wider investigation of OOB interference resulting from digital modulation, which appears impulsive in a receiver, and its mitigation by nonlinear filters.
Tunable photonic filters: a digital signal processing design approach.
Binh, Le Nguyen
2009-05-20
Digital signal processing techniques are used for synthesizing tunable optical filters with variable bandwidth and centered reference frequency including the tunability of the low-pass, high-pass, bandpass, and bandstop optical filters. Potential applications of such filters are discussed, and the design techniques and properties of recursive digital filters are outlined. The basic filter structures, namely, the first-order all-pole optical filter (FOAPOF) and the first-order all-zero optical filter (FOAZOF), are described, and finally the design process of tunable optical filters and the designs of the second-order Butterworth low-pass, high-pass, bandpass, and bandstop tunable optical filters are presented. Indeed, we identify that the all-zero and all-pole networks are equivalent with well known principles of optics of interference and resonance, respectively. It is thus very straightforward to implement tunable optical filters, which is a unique feature.
Nonlinear Adaptive Filter for MEMS Gyro Error Cancellation Project
National Aeronautics and Space Administration — The Nonlinear adaptive filters (NAF) can learn deterministic gyro errors and cancel the error’s effect from attitude estimates. By completely canceling...
Parallel digital modem using multirate digital filter banks
Sadr, Ramin; Vaidyanathan, P. P.; Raphaeli, Dan; Hinedi, Sami
1994-01-01
A new class of architectures for an all-digital modem is presented in this report. This architecture, referred to as the parallel receiver (PRX), is based on employing multirate digital filter banks (DFB's) to demodulate, track, and detect the received symbol stream. The resulting architecture is derived, and specifications are outlined for designing the DFB for the PRX. The key feature of this approach is a lower processing rate then either the Nyquist rate or the symbol rate, without any degradation in the symbol error rate. Due to the freedom in choosing the processing rate, the designer is able to arbitrarily select and use digital components, independent of the speed of the integrated circuit technology. PRX architecture is particularly suited for high data rate applications, and due to the modular structure of the parallel signal path, expansion to even higher data rates is accommodated with each. Applications of the PRX would include gigabit satellite channels, multiple spacecraft, optical links, interactive cable-TV, telemedicine, code division multiple access (CDMA) communications, and others.
Federated nonlinear predictive filtering for the gyroless attitude determination system
Zhang, Lijun; Qian, Shan; Zhang, Shifeng; Cai, Hong
2016-11-01
This paper presents a federated nonlinear predictive filter (NPF) for the gyroless attitude determination system with star sensor and Global Positioning System (GPS) sensor. This approach combines the good qualities of both the NPF and federated filter. In order to combine them, the equivalence relationship between the NPF and classical Kalman filter (KF) is demonstrated from algorithm structure and estimation criterion. The main features of this approach include a nonlinear predictive filtering algorithm to estimate uncertain model errors and determine the spacecraft attitude by using attitude kinematics and dynamics, and a federated filtering algorithm to process measurement data from multiple attitude sensors. Moreover, a fault detection and isolation algorithm is applied to the proposed federated NPF to improve the estimation accuracy even when one sensor fails. Numerical examples are given to verify the navigation performance and fault-tolerant performance of the proposed federated nonlinear predictive attitude determination algorithm.
Khairuzzaman, Md; Zhang, Chao; Igarashi, Koji; Katoh, Kazuhiro; Kikuchi, Kazuro
2010-03-01
We describe a successful introduction of maximum-likelihood-sequence estimation (MLSE) into digital coherent receivers together with finite-impulse response (FIR) filters in order to equalize both linear and nonlinear fiber impairments. The MLSE equalizer based on the Viterbi algorithm is implemented in the offline digital signal processing (DSP) core. We transmit 20-Gbit/s quadrature phase-shift keying (QPSK) signals through a 200-km-long standard single-mode fiber. The bit-error rate performance shows that the MLSE equalizer outperforms the conventional adaptive FIR filter, especially when nonlinear impairments are predominant.
Digital Communications Using Chaos and Nonlinear Dynamics
Larson, Lawrence E; Liu, Jia-Ming
2006-01-01
This book introduces readers to a new and exciting cross-disciplinary field of digital communications with chaos. This field was born around 15 years ago, when it was first demonstrated that nonlinear systems which produce complex non-periodic noise-like chaotic signals, can be synchronized and modulated to carry useful information. Thus, chaotic signals can be used instead of pseudo-random digital sequences for spread-spectrum and private communication applications. This deceptively simple idea spun hundreds of research papers, and many novel communication schemes based on chaotic signals have been proposed. However, only very recently researchers have begun to make a transition from academic studies toward practical implementation issues, and many "promising" schemes had to be discarded or re-formulated. This book describes the state of the art (both theoretical and experimental) of this novel field. The book is written by leading experts in the fields of Nonlinear Dynamics and Electrical Engineering who pa...
Nonlinear H∞ filtering for interconnected Markovian jump systems
Institute of Scientific and Technical Information of China (English)
Zhang Xiaomei; Zheng Yufan
2006-01-01
The problem of nonlinear H∞ filtering for interconnected Markovian jump systems is discussed. The aim of this note is the design of a nonlinear Markovian jump filter such that the resulting error system is exponentially meansquare stable and ensures a prescribed H∞ performance. A sufficient condition for the solvability of this problem is given in terms of linear matrix inequalities(LMIs). A simulation example is presented to demonstrate the effectiveness of the proposed design approach.
On filter-successive linearization methods for nonlinear semidefinite programming
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially effcient.
On filter-successive linearization methods for nonlinear semidefinite programming
Institute of Scientific and Technical Information of China (English)
LI ChengJin; SUN WenYui
2009-01-01
In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially efficient.
Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters*
Hoteit, Ibrahim
2012-02-01
This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. The authors show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an “ensemble of Kalman filters” operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, the authors consider the construction of the PKF through an “ensemble” of ensemble Kalman filters (EnKFs) instead, and call the implementation the particle EnKF (PEnKF). It is shown that different types of the EnKFs can be considered as special cases of the PEnKF. Similar to the situation in the particle filter, the authors also introduce a resampling step to the PEnKF in order to reduce the risk of weights collapse and improve the performance of the filter. Numerical experiments with the strongly nonlinear Lorenz-96 model are presented and discussed.
Low Power Systolic Array Based Digital Filter for DSP Applications
Directory of Open Access Journals (Sweden)
S. Karthick
2015-01-01
Full Text Available Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.
Low Power Systolic Array Based Digital Filter for DSP Applications.
Karthick, S; Valarmathy, S; Prabhu, E
2015-01-01
Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP) based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.
A Novel Analog-to-digital conversion Technique using nonlinear duty-cycle modulation
Directory of Open Access Journals (Sweden)
Jean Mbihi
2012-06-01
Full Text Available A new type of analog-to-digital conversion technique is presented in this paper. The interfacing hardware is a very simple nonlinear circuit with 1-bit modulated output. As a implication, behind the hardware simplicity retained is hidden a dreadful nonlinear duty-cycle modulation ratio. However, the overall nonlinear behavior embeds a sufficiently wide linear range, for a rigorous digital reconstitution of the analog input signal using a standard linear filter. Simulation and experimental results obtained using a well tested prototyping system, show the feasibility and good quality of the proposed conversion technique.
Noise and resolution with digital filtering for nuclear spectrometry
Energy Technology Data Exchange (ETDEWEB)
Lakatos, T. (Inst. of Nuclear Research, Hungarian Academy of Sciences, Debrecen (Hungary))
1991-12-01
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.).
Noise and resolution with digital filtering for nuclear spectrometry
Lakatos, T.
1991-12-01
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 deals with the investigation of these effects using computer modelling.
Nonlinear Kalman filtering in the presence of additive noise
Kraszewski, Tomasz; Czopik, Grzegorz
2017-04-01
Each modern navigation or localization system designed for ground, water or air objects should provide information on the estimated parameters continuously and as accurately as possible. The implementation of such a process requires the application to operate on non-linear transformations. The defined expectations necessitate the use of nonlinear filtering elements with particular emphasis on the extended Kalman filter. The article presents the simulation research elements of this filter type in the aspect of the possibility of its practical implementation. In the initial phase of the study the conclusion was based on nonlinear one-dimensional model. The possibility of improving the precision of the output through the use of unscented Kalman filters was also analyzed.
DIGITAL FILTERS IMPLEMENTATION IN MICROPROCESSOR-BASED RELAY PROTECTION
Directory of Open Access Journals (Sweden)
Yu. V. Rumiantsev
2016-01-01
Full Text Available This article presents the implementation of digital filters used in digital relay protection current measuring elements. Mathematical descriptions of the considered digital filters as well as the computer programs for their coefficients calculation are described. It has been shown that in order to reliable estimate the digital filter performance its input signals waveforms must be close to the actual secondary current waveform of the current transformer to which the digital protection with the estimated digital filter is connected. For these purposes in MatLab–Simulink dynamic simulation environment the power system and the current measuring element models were developed. Performed calculations allowed to reveal that the exponentially decaying DC component which in some cases contains in primary fault current drives the current transformer core into saturation even when its nominal parameters are not exceeded. This results in distortion of the current transformer secondary current which in this case contains higher and inter-harmonics. Moreover, such harmonic content is not completely taking into account during coefficients calculation of the considered digital filters what results in signal magnitude estimation inaccuracy. Comparison of the digital filters response to the above-mentioned input signals allowed to find out such digital filter implementations which enable signal magnitude estimation with a minimum error. Ways of filtering quality improvement concerned with the window functions are proposed. Thus, the joint usage of digital filter and Hamming window allows to achieve the zero value of the signal magnitude gain factor in high-frequency range and substantially suppress all spectral components above 100 Hz. The increasing of the signal magnitude settling time in this case can be reduced by choosing the most optimal parameters of the all components of the current measuring element.
Algorithm for Design of Digital Notch Filter Using Simulation
Directory of Open Access Journals (Sweden)
Amit Verma
2013-08-01
Full Text Available A smooth waveform is generated of low frequency signal can be achieved through the Digital Notch Filter. Noise can be easily eliminated from a speech signal by using a Notch filter. In this paper the design of notch filter using MATLAB has been designed and implemented. The performance and characteristics of the filter has been shown in the waveform in the conclusion part of the paper.
Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics
Institute of Scientific and Technical Information of China (English)
Zhaoxia PU; Joshua HACKER
2009-01-01
This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.
Implementasi Order-Statistic Filters Untuk Mereduksi Noise Pada Citra Digital
Sihotang, Juni Santo
2014-01-01
Salt-and-pepper Noise or Gaussian Noise is noise there is usually found in digital images. Noise on the image usually occurs due to errors in image acquisition technique or because the image has been stored too long. To reduce noise we need a proper filter method so that the image resulted in accordance with the original. Order-Statistic Filters method is a non-linear filter whose results determined in accordance with the sorting image pixels that fil the area that are in the scope of the fil...
Non-linear DSGE Models and The Optimized Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper improves the accuracy and speed of particle filtering for non-linear DSGE models with potentially non-normal shocks. This is done by introducing a new proposal distribution which i) incorporates information from new observables and ii) has a small optimization step that minimizes...... the distance to the optimal proposal distribution. A particle filter with this proposal distribution is shown to deliver a high level of accuracy even with relatively few particles, and this filter is therefore much more efficient than the standard particle filter....
A digital filter for an analog-digital converter with delta-sigma modulation
Beliavskaia, T. G.; Levchuk, Iu. P.; Strigina, E. V.
1986-05-01
Various methods of implementing the digital versions of analog-digital converters are examined, with attention given to homogeneous, triangular, and low-frequency digital filters. A comparison of the implementations proposed here makes it possible to optimize the structure of an analog-digital converter with respect to the hardware costs depending on the required accuracy.
APPLICATION OF NONLINEAR WATERMARK TECHNIQUES IN DIGITAL LIBRARIES
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
A digital watermark is an invisible mark embedded in a digital image that may be used for a number of different purposes including copyright protection. Due to the urgent need for protecting the copyright of digital products in digital library, digital watermarking has been proposed as a solution to this problem. This letter describes potential situations that nonlinear theory can be used to enhance robustness and security of the watermark in digital library. Some nonlinear watermark techniques have been enumerated. Experimental results show that the proposed scheme is superior to the general watermark scheme both in security and robustness in digital library.
Nonlinear filtering in ECG Signal Enhancement
Directory of Open Access Journals (Sweden)
N. Siddiah
2012-02-01
Full Text Available High resolution ECG signals are needed in measuring cardiac abnormalities analysis. Generally baseline wander is one of the important artifact occurred in ECG signal extraction, this strongly affects the signal quality. In order to facilitate proper diagnosis these artifacts have to be removed. In this paper various non linear, non adaptive filtering techniques are presented for the removal of baseline wander removal from ECG signals. The performance characteristics of various filtering techniques are measured in terms of signal to noise ratio.
Nonlinear dynamical system identification using unscented Kalman filter
Rehman, M. Javvad ur; Dass, Sarat Chandra; Asirvadam, Vijanth Sagayan
2016-11-01
Kalman Filter is the most suitable choice for linear state space and Gaussian error distribution from decades. In general practical systems are not linear and Gaussian so these assumptions give inconsistent results. System Identification for nonlinear dynamical systems is a difficult task to perform. Usually, Extended Kalman Filter (EKF) is used to deal with non-linearity in which Jacobian method is used for linearizing the system dynamics, But it has been observed that in highly non-linear environment performance of EKF is poor. Unscented Kalman Filter (UKF) is proposed here as a better option because instead of analytical linearization of state space, UKF performs statistical linearization by using sigma point calculated from deterministic samples. Formation of the posterior distribution is based on the propagation of mean and covariance through sigma points.
Development and applications of an interactive digital filter design program.
Woo, H W; Kim, Y M; Tompkins, W J
1985-10-01
We have implemented an interactive digital filter design program in the HP 1000 computer at the Department of Electrical Engineering of the University of Washington. This program allows users to design different types of filters interactively with both amplitude and phase responses displayed on graphic devices. The performance of each designed filter can be evaluated conveniently before the best one is chosen and implemented for any particular application. This program can design recursive filters, e.g. Butterworth, Chebyshev and elliptic, or nonrecursive filters with one out of six different windows, i.e. rectangular, triangular, Hann, Hamming, Blackman and Kaiser. The main outputs from this program are coefficients of a transfer function of an analog filter, a digital filter, or both. Therefore, the design of both analog and digital filters is facilitated by using this program. The program is very simple to use and does not require background in analog or digital filter principles in order to run it. The program is written in standard FORTRAN and is about 30 kbytes in size excluding the graphics display routines. Since it uses standard FORTRAN, it can be easily transported to minicomputer and microcomputer systems that have a FORTRAN compiler and minimal graphics capabilities. This program is available for distribution to interested institutions and laboratories.
Non-linear and signal energy optimal asymptotic filter design
Directory of Open Access Journals (Sweden)
Josef Hrusak
2003-10-01
Full Text Available The paper studies some connections between the main results of the well known Wiener-Kalman-Bucy stochastic approach to filtering problems based mainly on the linear stochastic estimation theory and emphasizing the optimality aspects of the achieved results and the classical deterministic frequency domain linear filters such as Chebyshev, Butterworth, Bessel, etc. A new non-stochastic but not necessarily deterministic (possibly non-linear alternative approach called asymptotic filtering based mainly on the concepts of signal power, signal energy and a system equivalence relation plays an important role in the presentation. Filtering error invariance and convergence aspects are emphasized in the approach. It is shown that introducing the signal power as the quantitative measure of energy dissipation makes it possible to achieve reasonable results from the optimality point of view as well. The property of structural energy dissipativeness is one of the most important and fundamental features of resulting filters. Therefore, it is natural to call them asymptotic filters. The notion of the asymptotic filter is carried in the paper as a proper tool in order to unify stochastic and non-stochastic, linear and nonlinear approaches to signal filtering.
Approximations and Implementations of Nonlinear Filtering Schemes.
1988-02-01
SYSTEMS 13/14 (Blank) JP{ I LDMX MAJ=V AMOnUXIO rOQO v F 3LES LXIMKR STOCASTIC STSTEN A. a. Uaded an L 1. Verriest School of flectrical Engineering...1975. (15] P. G. Hoel , S. C. Port, and C. J. Stone, "Introduction to Stochastic Processes", Houghton Mifflin Co., 1972. (161 A. Isidori, "Nonlinear
A Filter Method for Nonlinear Semidefinite Programming with Global Convergence
Institute of Scientific and Technical Information of China (English)
Zhi Bin ZHU; Hua Li ZHU
2014-01-01
In this study, a new filter algorithm is presented for solving the nonlinear semidefinite programming. This algorithm is inspired by the classical sequential quadratic programming method. Unlike the traditional filter methods, the suffi cient descent is ensured by changing the step size instead of the trust region radius. Under some suitable conditions, the global convergence is obtained. In the end, some numerical experiments are given to show that the algorithm is eff ective.
Filtering nonlinear dynamical systems with linear stochastic models
Harlim, J.; Majda, A. J.
2008-06-01
An important emerging scientific issue is the real time filtering through observations of noisy signals for nonlinear dynamical systems as well as the statistical accuracy of spatio-temporal discretizations for filtering such systems. From the practical standpoint, the demand for operationally practical filtering methods escalates as the model resolution is significantly increased. For example, in numerical weather forecasting the current generation of global circulation models with resolution of 35 km has a total of billions of state variables. Numerous ensemble based Kalman filters (Evensen 2003 Ocean Dyn. 53 343-67 Bishop et al 2001 Mon. Weather Rev. 129 420-36 Anderson 2001 Mon. Weather Rev. 129 2884-903 Szunyogh et al 2005 Tellus A 57 528-45 Hunt et al 2007 Physica D 230 112-26) show promising results in addressing this issue; however, all these methods are very sensitive to model resolution, observation frequency, and the nature of the turbulent signals when a practical limited ensemble size (typically less than 100) is used. In this paper, we implement a radical filtering approach to a relatively low (40) dimensional toy model, the L-96 model (Lorenz 1996 Proc. on Predictability (ECMWF, 4-8 September 1995) pp 1-18) in various chaotic regimes in order to address the 'curse of ensemble size' for complex nonlinear systems. Practically, our approach has several desirable features such as extremely high computational efficiency, filter robustness towards variations of ensemble size (we found that the filter is reasonably stable even with a single realization) which makes it feasible for high dimensional problems, and it is independent of any tunable parameters such as the variance inflation coefficient in an ensemble Kalman filter. This radical filtering strategy decouples the problem of filtering a spatially extended nonlinear deterministic system to filtering a Fourier diagonal system of parametrized linear stochastic differential equations (Majda and Grote
Nonlinear Principal Component Analysis Using Strong Tracking Filter
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive leastsquares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.
Digital simulation and modeling of nonlinear stochastic systems
Energy Technology Data Exchange (ETDEWEB)
Richardson, J M; Rowland, J R
1981-04-01
Digitally generated solutions of nonlinear stochastic systems are not unique but depend critically on the numerical integration algorithm used. Some theoretical and practical implications of this dependence are examined. The Ito-Stratonovich controversy concerning the solution of nonlinear stochastic systems is shown to be more than a theoretical debate on maintaining Markov properties as opposed to utilizing the computational rules of ordinary calculus. The theoretical arguments give rise to practical considerations in the formation and solution of discrete models from continuous stochastic systems. Well-known numerical integration algorithms are shown not only to provide different solutions for the same stochastic system but also to correspond to different stochastic integral definitions. These correspondences are proved by considering first and second moments of solutions that result from different integration algorithms and then comparing the moments to those arising from various stochastic integral definitions. This algorithm-dependence of solutions is in sharp contrast to the deterministic and linear stochastic cases in which unique solutions are determined by any convergent numerical algorithm. Consequences of the relationship between stochastic system solutions and simulation procedures are presented for a nonlinear filtering example. Monte Carlo simulations and statistical tests are applied to the example to illustrate the determining role which computational procedures play in generating solutions.
Digital simulation and modeling of nonlinear stochastic systems
Energy Technology Data Exchange (ETDEWEB)
Richardson, J M; Rowland, J R
1980-01-01
Digitally generated solutions of nonlinear stochastic systems are not unique, but depend critically on the numerical integration algorithm used. Some theoretical and practical implications of this dependence are examined. The Ito-Stratonovich controversy concerning the solution of nonlinear stochastic systems is shown to be more than a theoretical debate on maintaining Markov properties as opposed to utilizing the computational rules of ordinary calculus. The theoretical arguments give rise to practical considerations in the formation and solution of discrete models from continuous stochastic systems. Well-known numerical integration algorithms are shown not only to provide different solutions for the same stochastic system, but also to correspond to different stochastic integral definitions. These correspondences are proved by considering first and second moments of solutions resulting from different integration algorithms and comparing the moments to those arising from various stochastic integral definitions. Monte Carlo simulations and statistical tests are applied to illustrate the determining role that computational procedures play in generating solutions. This algorithm dependence of solutions is in sharp contrast to the deterministic and linear stochastic cases, in which unique solutions are determined by any convergent numerical algorithm. Consequences of this relationship between stochastic system solutions and simulation procedures are presented for a nonlinear filtering example. 2 figures.
Digital notch filter based active damping for LCL filters
DEFF Research Database (Denmark)
Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin
2015-01-01
. In contrast, the active damping does not require any dissipation elements, and thus has become of increasing interest. As a result, a vast of active damping solutions have been reported, among which multi-loop control systems and additional sensors are necessary, leading to increased cost and complexity....... In this paper, a notch filter based active damping without the requirement of additional sensors is proposed, where the inverter current is employed as the feedback variable. Firstly, a design method of the notch filter for active damping is presented. The entire system stability has then been investigated...... in the z-domain. Simulations and experiments are carried out to verify the proposed active damping method. Both results have confirmed that the notch filter based active damping can ensure the entire system stability in the case of resonances with a good system performance....
Weighted adaptive spatial filtering in digital holographic microscopy
Hong, Yuan; Shi, Tielin; Wang, Xiao; Zhang, Yichun; Chen, Kepeng; Liao, Guanglan
2017-01-01
Spatial filtering, a key point to realize real-time measurement, is used commonly in digital off-axis holography to extract desired terms. In this paper, we propose a weighted adaptive spatial filtering method by weighting the adaptive filtering window (obtained from image segmentation) based on signal to noise ratio. The advantages of this method are evaluated by simulations and further verified by recorded digital image plane holograms. The results demonstrate that our method is effective in suppressing noise and retaining the sharp edges in the reconstructed 3D profiles.
Nonlinear projective filtering; 1, Application to real time series
Schreiber, T
1998-01-01
We discuss applications of nonlinear filtering of time series by locally linear phase space projections. Noise can be reduced whenever the error due to the manifold approximation is smaller than the noise in the system. Examples include the real time extraction of the fetal electrocardiogram from abdominal recordings.
Linear and nonlinear filters under high power microwave conditions
Directory of Open Access Journals (Sweden)
F. Brauer
2009-05-01
Full Text Available The development of protection circuits against a variety of electromagnetic disturbances is important to assure the immunity of an electronic system. In this paper the behavior of linear and nonlinear filters is measured and simulated with high power microwave (HPM signals to achieve a comprehensive protection against different high power electromagnetic (HPEM threats.
Howarth, Samuel J; Callaghan, Jack P
2009-10-01
The influence of signal sampling frequency and the low-pass digital filter cutoff frequency on the minimum number of padding points when applied to kinematic data are factors often absent in data processing descriptions. This investigation determined a relationship between the number of padding points and the ratio of filter cutoff to signal sampling frequencies (f(c)/f(s)). Two kinematic recordings were used which represented signals with high and low deterministic variation magnitudes at the signals' beginning. Signal sampling rates (40-128 Hz) were generated at intervals of 1 Hz. Filter cutoff frequency was iterated from 2 to 10 Hz at 0.5 Hz intervals. Data extrapolation was performed using three different techniques (first order polynomial, third order polynomial, and data reflection). A maximum of 2s of padding points were added to the beginning of each test signal which was then dual-pass filtered using a second order Butterworth filter. For each successive increase in the number of padding points, the filtered test signal was compared to a criterion signal and the root mean square difference (RMSD) over the first second was calculated. The number of padding points required to attain a constant RMSD was recorded as the minimum number of padding points needed for that ratio of filter cutoff to sampling frequency. As f(c)/f(s) increased, the number of padding points decreased non-linearly. More padding points were required for the signal with higher deterministic variation at the beginning than the signal with lower deterministic variation. Additional padding points (beyond the determined minimum) did not further reduce the RMSD. The largest temporal extrapolation determined by the algorithm to produce a stable RMSD was 1s. It is suggested that a minimum of 1s of extraneous data be used when using a low-pass recursive digital filter to remove noise from kinematic data.
Nonlinear Statistical Signal Processing: A Particle Filtering Approach
Energy Technology Data Exchange (ETDEWEB)
Candy, J
2007-09-19
A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations.
Stent enhancement in digital x-ray fluoroscopy using an adaptive feature enhancement filter
Jiang, Yuhao; Zachary, Josey
2016-03-01
Fluoroscopic images belong to the classes of low contrast and high noise. Simply lowering radiation dose will render the images unreadable. Feature enhancement filters can reduce patient dose by acquiring images at low dose settings and then digitally restoring them to the original quality. In this study, a stent contrast enhancement filter is developed to selectively improve the contrast of stent contour without dramatically boosting the image noise including quantum noise and clinical background noise. Gabor directional filter banks are implemented to detect the edges and orientations of the stent. A high orientation resolution of 9° is used. To optimize the use of the information obtained from Gabor filters, a computerized Monte Carlo simulation followed by ROC study is used to find the best nonlinear operator. The next stage of filtering process is to extract symmetrical parts in the stent. The global and local symmetry measures are used. The information gathered from previous two filter stages are used to generate a stent contour map. The contour map is then scaled and added back to the original image to get a contrast enhanced stent image. We also apply a spatio-temporal channelized Hotelling observer model and other numerical measures to characterize the response of the filters and contour map to optimize the selections of parameters for image quality. The results are compared to those filtered by an adaptive unsharp masking filter previously developed. It is shown that stent enhancement filter can effectively improve the stent detection and differentiation in the interventional fluoroscopy.
Exploiting nonlinearities of micro-machined resonators for filtering applications
Ilyas, Saad
2017-06-21
We demonstrate the exploitation of the nonlinear behavior of two electrically coupled microbeam resonators to realize a band-pass filter. More specifically, we combine their nonlinear hardening and softening responses to realize a near flat pass band filter with sharp roll-off characteristics. The device is composed of two near identical doubly clamped and electrostatically actuated microbeams made of silicon. One of the resonators is buckled via thermal loading to produce a softening frequency response. It is then further tuned to create the desired overlap with the second resonator response of hardening behavior. This overlapping improves the pass band flatness. Also, the sudden jumps due to the softening and hardening behaviors create sharp roll-off characteristics. This approach can be promising for the future generation of filters with superior characteristics.
Personalized Service System Based on Hybrid Filtering for Digital Library
Institute of Scientific and Technical Information of China (English)
GAO Fengrong; XING Chunxiao; DU Xiaoyong; WANG Shan
2007-01-01
Personalized service systems are an effective way to help users obtain recommendations for unseen items, within the enormous volume of information available based on their preferences. The most commonly used personalized service system methods are collaborative filtering, content-based filtering, and hybrid filtering. Unfortunately,each method has its drawbacks. This paper proposes a new method which unified partition-based collaborative filtering and meta-information filtering.In partition-based collaborative filtering the user-item rating matrix can be partitioned into low-dimensional dense materces using a matrixclustering algorithm. Recommendations are generated based on these low-dimensional matrices.Additionally,the very low ratings problem can be solved using meta-information filtering. The unified method is applied to a digital resource management system. The experimental results show the high efficiency and good performance of the new approach.
Cost Analysis of Different Digital Fir Filter Design Methods
Directory of Open Access Journals (Sweden)
Amninder Singh,
2014-05-01
Full Text Available FIR digital filters are widely used in the communication world. The implementation cost of filter circuit is counted by the number of multipliers & adders used, that decides the chip area. In this paper, design techniques of low pass FIR filter using the different windows are presented. The simulation is done in MATLAB. It is shown that filter designed using Hamming and Blackman windows are better than rest of the windows used. Out of two, Hamming window is better as its transition width is narrow, 0.019 than Blackman, 0.034. Further the performance analysis of Kaiser Window, Equiripple and Minimum phase filters was obtained, for same 0.04 transition width. There is a disparity in implementation cost & area. The minimum phase filter can be implemented with lesser number of filter coefficients with tolerable pass-band, stop-band ripples specifications.
A Girsanov particle filter in nonlinear engineering dynamics
Energy Technology Data Exchange (ETDEWEB)
Saha, Nilanjan [Structures Lab, Department of Civil Engineering, Indian Institute of Science, Bangalore-560012 (India); Roy, D. [Structures Lab, Department of Civil Engineering, Indian Institute of Science, Bangalore-560012 (India)], E-mail: royd@civil.iisc.ernet.in
2009-02-02
In this Letter, we propose a novel variant of the particle filter (PF) for state and parameter estimations of nonlinear engineering dynamical systems, modelled through stochastic differential equations (SDEs). The aim is to address a possible loss of accuracy in the estimates due to the discretization errors, which are inevitable during numerical integration of the SDEs. In particular, we adopt an explicit local linearization of the governing nonlinear SDEs and the resulting linearization errors in the estimates are corrected using Girsanov transformation of measures. Indeed, the linearization scheme via transformation of measures provides a weak framework for computing moments and this fits in well with any stochastic filtering strategy wherein estimates are themselves statistical moments. We presently implement the strategy using a bootstrap PF and numerically illustrate its performance for state and parameter estimations of the Duffing oscillator with linear and nonlinear measurement equations.
Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Du, Wei
2012-01-01
Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive.
Directory of Open Access Journals (Sweden)
Wei Wang
2014-05-01
Full Text Available Hybrid filter bank (HFB analog-to-digital systems permit wideband, high frequency conversion. This paper presents mixed norm optimal design of digital synthesis filters of a HFB. The mixed norm is a convex combination of the 2-norm and the Chebyshev norm with a weighting parameter. Robust HFB design method based on worst-case ellipsoidal uncertainty in analog filters errors is also proposed. Both the problems can be solved using semidefinite programming. The proposed mixed norm method allows designers to select the best suitable filters among a family of synthesis filters for specific applications, and the robust design method is more insensitive to analog filters errors than the nominal minimax design
A fast n-dimensional nonlinear filter
Tremblais, Benoit; Augereau, Bertrand
2004-05-01
In this communication, we propose an original approach for the diffusion paradigm in image processing. Our starting point is the iterative resolution of partial differential equations (PDE) according to the explicit resolution scheme. We simply consider that this iterative process is nothing but a fixed point search. So we obtain a convergence condition which applies to a large set of image processing PDE. That allows to introduce a new smoothing process with strong abilities to preserve any structure of interest in the images. As an example we choose a linear isotropic diffusion for the denoising performances. Thus while resolving the equation of isotropic diffusion and by using an adaptive resolution parameter, we obtain a filtering process which can preserve arbitrary dimension object edges as one-dimensional signals, gray level images, color images, volumes, films, etc. We show the edge localization preserving property of the process. And we compare the complexity of the process with the Perona and Malik explicit scheme, and the Weickert AOS scheme. We establish that the computational effort of our scheme is lower than this of the two others. For illustration, we apply this new process to denoising of different kinds of medical images.
The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics
Zhu, Yanqiu; Cohn, Stephen E.; Todling, Ricardo
1999-01-01
The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.
Digital filters in radio detectors of the Pierre Auger Observatory
Szadkowski, Zbigniew; Głas, Dariusz
2016-09-01
Ultra-high energy cosmic rays (UHECR) are the most energetic observable particles in Universe. The main challenge in detecting such energetic particles is very small flux. Most experiments focus on detecting Extensive Air Showers (EAS), initiated by primary UHECR particle in interaction with particles of the atmosphere. One of the observation method is detecting the radio emission from the EAS. This emission was theoretically suggested in 1960's, but technological development allow successful detection only in the last several years. This detection technique is used by Auger Engineering Radio Array (AERA). Most of the emission can be observed in frequency band 30 - 80 MHz, however this range is contaminated by radio frequency interferences (RFI). These contaminations must be reduced to decrease false trigger rate. Currently, there are two kind of digital filters used in AERA. One of them is median filter, based on Fast Fourier Transform. Second one is the notch filter, which is a composition of four infinite impulse response filters. Those filters have properly work in AERA radio detectors for many years. Dynamic progress in electronics allows to use more sophisticated algorithms of RFI reduction. Planned modernization of the AERA radio detectors' electronic allows to use finte impulse response (FIR) filters, which can fast adapt to environment conditions. These filters are: Least Mean Squares (LMS) filter and filter based on linear prediction (LP). Tests of new kind of filters are promising and show that FIR filters can be used in next generation radio detectors in AERA experiment.
Modified unscented particle filter for nonlinear Bayesian tracking
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A modified unscented particle filtering scheme for nonlinear tracking is proposed,in view of the potential drawbacks (such as,particle impoverishment and numerical sensitivity in calculating the prior) of the conventional unscented particle filter (UPF) confronted in practice.Specifically,a different derivation of the importance weight is presented in detail.The proposed method can avoid the calculation of the prior and reduce the effects of the impoverishment problem caused by sampling from the proposal distribution.Simulations have been performed using two illustrative examples and results have been provided to demonstrate the validity of the modified UPF as well as its improved performance over the conventional one.
A neural architecture for nonlinear adaptive filtering of time series
DEFF Research Database (Denmark)
Hoffmann, Nils; Larsen, Jan
1991-01-01
A neural architecture for adaptive filtering which incorporates a modularization principle is proposed. It facilitates a sparse parameterization, i.e. fewer parameters have to be estimated in a supervised training procedure. The main idea is to use a preprocessor which determines the dimension...... of the input space and can be designed independently of the subsequent nonlinearity. Two suggestions for the preprocessor are presented: the derivative preprocessor and the principal component analysis. A novel implementation of fixed Volterra nonlinearities is given. It forces the boundedness...
Design and Analysis of Robust Active Damping for LCL Filters using Digital Notch Filters
DEFF Research Database (Denmark)
Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin;
2017-01-01
Resonant poles of LCL filters may challenge the entire system stability especially in digital-controlled Pulse Width Modulation (PWM) inverters. In order to tackle the resonance issues, many active damping solutions have been reported. For instance, a notch filter can be employed to damp the reso......Resonant poles of LCL filters may challenge the entire system stability especially in digital-controlled Pulse Width Modulation (PWM) inverters. In order to tackle the resonance issues, many active damping solutions have been reported. For instance, a notch filter can be employed to damp...... the resonance, where the notch frequency should be aligned exactly to the resonant frequency of the LCL filter. However, parameter variations of the LCL filter as well as the time delay appearing in digital control systems will induce resonance drifting, and thus break this alignment, possibly deteriorating...... the original damping. In this paper, the effectiveness of the notch filter based active damping is firstly explored, considering the drifts of the resonant frequency. It is revealed that, when the resonant frequency drifts away from its nominal value, the phase lead or lag introduced by the notch filter may...
Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper shows how non-linear DSGE models with potential non-normal shocks can be estimated by Quasi-Maximum Likelihood based on the Central Difference Kalman Filter (CDKF). The advantage of this estimator is that evaluating the quasi log-likelihood function only takes a fraction of a second. T...
Design of Absorbing Wave Maker based on Digital Filters
DEFF Research Database (Denmark)
Christensen, Morten; Frigaard, Peter
An absorbing wave maker operated by means of on-line signals from digital FIR filters is presented. Surface elevations are measured in two positions in front of the wave maker. The reflected wave train is seperated by the sum of the incident and reflected wave trains by means of digital filtering...... and subsequent superposition of the measured surface elevations. The motion of the wave paddle required to absorb reflected waves is determined and added to the original wave paddle control signal. Irregular wave tests involving test structures with different degrees of reflection show that excellent absorption...
A Particle Filtering Approach to Change Detection for Nonlinear Systems
Directory of Open Access Journals (Sweden)
P. S. Krishnaprasad
2004-11-01
Full Text Available We present a change detection method for nonlinear stochastic systems based on particle filtering. We assume that the parameters of the system before and after change are known. The statistic for this method is chosen in such a way that it can be calculated recursively while the computational complexity of the method remains constant with respect to time. We present simulation results that show the advantages of this method compared to linearization techniques.
A Comparative Study of Stability Testing Approaches of Two-Dimensional Recursive Digital Filters
K. R. Santhi; M.Ponnavaikko; N. Gangatharan
2008-01-01
There are many problems in science and engineering whose solution is applied in the design of Multi-Dimensional (MD) digital filters. Digital filtering finds an important position in the field of digital signal and image processing. Recently there had been a great deal of interest in the design and stability analysis of Two-Dimensional (2-D) recursive digital filters. The design techniques for stable One Dimensional (1-D) digital filters are relatively well developed; but their extension to 2...
Fast recursive filters for simulating nonlinear dynamic systems.
van Hateren, J H
2008-07-01
A fast and accurate computational scheme for simulating nonlinear dynamic systems is presented. The scheme assumes that the system can be represented by a combination of components of only two different types: first-order low-pass filters and static nonlinearities. The parameters of these filters and nonlinearities may depend on system variables, and the topology of the system may be complex, including feedback. Several examples taken from neuroscience are given: phototransduction, photopigment bleaching, and spike generation according to the Hodgkin-Huxley equations. The scheme uses two slightly different forms of autoregressive filters, with an implicit delay of zero for feedforward control and an implicit delay of half a sample distance for feedback control. On a fairly complex model of the macaque retinal horizontal cell, it computes, for a given level of accuracy, one to two orders of magnitude faster than the fourth-order Runge-Kutta. The computational scheme has minimal memory requirements and is also suited for computation on a stream processor, such as a graphical processing unit.
Directory of Open Access Journals (Sweden)
Juan Carlos García Infante
2011-01-01
Full Text Available Multivariate identifier filters (multiple inputs and multiple outputs - MIMO are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948. This paper considers the MIMO digital filter model using neuro fuzzy digital filtering to find an adaptive parameter matrix which is integrated into the Kalman filter by the transition matrix. The filter uses the neural network as back-propagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. The Matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error.
Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique
Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid
2014-01-01
The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.
Non-linear Kalman filters for calibration in radio interferometry
Tasse, Cyril
2014-01-01
We present a new calibration scheme based on a non-linear version of Kalman filter that aims at estimating the physical terms appearing in the Radio Interferometry Measurement Equation (RIME). We enrich the filter's structure with a tunable data representation model, together with an augmented measurement model for regularization. We show using simulations that it can properly estimate the physical effects appearing in the RIME. We found that this approach is particularly useful in the most extreme cases such as when ionospheric and clock effects are simultaneously present. Combined with the ability to provide prior knowledge on the expected structure of the physical instrumental effects (expected physical state and dynamics), we obtain a fairly cheap algorithm that we believe to be robust, especially in low signal-to-noise regime. Potentially the use of filters and other similar methods can represent an improvement for calibration in radio interferometry, under the condition that the effects corrupting visib...
A nonlinear optoelectronic filter for electronic signal processing
Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J.; Juodawlkis, Paul W.
2014-01-01
The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology. PMID:24402418
Nonlinear Filtering Techniques Comparison for Battery State Estimation
Directory of Open Access Journals (Sweden)
Aspasia Papazoglou
2014-09-01
Full Text Available The performance of estimation algorithms is vital for the correct functioning of batteries in electric vehicles, as poor estimates will inevitably jeopardize the operations that rely on un-measurable quantities, such as State of Charge and State of Health. This paper compares the performance of three nonlinear estimation algorithms: the Extended Kalman Filter, the Unscented Kalman Filter and the Particle Filter, where a lithium-ion cell model is considered. The effectiveness of these algorithms is measured by their ability to produce accurate estimates against their computational complexity in terms of number of operations and execution time required. The trade-offs between estimators' performance and their computational complexity are analyzed.
Nonlinear stochastic systems with incomplete information filtering and control
Shen, Bo; Shu, Huisheng
2013-01-01
Nonlinear Stochastic Processes addresses the frequently-encountered problem of incomplete information. The causes of this problem considered here include: missing measurements; sensor delays and saturation; quantization effects; and signal sampling. Divided into three parts, the text begins with a focus on H∞ filtering and control problems associated with general classes of nonlinear stochastic discrete-time systems. Filtering problems are considered in the second part, and in the third the theory and techniques previously developed are applied to the solution of issues arising in complex networks with the design of sampled-data-based controllers and filters. Among its highlights, the text provides: · a unified framework for handling filtering and control problems in complex communication networks with limited bandwidth; · new concepts such as random sensor and signal saturations for more realistic modeling; and · demonstration of the use of techniques such...
A digital matched filter for reverse time chaos
Energy Technology Data Exchange (ETDEWEB)
Bailey, J. Phillip, E-mail: mchamilton@auburn.edu; Beal, Aubrey N.; Dean, Robert N.; Hamilton, Michael C. [Electrical and Computer Engineering Department, Auburn University, Auburn, Alabama 36489 (United States)
2016-07-15
The use of reverse time chaos allows the realization of hardware chaotic systems that can operate at speeds equivalent to existing state of the art while requiring significantly less complex circuitry. Matched filter decoding is possible for the reverse time system since it exhibits a closed form solution formed partially by a linear basis pulse. Coefficients have been calculated and are used to realize the matched filter digitally as a finite impulse response filter. Numerical simulations confirm that this correctly implements a matched filter that can be used for detection of the chaotic signal. In addition, the direct form of the filter has been implemented in hardware description language and demonstrates performance in agreement with numerical results.
On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles
Luo, Xiaodong
2010-09-19
The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].
Digital set point control of nonlinear stochastic systems
Moose, R. L.; Vanlandingham, H. F.; Zwicke, P. E.
1978-01-01
A technique for digital control of nonlinear stochastic plants is presented. The development achieves a practical digital algorithm with which the closed-loop system behaves in a classical Type I manner even with gross nonlinearities in the plant structure and low signal-to-noise power ratios. The design procedure is explained in detail and illustrated by an example whose simulated responses testify to the practicality of the approach.
DIGITAL FILTER PROCESS DURING THE DISCRETE MAGNITUDE DATA GATHERING
Institute of Scientific and Technical Information of China (English)
姚天忠; 邹丽新; 胡冶
1995-01-01
We analyze the reason that causes the error during the discrete magnitude data gathering.A method,dealing with data by means of second-order low-pass digital filter,is brought out,which will improve both the smooth degree and the reponse of the data into a quite good state.
Digitally Controlled ’Programmable’ Active Filters.
1985-12-01
Mitra, S. K., Analysis and Synthesis of Linear Active .. Networks, Wiley, New York, 1969. * 6. Sedra , A. S. and Smith , K. C., "A Second-Generation...Current Conveyor and its Applications," IEEE Trans. Circuit Theory, Vol. CT-17, pp. 132-134, 1970. 7. Sedra , A. S., "A New Approach to Active Network...CT-18, pp. 358-361, May 1971. 27. Hamilton, T. A., and Sedra , A. S., "Some New IJ Configurations for Active Filters," IEEE Trans. Circuit Tehory, Vol
A nested sampling particle filter for nonlinear data assimilation
Elsheikh, Ahmed H.
2014-04-15
We present an efficient nonlinear data assimilation filter that combines particle filtering with the nested sampling algorithm. Particle filters (PF) utilize a set of weighted particles as a discrete representation of probability distribution functions (PDF). These particles are propagated through the system dynamics and their weights are sequentially updated based on the likelihood of the observed data. Nested sampling (NS) is an efficient sampling algorithm that iteratively builds a discrete representation of the posterior distributions by focusing a set of particles to high-likelihood regions. This would allow the representation of the posterior PDF with a smaller number of particles and reduce the effects of the curse of dimensionality. The proposed nested sampling particle filter (NSPF) iteratively builds the posterior distribution by applying a constrained sampling from the prior distribution to obtain particles in high-likelihood regions of the search space, resulting in a reduction of the number of particles required for an efficient behaviour of particle filters. Numerical experiments with the 3-dimensional Lorenz63 and the 40-dimensional Lorenz96 models show that NSPF outperforms PF in accuracy with a relatively smaller number of particles. © 2013 Royal Meteorological Society.
Power and Aging Characterization of Digital FIR Filters Architectures
DEFF Research Database (Denmark)
Calimera, Andrea; Liu, Wei; Macii, Enrico;
2012-01-01
With technology scaling, newer metrics have been introduced, in addition to delay, area, and power dissipation, to characterize the behavior of digital systems. While dynamic and static power dissipation still remain the most serious concern at nanometer lengths (65nm and below), process-variatio......With technology scaling, newer metrics have been introduced, in addition to delay, area, and power dissipation, to characterize the behavior of digital systems. While dynamic and static power dissipation still remain the most serious concern at nanometer lengths (65nm and below), process......-variation, temperature and aging induced variations pose new challenges in the fabrication of the next generation of ICs. This work presents a detailed power and aging characterization of digital FIR filters in an industrial 45nm CMOS technology, and a design space exploration of different filter architectures...
Nonlinear ultrasonic measurements based on cross-correlation filtering techniques
Yee, Andrew; Stewart, Dylan; Bunget, Gheorghe; Kramer, Patrick; Farinholt, Kevin; Friedersdorf, Fritz; Pepi, Marc; Ghoshal, Anindya
2017-02-01
Cyclic loading of mechanical components promotes the formation of dislocation dipoles in metals, which can serve as precursors to crack nucleation and ultimately lead to failure. In the laboratory setting, an acoustic nonlinearity parameter has been assessed as an effective indicator for characterizing the progression of fatigue damage precursors. However, the need to use monochromatic waves of medium-to-high acoustic energy has presented a constraint, making it problematic for use in field applications. This paper presents a potential approach for field measurement of acoustic nonlinearity by using general purpose ultrasonic pulser-receivers. Nonlinear ultrasonic measurements during fatigue testing were analyzed by the using contact and immersion pulse-through method. A novel cross-correlation filtering technique was developed to extract the fundamental and higher harmonic waves from the signals. As in the case of the classic harmonic generation, the nonlinearity parameters of the second and third harmonics indicate a strong correlation with fatigue cycles. Consideration was given to potential nonlinearities in the measurement system, and tests have confirmed that measured second harmonic signals exhibit a linear dependence on the input signal strength, further affirming the conclusion that this parameter relates to damage precursor formation from cyclic loading.
State estimation of connected vehicles using a nonlinear ensemble filter
Institute of Scientific and Technical Information of China (English)
刘江; 陈华展; 蔡伯根; 王剑
2015-01-01
The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs (on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter (EnKF) is introduced to estimate the vehicle’s state with observations from navigation satellites and neighborhood vehicles, and the original EnKF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in EnKF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.
Optical notch filter design based on digital signal processing
Institute of Scientific and Technical Information of China (English)
GUO Sen; ZHANG Juan; LI Xue
2011-01-01
Based on digital signal processing theory, a novel method of designing optical notch filter is proposed for Mach-Zehnder interferometer with cascaded optical fiber rings coupled structure. The method is simple and effective, and it can be used to implement the designing of the optical notch filter which has arbitrary number of notch points in one free spectrum range (FSR). A design example of notch filter based on cascaded single-fiber-rings is given. On this basis, an improved cascaded double-fiber-rings structure is presented to eliminate the effect of phase shift caused by the single-fiber-ring structure. This new structure can improve the stability and applicability of system. The change of output intensity spectrum is finally investigated for each design parameter and the tuning characteristics of the notch filter are also discussed.
Digital Filter Performance for the ATLAS Level-1 Calorimeter Trigger
Hadley, D R; The ATLAS collaboration
2010-01-01
The ATLAS Level-1 Calorimeter Trigger is a hardware-based system designed to identify high-pT jets, electron/photon and tau candidates, and to measure total and missing ET in the ATLAS Liquid Argon and Tile calorimeters. It is a pipelined processor system, with a new set of inputs being evaluated every 25ns. The overall trigger decision has a latency budget of 2µs, including all transmission delays. The calorimeter trigger uses about 7200 reduced granularity analogue signals, which are first digitized at the 40 MHz LHC bunch-crossing frequency, before being passed to a digital Finite Impulse Response (FIR) filter. Due to latency and chip real-estate constraints, only a simple 5-element filter with limited precision can be used. Nevertheless this filter achieves a significant reduction in noise, along with improving the bunch-crossing assignment and energy resolution for small signals. The context in which digital filters are used for the ATLAS Level-1 Calorimeter Trigger will be presented, before describing ...
On a nonlinear Kalman filter with simplified divided difference approximation
Luo, Xiaodong
2012-03-01
We present a new ensemble-based approach that handles nonlinearity based on a simplified divided difference approximation through Stirling\\'s interpolation formula, which is hence called the simplified divided difference filter (sDDF). The sDDF uses Stirling\\'s interpolation formula to evaluate the statistics of the background ensemble during the prediction step, while at the filtering step the sDDF employs the formulae in an ensemble square root filter (EnSRF) to update the background to the analysis. In this sense, the sDDF is a hybrid of Stirling\\'s interpolation formula and the EnSRF method, while the computational cost of the sDDF is less than that of the EnSRF. Numerical comparison between the sDDF and the EnSRF, with the ensemble transform Kalman filter (ETKF) as the representative, is conducted. The experiment results suggest that the sDDF outperforms the ETKF with a relatively large ensemble size, and thus is a good candidate for data assimilation in systems with moderate dimensions. © 2011 Elsevier B.V. All rights reserved.
Nonlinear filtering for character recognition in low quality document images
Diaz-Escobar, Julia; Kober, Vitaly
2014-09-01
Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.
Digital filters in spectrometry; Filtros digitales en espectrometria
Energy Technology Data Exchange (ETDEWEB)
Barron B, J. I.; Hernandez D, V. M.; Vega C, H. R., E-mail: israel_176@hotmail.com [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98060 Zacatecas (Mexico)
2013-10-15
In this work is presented the development and application of the digital signal processing for different multichannel analysis spectra. The use of the smoothing classic methods in applications of signal processing is illustrated by a filters discussion; autoregressive, mobile average and the ARMA filters. Generally, simple routines of lineal smoothing do not provide appropriate smoothing of the data that show the local ruggedness as the strong discontinuities; however the indicated development algorithms have been enough to leave adapting to this task. Four algorithms were proven: autoregressive, mobile average, ARMA and binomial methods for 5, 7, and 9 of data, everything in the domain of the time and programmed in Mat lab. (Author)
Gutierrez, Alberto, Jr.
1995-01-01
This dissertation evaluates receiver-based methods for mitigating the effects due to nonlinear bandlimited signal distortion present in high data rate satellite channels. The effects of the nonlinear bandlimited distortion is illustrated for digitally modulated signals. A lucid development of the low-pass Volterra discrete time model for a nonlinear communication channel is presented. In addition, finite-state machine models are explicitly developed for a nonlinear bandlimited satellite channel. A nonlinear fixed equalizer based on Volterra series has previously been studied for compensation of noiseless signal distortion due to a nonlinear satellite channel. This dissertation studies adaptive Volterra equalizers on a downlink-limited nonlinear bandlimited satellite channel. We employ as figure of merits performance in the mean-square error and probability of error senses. In addition, a receiver consisting of a fractionally-spaced equalizer (FSE) followed by a Volterra equalizer (FSE-Volterra) is found to give improvement beyond that gained by the Volterra equalizer. Significant probability of error performance improvement is found for multilevel modulation schemes. Also, it is found that probability of error improvement is more significant for modulation schemes, constant amplitude and multilevel, which require higher signal to noise ratios (i.e., higher modulation orders) for reliable operation. The maximum likelihood sequence detection (MLSD) receiver for a nonlinear satellite channel, a bank of matched filters followed by a Viterbi detector, serves as a probability of error lower bound for the Volterra and FSE-Volterra equalizers. However, this receiver has not been evaluated for a specific satellite channel. In this work, an MLSD receiver is evaluated for a specific downlink-limited satellite channel. Because of the bank of matched filters, the MLSD receiver may be high in complexity. Consequently, the probability of error performance of a more practical
Out-of-band and adjacent-channel interference reduction by analog nonlinear filters
Nikitin, Alexei V.; Davidchack, Ruslan L.; Smith, Jeffrey E.
2015-12-01
In a perfect world, we would have `brick wall' filters, no-distortion amplifiers and mixers, and well-coordinated spectrum operations. The real world, however, is prone to various types of unintentional and intentional interference of technogenic (man-made) origin that can disrupt critical communication systems. In this paper, we introduce a methodology for mitigating technogenic interference in communication channels by analog nonlinear filters, with an emphasis on the mitigation of out-of-band and adjacent-channel interference. Interference induced in a communications receiver by external transmitters can be viewed as wide-band non-Gaussian noise affecting a narrower-band signal of interest. This noise may contain a strong component within the receiver passband, which may dominate over the thermal noise. While the total wide-band interference seen by the receiver may or may not be impulsive, we demonstrate that the interfering component due to power emitted by the transmitter into the receiver channel is likely to appear impulsive under a wide range of conditions. We give an example of mechanisms of impulsive interference in digital communication systems resulting from the nonsmooth nature of any physically realizable modulation scheme for transmission of a digital (discontinuous) message. We show that impulsive interference can be effectively mitigated by nonlinear differential limiters (NDLs). An NDL can be configured to behave linearly when the input signal does not contain outliers. When outliers are encountered, the nonlinear response of the NDL limits the magnitude of the respective outliers in the output signal. The signal quality is improved in excess of that achievable by the respective linear filter, increasing the capacity of a communications channel. The behavior of an NDL, and its degree of nonlinearity, is controlled by a single parameter in a manner that enables significantly better overall suppression of the noise-containing impulsive components
Neural network-based H∞ filtering for nonlinear systems with time-delays
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed.Firstly,neural networks are employed to approximate the nonlinearities.Next,the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion (LDI).Finally,based on the LDI model,a neural network-based nonlinear filter (NNBNF) is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality (LMI) constraints.Compared with the existing nonlinear filters,NNBNF is time-invariant and numerically tractable.The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.
Numerical filtering techniques for the reduction of noise in digital telemetry data
Helfrich-Stone, Thomas M.
Telemetry data noise is due to the marginal or complete loss of telemetry carrier signal, leading to errors in the PCM data received. Attention is presently given to several postflight numerical filtering techniques for the reduction and/or removal of noise in digital telemetry data, prior to use in automated computer data analysis. The techniques encompass manual filtering, upper/lower bound filtering, mean-plus/minus standard deviation filtering, rate-of-change filtering, multiple-measurement filtering, and multiple filters.
Design of recursive variable digital filters with theoretically guaranteed stability
Deng, Tian-Bo
2016-12-01
Stability is one of the most concerned issues in designing a recursive variable digital filter (VDF). This is because the coefficients of a recursive VDF constantly vary in the tuning process, and updating the coefficients may incur instability. Thus, an appropriate measure needs to be taken for ensuring its stability. This paper presents a new coefficient transformation (CT) method for transforming the coefficients of a recursive transfer-function denominator into a set of new coefficients. From the viewpoint of conventional constant-coefficient filter (constant filter) design, the new coefficients can take arbitrary values without incurring instability. For designing a stable VDF, we apply this CT to the variable case and approximate each transformed coefficient as a distinct polynomial in the tuning parameter. Thus, we can change the filter coefficients by changing the value of the tuning parameter, and thus tune the magnitude response. Thanks to the proposed CT, updating the filter coefficients will never incur instability. This is the core part of the CT-based design approach. In this paper, we utilise a weighting function to ignore the transition-band errors and thus enhance the design accuracy of important frequency bands (passband and stopband). Moreover, the polynomials use different degrees so as to reduce the VDF complexity. Two design examples (lowpass VDF and bandpass VDF) are provided for verifying the design accuracy and checking the stability.
Rigatos, Gerasimos G
2015-01-01
This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The bo...
SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA
Directory of Open Access Journals (Sweden)
Karsten Rodenacker
2011-05-01
Full Text Available Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D is gathered during relatively long time ranges (3-5 min. From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters. Filters applied are compared by classifications of activations.
Advanced nonlinear control of three phase series active power filter
Directory of Open Access Journals (Sweden)
Abouelmahjoub Y.
2014-01-01
Full Text Available The problem of controlling three-phase series active power filter (TPSAPF is addressed in this paper in presence of the perturbations in the voltages of the electrical supply network. The control objective of the TPSAPF is twofold: (i compensation of all voltage perturbations (voltage harmonics, voltage unbalance and voltage sags, (ii regulation of the DC bus voltage of the inverter. A controller formed by two nonlinear regulators is designed, using the Backstepping technique, to provide the above compensation. The regulation of the DC bus voltage of the inverter is ensured by the use of a diode bridge rectifier which its output is in parallel with the DC bus capacitor. The Analysis of controller performances is illustrated by numerical simulation in Matlab/Simulink environment.
Nonlinear Optical Materials for the Smart Filtering of Optical Radiation.
Dini, Danilo; Calvete, Mário J F; Hanack, Michael
2016-11-23
The control of luminous radiation has extremely important implications for modern and future technologies as well as in medicine. In this Review, we detail chemical structures and their relevant photophysical features for various groups of materials, including organic dyes such as metalloporphyrins and metallophthalocyanines (and derivatives), other common organic materials, mixed metal complexes and clusters, fullerenes, dendrimeric nanocomposites, polymeric materials (organic and/or inorganic), inorganic semiconductors, and other nanoscopic materials, utilized or potentially useful for the realization of devices able to filter in a smart way an external radiation. The concept of smart is referred to the characteristic of those materials that are capable to filter the radiation in a dynamic way without the need of an ancillary system for the activation of the required transmission change. In particular, this Review gives emphasis to the nonlinear optical properties of photoactive materials for the function of optical power limiting. All known mechanisms of optical limiting have been analyzed and discussed for the different types of materials.
Empirical intrinsic geometry for nonlinear modeling and time series filtering.
Talmon, Ronen; Coifman, Ronald R
2013-07-30
In this paper, we present a method for time series analysis based on empirical intrinsic geometry (EIG). EIG enables one to reveal the low-dimensional parametric manifold as well as to infer the underlying dynamics of high-dimensional time series. By incorporating concepts of information geometry, this method extends existing geometric analysis tools to support stochastic settings and parametrizes the geometry of empirical distributions. However, the statistical models are not required as priors; hence, EIG may be applied to a wide range of real signals without existing definitive models. We show that the inferred model is noise-resilient and invariant under different observation and instrumental modalities. In addition, we show that it can be extended efficiently to newly acquired measurements in a sequential manner. These two advantages enable us to revisit the Bayesian approach and incorporate empirical dynamics and intrinsic geometry into a nonlinear filtering framework. We show applications to nonlinear and non-Gaussian tracking problems as well as to acoustic signal localization.
Reduction of nonlinear patterning effects in SOA-based All-optical Switches using Optical filtering
DEFF Research Database (Denmark)
Nielsen, Mads Lønstrup; Mørk, Jesper; Skaguchi, J.
2005-01-01
We explain theoretically, and demonstrate and quantify experimentally, how appropriate filtering can reduce the dominant nonlinear patterning effect, which limits the performance of differential-mode SOA-based switches.......We explain theoretically, and demonstrate and quantify experimentally, how appropriate filtering can reduce the dominant nonlinear patterning effect, which limits the performance of differential-mode SOA-based switches....
Design of two-dimensional digital filters using neural networks
Institute of Scientific and Technical Information of China (English)
Wang Xiaohua; He Yigang
2005-01-01
A new approach for the design of two-dimensional (2-D) linear phase FIR digital filters based on a new neural networks algorithm (NNA) is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations.
Digitally Programmable High-Q Voltage Mode Universal Filter
Directory of Open Access Journals (Sweden)
D. Singh
2013-12-01
Full Text Available A new low-voltage low-power CMOS current feedback amplifier (CFA is presented in this paper. This is used to realize a novel digitally programmable CFA (DPCFA using transistor arrays and MOS switches. The proposed realizations nearly allow rail-to-rail swing capability at all the ports. Class-AB output stage ensures low power dissipation and high current drive capability. The proposed CFA/ DPCFA operates at supply voltage of ±0.75 V and exhibits bandwidth better than 95 MHz. An application of the DPCFA to realize a novel voltage mode high-Q digitally programmable universal filter (UF is given. Performances of all the proposed circuits are verified by PSPICE simulation using TSMC 0.25μm technology parameters.
An emergent theory of digital library metadata enrich then filter
Stevens, Brett
2015-01-01
An Emergent Theory of Digital Library Metadata is a reaction to the current digital library landscape that is being challenged with growing online collections and changing user expectations. The theory provides the conceptual underpinnings for a new approach which moves away from expert defined standardised metadata to a user driven approach with users as metadata co-creators. Moving away from definitive, authoritative, metadata to a system that reflects the diversity of users’ terminologies, it changes the current focus on metadata simplicity and efficiency to one of metadata enriching, which is a continuous and evolving process of data linking. From predefined description to information conceptualised, contextualised and filtered at the point of delivery. By presenting this shift, this book provides a coherent structure in which future technological developments can be considered.
Hu, Jun; Gao, Huijun
2014-01-01
This monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced phenomena consequent on limited communication capacity. Such phenomena include communication delay, packet dropout, signal quantization or saturation, randomly occurring nonlinearities and randomly occurring uncertainties.The text is self-contained, beginning with an introduction to nonlinear stochastic systems, network-induced phenomena and filtering and control, moving through a collection of the latest research results which focuses on the three aspects
Local-instantaneous filtering in the integral transform solution of nonlinear diffusion problems
Macêdo, E. N.; Cotta, R. M.; Orlande, H. R. B.
A novel filtering strategy is proposed to be utilized in conjunction with the Generalized Integral Transform Technique (GITT), in the solution of nonlinear diffusion problems. The aim is to optimize convergence enhancement, yielding computationally efficient eigenfunction expansions. The proposed filters include space and time dependence, extracted from linearized versions of the original partial differential system. The scheme automatically updates the filter along the time integration march, as the required truncation orders for the user requested accuracy begin to exceed a prescribed maximum system size. A fully nonlinear heat conduction example is selected to illustrate the computational performance of the filtering strategy, against the classical single-filter solution behavior.
A novel extended Kalman filter for a class of nonlinear systems
Institute of Scientific and Technical Information of China (English)
DONG Zhe; YOU Zheng
2006-01-01
Estimation of the state variables of nonlinear systems is one of the fundamental and significant problems in control and signal processing. A new extended Kalman filtering approach for a class of nonlinear discrete-time systems in engineering is presented in this paper. In contrast to the celebrated extended Kalman filter (EKF), there is no linearization operation in the design procedure of the filter, and the parameters of the filter are obtained through minimizing a proper upper bound of the mean-square estimation error. Simulation results show that this filter can provide higher estimation precision than that provided by the EKF.
Digital filter technology and its application to geomagnetic pulsations in Antarctica
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Digital filter technology is an important method in study of geomagnetic pulsations in Antarctica. The signals received by pulsation magnetometer on the ground include various types of magnetic pulsations. Some types of pulsations or some frequency hands of pulsations can be extracted from the signals by means of digital filter technology because types of pulsations are defined according to their frequency range. In this paper usual digital filter technology is provided for study of magnetic pulsations in Antarctica and some examples are introduced.
Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter
Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey
2015-12-01
The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.
An improved exponential filter for fast nonlinear registration of brain magnetic resonance images
Institute of Scientific and Technical Information of China (English)
Zhiying Long; Li Yao; Kewei Chen; Danling Peng
2009-01-01
A linear elastic convolution filter was derived from the eigenfunctions of the Navier-Stokes differential operator by Bro-Nielsen in order to match images with large deformations. Due to the complexity of constructing the elastic convolution filter, the algorithm's effi-ciency reduces rapidly with the increase in the image's size. In our previous work, a simple two-sided exponential filter with high efficiency was proposed to approximate an elastic filter. However, its poor smoothness may degenerate the performance. In this paper, a new expo-nential filter was constructed by utilizing a modified nonlinear curve fitting method to approximate the elastic filter. The new filter's good smoothness makes its performance comparable to an elastic filter. Its simple and separable form makes the algorithm's speed faster than the elastic filter. Furthermore, our experiments demonstrated that the new filter was suitable for both the elastic and fluid models.
Rigatos, Gerasimos
2016-07-01
The Derivative-free nonlinear Kalman Filter is used for developing a communication system that is based on a chaotic modulator such as the Duffing system. In the transmitter's side, the source of information undergoes modulation (encryption) in which a chaotic signal generated by the Duffing system is the carrier. The modulated signal is transmitted through a communication channel and at the receiver's side demodulation takes place, after exploiting the estimation provided about the state vector of the chaotic oscillator by the Derivative-free nonlinear Kalman Filter. Evaluation tests confirm that the proposed filtering method has improved performance over the Extended Kalman Filter and reduces significantly the rate of transmission errors. Moreover, it is shown that the proposed Derivative-free nonlinear Kalman Filter can work within a dual Kalman Filtering scheme, for performing simultaneously transmitter-receiver synchronisation and estimation of unknown coefficients of the communication channel.
Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter
DEFF Research Database (Denmark)
Abächerli, Roger; Isaksen, Jonas; Schmid, Ramun
2016-01-01
Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can...... result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10−8 LSB....... Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use...
Directory of Open Access Journals (Sweden)
Peter Kulla
2004-01-01
Full Text Available The main image information content, from the human visual system viewing point, is focused into whole colorimetric and spatial informations. Because every image is result of some previous processes, the goal for all standard image processing methods is improvement colorimetric and spatial image parameters in relation maximum information content by the complicated and expensive systems for digital image processing in (quasireal time [1] based on the flash signal (multiprocessors. Some single-purpose applications do not need the robust and flash systems for DIP and be enough for their use single digital filters with suitable hardware implementation. In the contribution discussed problem is therefore focused on the short description of FIR digital tilters and their hardware implementation in FPGAs-Xilinx for usage in the image processing in real time include obtained experimental results.
A tunable Butterworth low-pass filter with digitally controlled DDCC
Directory of Open Access Journals (Sweden)
Y. S. Hwang
2013-06-01
Full Text Available This paper presents a 6th-order tunable Butterworth low-pass active filter with Digitally Controlled Differential Difference Current Conveyor (DDCC. This active filter is synthesized using the systematic method of voltage-mode linear transformation (VMLT which enables the filter use fewer active components, grounded capacitors and grounded resistors to avoid the parasitical effects. The bandwidth of the filter can be tuned by digital switches to adjust the output current of the DDCC. The specifications of the filter are based on 3G standard, and the filter is controlled by 8-bits digital signals. The tunable bandwidth of the filter is from 12 KHz to 2.6 MHz. The filter chip layout is realized by TSMC 0.18 um CMOS 1P6M mixed-mode technology. The supply voltage is 1.8V and the power consumption is 3.6 mW.
Energy Technology Data Exchange (ETDEWEB)
Royer, L; Manen, S; Gay, P, E-mail: royer@clermont.in2p3.f [Clermont Universite, Universite Blaise Pascal, CNRS/IN2P3, LPC, BP 10448, F-63000 Clermont-Ferrand (France)
2010-12-15
A very-front-end electronics dedicated to high granularity calorimeters has been designed and its performance measured. This electronics performs the amplification of the charge delivered by the detector thanks to a low-noise Charge Sensitive Amplifier. The dynamic range is improved using a bandpass filter based on a Gated Integrator. Studying its weighting function, we show that this filter is more efficient than standard CRRC shaper, thanks to the integration time which can be expand near the bunch interval time, whereas the peaking time of the CRRC shaper is limited to pile-up consideration. Moreover, the Gated Integrator performs intrinsically the analog memorization of the signal before its delayed digital conversion. The analog-to-digital conversion is performed through a 12-bit cyclic ADC specifically developed for this application. The very-front-end channel has been fabricated using a 0.35 {mu}m CMOS technology. Measurements show a global non-linearity better than 0.1%. The Equivalent Noise Charge at the input of the channel is evaluated to 1.8 fC, compare to the maximum input charge of 10 pC. The power consumption of the complete channel is limited to 6.5 mW.
Design of Low Pass Digital FIR Filter Using Cuckoo Search Algorithm
Taranjit Singh; Harvinder Singh Josan
2014-01-01
This paper presents a novel approach of designing linear phase FIR low pass filter using cuckoo Search Algorithm (CSA). FIR filter design is a multi-modal optimization problem. The conventional optimization techniques are not efficient for digital filter design. An iterative method is introduced to find the best solution of FIR filter design problem.Flat passband and high stopband attenuation are the major characteristics required in FIR filter design. To achieve these charact...
Adaptive Filters with Error Nonlinearities: Mean-Square Analysis and Optimum Design
Directory of Open Access Journals (Sweden)
Ali H. Sayed
2001-01-01
Full Text Available This paper develops a unified approach to the analysis and design of adaptive filters with error nonlinearities. In particular, the paper performs stability and steady-state analysis of this class of filters under weaker conditions than what is usually encountered in the literature, and without imposing any restriction on the color or statistics of the input. The analysis results are subsequently used to derive an expression for the optimum nonlinearity, which turns out to be a function of the probability density function of the estimation error. Some common nonlinearities are shown to be approximations to the optimum nonlinearity. The framework pursued here is based on energy conservation arguments.
[Radiation dose reduction using a non-linear image filter in MDCT].
Nakashima, Junya; Takahashi, Toshiyuki; Takahashi, Yoshimasa; Imai, Yasuhiro; Ishihara, Yotaro; Kato, Kyoichi; Nakazawa, Yasuo
2010-05-20
The development of MDCT enabled various high-quality 3D imaging and optimized scan timing with contrast injection in a multi-phase dynamic study. Since radiation dose tends to increase to yield such high-quality images, we have to make an effort to reduce radiation dose. A non-linear image filter (Neuro 3D filter: N3D filter) has been developed in order to improve image noise. The purpose of this study was to evaluate the physical performance and effectiveness of this non-linear image filter using phantoms, and show how we can reduce radiation dose in clinical use of this filter. This N3D filter reduced radiation dose by about 50%, with minimum deterioration of spatial reduction in phantom and clinical studies. This filter shows great potential for clinical application.
Collaborative Filtering without Explicit Feedbacks for Digital Recorders
Basso, Alessandro; Panisson, André; Ruffo, Giancarlo
2011-01-01
Recommendation is usually reduced to a prediction problem over the function $r(u_a, e_i)$ that returns the expected rating of element $e_i$ for user $u_a$. In the IPTV domain, we deal with an environment where the definitions of all the parameters involved in this function (i.e., user profiles, feedback ratings and elements) are controversial. To our knowledge, this paper represents the first attempt to run collaborative filtering algorithms without inner assumptions: we start our analysis from an unstructured set of recordings, before performing a data pre-processing phase in order to extract useful information. Hence, we experiment with a real Digital Video Recorder system where EPG have not been provided to the user for selecting event timings and where explicit feedbacks were not collected.
Digital high-pass filter deconvolution by means of an infinite impulse response filter
Födisch, P.; Wohsmann, J.; Lange, B.; Schönherr, J.; Enghardt, W.; Kaever, P.
2016-09-01
In the application of semiconductor detectors, the charge-sensitive amplifier is widely used in front-end electronics. The output signal is shaped by a typical exponential decay. Depending on the feedback network, this type of front-end electronics suffers from the ballistic deficit problem, or an increased rate of pulse pile-ups. Moreover, spectroscopy applications require a correction of the pulse-height, while a shortened pulse-width is desirable for high-throughput applications. For both objectives, digital deconvolution of the exponential decay is convenient. With a general method and the signals of our custom charge-sensitive amplifier for cadmium zinc telluride detectors, we show how the transfer function of an amplifier is adapted to an infinite impulse response (IIR) filter. This paper investigates different design methods for an IIR filter in the discrete-time domain and verifies the obtained filter coefficients with respect to the equivalent continuous-time frequency response. Finally, the exponential decay is shaped to a step-like output signal that is exploited by a forward-looking pulse processing.
Digital high-pass filter deconvolution by means of an infinite impulse response filter
Energy Technology Data Exchange (ETDEWEB)
Födisch, P., E-mail: p.foedisch@hzdr.de [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Wohsmann, J. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany); Lange, B. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Schönherr, J. [Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany); Enghardt, W. [OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, PF 41, 01307 Dresden (Germany); Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology, Bautzner Landstr. 400, 01328 Dresden (Germany); German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Kaever, P. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany)
2016-09-11
In the application of semiconductor detectors, the charge-sensitive amplifier is widely used in front-end electronics. The output signal is shaped by a typical exponential decay. Depending on the feedback network, this type of front-end electronics suffers from the ballistic deficit problem, or an increased rate of pulse pile-ups. Moreover, spectroscopy applications require a correction of the pulse-height, while a shortened pulse-width is desirable for high-throughput applications. For both objectives, digital deconvolution of the exponential decay is convenient. With a general method and the signals of our custom charge-sensitive amplifier for cadmium zinc telluride detectors, we show how the transfer function of an amplifier is adapted to an infinite impulse response (IIR) filter. This paper investigates different design methods for an IIR filter in the discrete-time domain and verifies the obtained filter coefficients with respect to the equivalent continuous-time frequency response. Finally, the exponential decay is shaped to a step-like output signal that is exploited by a forward-looking pulse processing.
Low power adder based digital filter for QRS detector.
Murali, L; Chitra, D; Manigandan, T
2014-01-01
Most of the Biomedical applications use dedicated processors for the implementation of complex signal processing. Among them, sensor network is also a type, which has the constraint of low power consumption. Since the processing elements are the most copiously used operations in the signal processors, the power consumption of this has the major impact on the system level application. In this paper, we introduce low power concept of transistor stacking to reduce leakage power; and new architectures based on stacking to implement the full adder and its significance at the digital filter level for QRS detector are implemented. The proposed concept has lesser leakage power at the adder as well as filter level with trade-off in other quality metrics of the design. This enabled the design to be dealt with as the low-power corner and can be made adaptable to any level of hierarchical abstractions as per the requirement of the application. The proposed architectures are designed, modeled at RTL level using the Verilog-HDL, and synthesized in Synopsys Design Compiler by mapping the design to 65 nm technology library standard cells.
A reconfigurable OTA-C baseband filter with wide digital tuning for GNSS receivers
Energy Technology Data Exchange (ETDEWEB)
Pan Wenguang; Gan Yebing [Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029 (China); Ma Chengyan; Ye Tianchun, E-mail: panwenguang@casic.ac.c [Hangzhou Zhongke Microelectronics Co. Ltd, Hangzhou 310053 (China)
2010-09-15
The design of a digitally-tunable sixth-order reconfigurable OTA-C filter in a 0.18-{mu}m RFCMOS process is proposed. The filter can be configured as a complex band pass filter or two real low pass filters. An improved digital automatic frequency tuning scheme based on the voltage controlled oscillator technique is adopted to compensate for process variations. An extended tuning range (above 8:1) is obtained by using widely continuously tunable transconductors based on digital techniques. In the complex band pass mode, the bandwidth can be tuned from 3 to 24 MHz and the center frequency from 3 to 16 MHz. (semiconductor integrated circuits)
Digital filtering using the multidimensional logarithmic number system
Dimitrov, Vassil S.; Jullien, Graham A.; Walus, Konrad
2002-12-01
We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LNS is the requirement to use very large ROM arrays in implementing the additions and subtraction and it limits its use to low-precision applications. MDLNS allows exponential reduction of the size of the ROMs used without affecting the speed of the computational process; moreover, the calculations over different bases and digits are completely independent, which makes this particular representation perfectly suitable for massively parallel DSP architectures. The use of more than one base has at least two extra advantages. Firstly, the proposed architecture allows us to obtain the final result straightforwardly in binary form, thus, there is no need of the exponential amplifier, used in the known LNS architectures. Secondly, the second base can be optimized in accordance to the specific digital filter characteristics. This leads to dramatic reduction of the exponents used and, consequently, to large area savings. We offer many examples showing the computational advantages of the proposed approach.
Hypersonic entry vehicle state estimation using nonlinearity-based adaptive cubature Kalman filters
Sun, Tao; Xin, Ming
2017-05-01
Guidance, navigation, and control of a hypersonic vehicle landing on the Mars rely on precise state feedback information, which is obtained from state estimation. The high uncertainty and nonlinearity of the entry dynamics make the estimation a very challenging problem. In this paper, a new adaptive cubature Kalman filter is proposed for state trajectory estimation of a hypersonic entry vehicle. This new adaptive estimation strategy is based on the measure of nonlinearity of the stochastic system. According to the severity of nonlinearity along the trajectory, the high degree cubature rule or the conventional third degree cubature rule is adaptively used in the cubature Kalman filter. This strategy has the benefit of attaining higher estimation accuracy only when necessary without causing excessive computation load. The simulation results demonstrate that the proposed adaptive filter exhibits better performance than the conventional third-degree cubature Kalman filter while maintaining the same performance as the uniform high degree cubature Kalman filter but with lower computation complexity.
Estimation in continuous-time stochastic| volatility models using nonlinear filters
DEFF Research Database (Denmark)
Nielsen, Jan Nygaard; Vestergaard, M.; Madsen, Henrik
2000-01-01
Presents a correction to the authorship of the article 'Estimation in Continuous-Time Stochastic Volatility Models Using Nonlinear Filters,' published in the periodical 'International Journal of Theoretical and Applied Finance,' Vol. 3, No. 2., pp. 279-308.......Presents a correction to the authorship of the article 'Estimation in Continuous-Time Stochastic Volatility Models Using Nonlinear Filters,' published in the periodical 'International Journal of Theoretical and Applied Finance,' Vol. 3, No. 2., pp. 279-308....
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.
The Use of Nonlinear Constitutive Equations to Evaluate Draw Resistance and Filter Ventilation
Eitzinger B; Ederer G
2014-01-01
This study investigates by nonlinear constitutive equations the influence of tipping paper, cigarette paper, filter, and tobacco rod on the degree of filter ventilation and draw resistance. Starting from the laws of conservation, the path to the theory of fluid dynamics in porous media and Darcy's law is reviewed and, as an extension to Darcy's law, two different nonlinear pressure drop-flow relations are proposed. It is proven that these relations are valid constitutive equations and the par...
Directory of Open Access Journals (Sweden)
Medel Juárez José de J.
2011-05-01
Full Text Available
Los filtros identificadores multivariables (MIMO son sistemas digitales adaptivos que cuentan con retroalimentación para que, de acuerdo a una función objetivo, ajusten su matriz de parámetros con la que se aproximan a la di-námica observable del sistema de referencia. Una forma de que un identificador cumpla con esas condiciones, es la de la lógica difusa por medio de sus mecanismos de in-ferencia que interpretan y seleccionan en una base de co-nocimiento la mejor matriz de parámetros. Estos mecanismos de selección mediante las redes neuronales permiten encontrar la respuesta con el mejor nivel de operación para cada cambio de estado (Shannon, 1948. En este artículo se considera en el modelo MIMO del filtrado digital, el proceso neuronal difuso para la estimación matricial de parámetros adaptiva, que se integra en el filtro de Kalman a través de la matriz de transición. Para ello se utilizó la red neuronal del tipo retropropagación en el mecanismo difuso, interpretando sus variables y sus respectivos niveles, seleccionando los mejores valores para ajustar automáticamente los valores de la matriz de transición. La simulación en Matlab presenta al filtrado digital neuronal difuso dando el seguimiento, observándose un funcional de error decreciente exponencialmente.
Multivariate identifier filters (multiple inputs and multiple outputs - MIMO are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter
1989-10-30
In this Phase I SBIR study, new methods are developed for the system identification and stochastic filtering of nonlinear controlled Markov processes...state space Markov process models and canonical variate analysis (CVA) for obtaining optimal nonlinear procedures for system identification and stochastic
An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models
Chow, Sy-Miin; Ferrer, Emilio; Nesselroade, John R.
2007-01-01
In the past several decades, methodologies used to estimate nonlinear relationships among latent variables have been developed almost exclusively to fit cross-sectional models. We present a relatively new estimation approach, the unscented Kalman filter (UKF), and illustrate its potential as a tool for fitting nonlinear dynamic models in two ways:…
Application of multirate digital filter banks to wideband all-digital phase-locked loops design
Sadr, Ramin; Shah, Biren; Hinedi, Sami
1993-01-01
A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.
Institute of Scientific and Technical Information of China (English)
ZHANG JIA-SHU; XIAO XIAN-CI
2001-01-01
A multistage adaptive higher-order nonlinear finite impulse response (MAHONFIR) filter is proposed to predict chaotic time series. Using this approach, we may readily derive the decoupled parallel algorithm for the adaptation of the coefficients of the MAHONFIR filter, to guarantee a more rapid convergence of the adaptive weights to their optimal values. Numerical simulation results show that the MAHONFIR filters proposed here illustrate a very good performance for making an adaptive prediction of chaotic time series.
Single-step digital backpropagation for nonlinearity mitigation
DEFF Research Database (Denmark)
Secondini, Marco; Rommel, Simon; Meloni, Gianluca;
2015-01-01
Nonlinearity mitigation based on the enhanced split-step Fourier method (ESSFM) for the implementation of low-complexity digital backpropagation (DBP) is investigated and experimentally demonstrated. After reviewing the main computational aspects of DBP and of the conventional split-step Fourier...... method (SSFM), the ESSFM for dual-polarization signals is introduced. Computational complexity, latency, and power consumption of DBP based on the SSFM and ESSFM algorithms are estimated and compared. Effective low-complexity nonlinearity mitigation in a 112 Gb/s polarization-multiplexed QPSK system...... of the SSFM algorithm to achieve the same performance. An analysis of the computational complexity and structure of the two algorithms reveals that the overall complexity and power consumption of DBP are reduced by a factor of 16 with respect to a conventional implementation, while the computation time...
Nonlinear performance characterization in an eight-pole quasi-elliptic bandpass filter
Energy Technology Data Exchange (ETDEWEB)
Mateu, J [Centre Tecnologic de Telecomunicacions de Catalunya, Edifici Nexus, Gran Capita, 2nd Floor, Room 202-203, 08034 Barcelona (Spain); Collado, C [Universitat Politecnica de Catalunya, Department of Signal Theory and Communications, Campus Nord UPC, D3-Jordi Girona, 1-3, 08034 Barcelona (Spain); Menendez, O [Universitat Politecnica de Catalunya, Department of Signal Theory and Communications, Campus Nord UPC, D3-Jordi Girona, 1-3, 08034 Barcelona (Spain); O' Callaghan, J M [Universitat Politecnica de Catalunya, Department of Signal Theory and Communications, Campus Nord UPC, D3-Jordi Girona, 1-3, 08034 Barcelona (Spain)
2004-05-01
In this work we predict the nonlinear behaviour of an eight-pole quasi-elliptic bandpass high temperature superconducting (HTS) filter with an equivalent circuit extracted from intermodulation measurements performed at the centre of the filter passband. We present measurements that show that the equivalent circuit is able to predict the intermodulation products produced by the filter when driven by two in-band or out-of-band sinusoidal signals. Numerical techniques based on harmonic balance are used to extract the elements of the equivalent circuit and to simulate its nonlinear performance.
2-D nonlinear IIR-filters for image processing - An exploratory analysis
Bauer, P. H.; Sartori, M.
1991-01-01
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
2-D nonlinear IIR-filters for image processing - An exploratory analysis
Bauer, P. H.; Sartori, M.
1991-01-01
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
Directory of Open Access Journals (Sweden)
Jingjing Wu
2015-01-01
Full Text Available A robust particle filter (PF and its application to fault/defect detection of nonlinear system are investigated in this paper. First, an adaptive parametric model is exploited as the observation model for a nonlinear system. Second, by incorporating the parametric model, particle filter is employed to estimate more accurate hidden states for the nonlinear stochastic system. Third, by formulating the problem of defect detection within the hypothesis testing framework, the statistical properties of the proposed testing are established. Finally, experimental results demonstrate the effectiveness and robustness of the proposed detector on real defect detection and localization in images.
Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Lin, Chong
2016-12-13
In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example.
Grey Box Non-Linearities Modeling and Characterization of a BandPass BAW Filter
Directory of Open Access Journals (Sweden)
M. Mabrouk
2016-06-01
Full Text Available In this work, the non-linearities of a 3G/UMTS geared BandPass Bulk Acoustic Wave ladder filter composed of five resonators were modeled using non-linear modified Butterworth-Van Dyke model. The non-linear characteristics were measured and simulated, and they were compared and found to be fairly identical. The filter's central frequency is 2.12 GHz, the corresponding bandwidth is 61.55 MHz, and the quality factor is 34.55.
Method and system for training dynamic nonlinear adaptive filters which have embedded memory
Rabinowitz, Matthew (Inventor)
2002-01-01
Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.
Nonlinear Diffusion Filtering of the GOCE-Based Satellite-Only Mean Dynamic Topography
Cunderlik, Robert; Mikula, Karol
2015-03-01
The paper presents nonlinear diffusion filtering of the GOCE-based satellite-only mean dynamic topography (MDT). Our approach is based on a numerical solution to the nonlinear diffusion equation defined on the discretized Earth’s surface using the regularized surface Perona-Malik Model. For its numerical discretization we use a surface finite volume method. A key idea is that the diffusivity coefficient depends on the edge detector. It allows effectively reduce the stripping noise while preserve important gradients in filtered data. Numerical experiments present nonlinear filtering of the geopotential evaluated from the GO_CONS_GCF_2_ DIR_R5 model on the DTU13 mean sea surface. After filtering the geopotential is transformed into the MDT.
A novel strong tracking finite-difference extended Kalman filter for nonlinear eye tracking
Institute of Scientific and Technical Information of China (English)
ZHANG ZuTao; ZHANG JiaShu
2009-01-01
Non-Intrusive methods for eye tracking are Important for many applications of vision-based human computer interaction. However, due to the high nonlinearity of eye motion, how to ensure the robust-ness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into today's interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty In modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and im-prove the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions.
NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM
Institute of Scientific and Technical Information of China (English)
ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi
2005-01-01
Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.
Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter.
Directory of Open Access Journals (Sweden)
Roger Abächerli
Full Text Available Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10(-8 LSB. Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use of the suggested filters, it is possible to recover the original DC-coupled ECGs from AC-coupled ECGs, at least when a 0.05 Hz first order digital single pole high-pass filter is used for the AC-coupling.
Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter.
Abächerli, Roger; Isaksen, Jonas; Schmid, Ramun; Leber, Remo; Schmid, Hans-Jakob; Generali, Gianluca
2016-01-01
Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10(-8) LSB. Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use of the suggested filters, it is possible to recover the original DC-coupled ECGs from AC-coupled ECGs, at least when a 0.05 Hz first order digital single pole high-pass filter is used for the AC-coupling.
Finite-time H∞ filtering for non-linear stochastic systems
Hou, Mingzhe; Deng, Zongquan; Duan, Guangren
2016-09-01
This paper describes the robust H∞ filtering analysis and the synthesis of general non-linear stochastic systems with finite settling time. We assume that the system dynamic is modelled by Itô-type stochastic differential equations of which the state and the measurement are corrupted by state-dependent noises and exogenous disturbances. A sufficient condition for non-linear stochastic systems to have the finite-time H∞ performance with gain less than or equal to a prescribed positive number is established in terms of a certain Hamilton-Jacobi inequality. Based on this result, the existence of a finite-time H∞ filter is given for the general non-linear stochastic system by a second-order non-linear partial differential inequality, and the filter can be obtained by solving this inequality. The effectiveness of the obtained result is illustrated by a numerical example.
A New Adaptive Square-Root Unscented Kalman Filter for Nonlinear Systems with Additive Noise
Directory of Open Access Journals (Sweden)
Yong Zhou
2015-01-01
Full Text Available The Kalman filter (KF, extended KF, and unscented KF all lack a self-adaptive capacity to deal with system noise. This paper describes a new adaptive filtering approach for nonlinear systems with additive noise. Based on the square-root unscented KF (SRUKF, traditional Maybeck’s estimator is modified and extended to nonlinear systems. The square root of the process noise covariance matrix Q or that of the measurement noise covariance matrix R is estimated straightforwardly. Because positive semidefiniteness of Q or R is guaranteed, several shortcomings of traditional Maybeck’s algorithm are overcome. Thus, the stability and accuracy of the filter are greatly improved. In addition, based on three different nonlinear systems, a new adaptive filtering technique is described in detail. Specifically, simulation results are presented, where the new filter was applied to a highly nonlinear model (i.e., the univariate nonstationary growth model (UNGM. The UNGM is compared with the standard SRUKF to demonstrate its superior filtering performance. The adaptive SRUKF (ASRUKF algorithm can complete direct recursion and calculate the square roots of the variance matrixes of the system state and noise, which ensures the symmetry and nonnegative definiteness of the matrixes and greatly improves the accuracy, stability, and self-adaptability of the filter.
Automatic digital filtering for the accuracy improving of a digital holographic measurement system
Matrecano, Marcella; Miccio, Lisa; Persano, Anna; Quaranta, Fabio; Siciliano, Pietro; Ferraro, Pietro
2014-05-01
Digital holography (DH) is a well-established interferometric tool in optical metrology allowing the investigation of engineered surface shapes with microscale lateral resolution and nanoscale axial precision. With the advent of charged coupled devices (CCDs) with smaller pixel sizes, high speed computers and greater pixel numbers, DH became a very feasible technology which offers new possibilities for a large variety of applications. DH presents numerous advantages such as the direct access to the phase information, numerical correction of optical aberrations and the ability of a numerical refocusing from a single hologram. Furthermore, as an interferometric method, DH offers both a nodestructive and no-contact approach to very fragile objects combined with flexibility and a high sensitivity to geometric quantities such as thicknesses and displacements. These features recommend it for the solution of many imaging and measurements problems, such as microelectro-optomechanical systems (MEMS/MEOMS) inspection and characterization. In this work, we propose to improve the performance of a DH measurement on MEMS devices, through digital filters. We have developed an automatic procedure, inserted in the hologram reconstruction process, to selectively filter the hologram spectrum. The purpose is to provide very few noisy reconstructed images, thus increasing the accuracy of the conveyed information and measures performed on images. Furthermore, improving the image quality, we aim to make this technique application as simple and as accurate as possible.
Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
. The second contribution of this paper is to derive a new particle filter which we term the Mean Shifted Particle Filter (MSPFb). We show that the MSPFb outperforms the standard Particle Filter by delivering more precise state estimates, and in general the MSPFb has lower Monte Carlo variation in the reported...
Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology.
Ginsburg, Shoshana B; Lee, George; Ali, Sahirzeeshan; Madabhushi, Anant
2016-01-01
Quantitative histomorphometry (QH) refers to the process of computationally modeling disease appearance on digital pathology images by extracting hundreds of image features and using them to predict disease presence or outcome. Since constructing a robust and interpretable classifier is challenging in a high dimensional feature space, dimensionality reduction (DR) is often implemented prior to classifier construction. However, when DR is performed it can be challenging to quantify the contribution of each of the original features to the final classification result. We have previously presented a method for scoring features based on their importance for classification on an embedding derived via principal components analysis (PCA). However, nonlinear DR involves the eigen-decomposition of a kernel matrix rather than the data itself, compounding the issue of classifier interpretability. In this paper we present feature importance in nonlinear embeddings (FINE), an extension of our PCA-based feature scoring method to kernel PCA (KPCA), as well as several NLDR algorithms that can be cast as variants of KPCA. FINE is applied to four digital pathology datasets to identify key QH features for predicting the risk of breast and prostate cancer recurrence. Measures of nuclear and glandular architecture and clusteredness were found to play an important role in predicting the likelihood of recurrence of both breast and prostate cancers. Compared to the t-test, Fisher score, and Gini index, FINE was able to identify a stable set of features that provide good classification accuracy on four publicly available datasets from the NIPS 2003 Feature Selection Challenge.
A filter algorithm for multi-measurement nonlinear system with parameter perturbation
Institute of Scientific and Technical Information of China (English)
GUO Yun-fei; WEI Wei; XUE An-ke; MAO Dong-cai
2006-01-01
An improved interacting multiple models particle filter (IMM-PF) algorithm is proposed for multi-measurement nonlinear system with parameter perturbation. It divides the perturbation region into sub-regions and assigns each of them a particle filter. Hence the perturbation problem is converted into a multi-model filters problem. It combines the multiple measurements into a fusion value according to their likelihood function. In the simulation study, we compared it with the IMM-KF and the H-infinite filter; the results testify to its advantage over the other two methods.
Signal-to-noise-ratio analysis for nonlinear N-ary phase filters.
Miller, Paul C
2007-09-01
The problem of recognizing targets in nonoverlapping clutter using nonlinear N-ary phase filters is addressed. Using mathematical analysis, expressions were derived for an N-ary phase filter and the intensity variance of an optical correlator output. The N-ary phase filter was shown to consist of an infinite sum of harmonic terms whose periodicity was determined by N. For the intensity variance, it was found that under certain conditions the variance was minimized due to a previously undiscovered phase quadrature effect. Comparison showed that optimal real filters produced greater signal-to-noise-ratio values than the continuous phase versions as a consequence of this effect.
Design and responses of Butterworth and critically damped digital filters.
Robertson, D Gordon E; Dowling, James J
2003-12-01
For many years the Butterworth lowpass filter has been used to smooth many kinds of biomechanical data, despite the fact that it is underdamped and therefore overshoots and/or undershoots data during rapid transitions. A comparison of the conventional Butterworth filter with a critically damped filter shows that the critically damped filter not only removes the undershooting and overshooting, but has a superior rise time during rapid transitions. While analog filters always create phase distortion, both the critically damped and Butterworth filters can be modified to become zero-lag filters when the data are processed in both the forward and reverse directions. In such cases little improvement is realized by applying multiple passes. The Butterworth filter has superior 'roll-off' (attenuation of noise above the cutoff frequency) than the critically damped filter, but by increasing the number of passes of the critically damped filter the same 'roll-off' can be achieved. In summary, the critically damped filter was shown to have superior performance in the time domain than the Butterworth filter, but for data that need to be double differentiated (e.g. displacement data) the Butterworth filter may still be the better choice.
Digital controller for hybrid filter in HVDC based on approximate inverse system
Institute of Scientific and Technical Information of China (English)
SU Ling; ZHAO Dong-yuan; CHEN Jian-ye; WANG Zan-ji
2006-01-01
In order to eliminate the characteristic harmonics in high voltage direct current (HVDC) transmission systems and to simplify the analog controller structure,this paper proposes a new digital controller by adopting an approximate inverse system control strategy according to the frequency response characteristic of the hybrid power filter.The proposed digital controller is implemented with a TMS320C32 DSP,including a series of parallel digital band-pass filters,phase shifters and amplifiers.The results of both simulations based on PSCAD and experiments on a 30 kVA HVDC system prove that the proposed digital control system is stable and efficient for eliminating the harmonics.
Peterson, A.; Narasimha, M.; Narayan, S.
1980-01-01
The system design of a wideband (8 MHz) million-channel digital spectrum analyzer for use with a SETI receiver is presented. The analyzer makes use of a digital bandpass filter bank for transforming the wideband input signal into a specified number (120) of uniform narrowband output channels by the use of a Fourier transform digital processor combined with a prototype digital weighting network (finite impulse response filter). The output is then processed separately by 120 microprocessor-based discrete Fourier transform computers, each producing 8190 output channels of approximately 8 Hz bandwidth by the use of an 8190-point prime factor algorithm.
IDENTIFICATION OF NONLINEAR DYNAMIC SYSTEMS:TIME-FREQUENCY FILTERING AND SKELETON CURVES
Institute of Scientific and Technical Information of China (English)
王丽丽; 张景绘
2001-01-01
The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O . F nonlinear system.A masking operator on definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system ( GSLS ). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. More over, an identification method is proposed through the skeleton curves and the time frequency filtering technique.
Interaction of Lyapunov vectors in the formulation of the nonlinear extension of the Kalman filter.
Palatella, Luigi; Trevisan, Anna
2015-04-01
When applied to strongly nonlinear chaotic dynamics the extended Kalman filter (EKF) is prone to divergence due to the difficulty of correctly forecasting the forecast error probability density function. In operational forecasting applications ensemble Kalman filters circumvent this problem with empirical procedures such as covariance inflation. This paper presents an extension of the EKF that includes nonlinear terms in the evolution of the forecast error estimate. This is achieved starting from a particular square-root implementation of the EKF with assimilation confined in the unstable subspace (EKF-AUS), that is, the span of the Lyapunov vectors with non-negative exponents. When the error evolution is nonlinear, the space where it is confined is no more restricted to the unstable and neutral subspace causing filter divergence. The algorithm presented here, denominated EKF-AUS-NL, includes the nonlinear terms in the error dynamics: These result from the nonlinear interaction among the leading Lyapunov vectors and account for all directions where the error growth may take place. Numerical results show that with the nonlinear terms included, filter divergence can be avoided. We test the algorithm on the Lorenz96 model, showing very promising results.
Data Acquisition and Digital Filtering for Infrasonic Records on Active Volcanoes
Directory of Open Access Journals (Sweden)
José Chilo
2007-03-01
Full Text Available This paper presents the design of a digital data acquisition system for volcanic infrasound records. The system includes four electret condenser element microphones, a QF4A512 programmable signal converter from Quickfilter Technologies and a MSP430 microcontroller from Texas Instruments. The signal output of every microphone is converted to digital via a 16-bit Analog to Digital Converter (ADC. To prevent errors in the conversion process, Anti-Aliasing Filters are employed prior to the ADC. Digital filtering is performed after the ADC using a Digital Signal Processor, which is implemented on the QF4A512. The four digital signals are summed to get only one signal. Data storing and digital wireless data transmission will be described in a future paper.
Directory of Open Access Journals (Sweden)
Kaustubh Gaikwad
2016-06-01
Full Text Available ASIC Chips and Digital Signal Processors are generally used for implementing digital filters. Now days the advanced technologies lead to use of field programmable Gate Array (FPGA for the implementation of Digital Filters.The present paper deals with Design and Implementation of Digital IIR Chebyshev type II filter using Xilinx System Generator. The Quantization and Overflow are main crucial parameters while designing the filter on FPGA and that need to be consider for getting the stability of the filter. As compare to the conventional DSP the speed of the system is increased by implementation on FPGA. Digital Chebyshev type II filter is initially designed analytically for the desired Specifications and simulated using Simulink in Matlab environment. This paper also proposes the method to implement Digital IIR Chebyshev type II Filter by using XSG platform. The filter has shown good performance for noise removal in ECG
NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL
Institute of Scientific and Technical Information of China (English)
WANG Shu-chang; HUANG Si-xun; ZHANG Wei-min; ZHU Xiao-qian; CAO Xiao-qun; LI Yi
2008-01-01
Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation "Weather Research and Forecasting Model". Severaloptions of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.
A new greedy search method for the design of digital IIR filter
Directory of Open Access Journals (Sweden)
Ranjit Kaur
2015-07-01
Full Text Available A new greedy search method is applied in this paper to design the optimal digital infinite impulse response (IIR filter. The greedy search method is based on binary successive approximation (BSA and evolutionary search (ES. The suggested greedy search method optimizes the magnitude response and the phase response simultaneously and also finds the lowest order of the filter. The order of the filter is controlled by a control gene whose value is also optimized along with the filter coefficients to obtain optimum order of designed IIR filter. The stability constraints of IIR filter are taken care of during the design procedure. To determine the trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. The proposed approach is effectively applied to solve the multiobjective optimization problems of designing the digital low-pass (LP, high-pass (HP, bandpass (BP, and bandstop (BS filters. It has been demonstrated that this technique not only fulfills all types of filter performance requirements, but also the lowest order of the filter can be found. The computational experiments show that the proposed approach gives better digital IIR filters than the existing evolutionary algorithm (EA based methods.
Weighted Ensemble Square Root Filters for Non-linear, Non-Gaussian, Data Assimilation
Livings, D. M.; van Leeuwen, P.
2012-12-01
In recent years the Ensemble Kalman Filter (EnKF) has become widely-used in both operational and research data assimilation systems. The particle filter is an alternative ensemble-based algorithm that offers the possibility of improved performance in non-linear and non-Gaussian problems. Papadakis et al (2010) introduced the Weighted Ensemble Kalman Filter (WEnKF) as a combination of the best features of the EnKF and the particle filter. Published work on the WEnKF has so far concentrated on the formulation of the EnKF in which observations are perturbed; no satisfactory general framework has been given for particle filters based on the alternative formulation of the EnKF known as the ensemble square root filter. This presentation will provide such a framework and show how several popular ensemble square root filters fit into it. No linear or Gaussian assumptions about the dynamical or observational models will be necessary. By examining the algorithms closely, shortcuts will be identified that increase both the simplicity and the efficiency of the resulting particle filter in comparison with a naive implementation. A procedure will be given for simply converting an existing ensemble square root filter into a particle filter. The procedure will not be limited to basic ensemble square root filters, but will be able to incorporate common variations such as covariance inflation without making any approximations.
Directory of Open Access Journals (Sweden)
Hua-Ming Qian
2014-01-01
Full Text Available A robust filtering problem is formulated and investigated for a class of nonlinear systems with correlated noises, packet losses, and multiplicative noises. The packet losses are assumed to be independent Bernoulli random variables. The multiplicative noises are described as random variables with bounded variance. Different from the traditional robust filter based on the assumption that the process noises are uncorrelated with the measurement noises, the objective of the addressed robust filtering problem is to design a recursive filter such that, for packet losses and multiplicative noises, the state prediction and filtering covariance matrices have the optimized upper bounds in the case that there are correlated process and measurement noises. Two examples are used to illustrate the effectiveness of the proposed filter.
A phase-equalized digital multirate filter for 50 Hz signal processing
Energy Technology Data Exchange (ETDEWEB)
Vainio, O. [Tampere University of Technology, Signal Processing Laboratory, Tampere (Finland)
1997-12-31
A new multistage digital filter is proposed for 50 Hz line frequency signal processing in zero-crossing detectors and synchronous power systems. The purpose of the filter is to extract the fundamental sinusoidal signal from noise and impulsive disturbances so that the output is accurately in phase with the primary input signal. This is accomplished with a cascade of a median filter, a linear-phase FIR filter, and a phase corrector. A 10 kHz output timing resolution is achieved by up-sampling with a customized interpolation filter. (orig.) 15 refs.
Improvement of nonlinear diffusion equation using relaxed geometric mean filter for low PSNR images
DEFF Research Database (Denmark)
Nadernejad, Ehsan
2013-01-01
A new method to improve the performance of low PSNR image denoising is presented. The proposed scheme estimates edge gradient from an image that is regularised with a relaxed geometric mean filter. The proposed method consists of two stages; the first stage consists of a second order nonlinear...... anisotropic diffusion equation with new neighboring structure and the second is a relaxed geometric mean filter, which processes the output of nonlinear anisotropic diffusion equation. The proposed algorithm enjoys the benefit of both nonlinear PDE and relaxed geometric mean filter. In addition, the algorithm...... will not introduce any artefacts, and preserves image details, sharp corners, curved structures and thin lines. Comparison of the results obtained by the proposed method, with those of other methods, shows that a noticeable improvement in the quality of the denoised images, that were evaluated subjectively...
Iterative nonlinear ISI cancellation in optical tilted filter-based Nyquist 4-PAM system
Ju, Cheng; Liu, Na
2016-09-01
The conventional double sideband (DSB) modulation and direct detection scheme suffers from severer power fading, linear and nonlinear inter-symbol interference (ISI) caused by fiber dispersion and square-law direct detection. The system's frequency response deteriorates at high frequencies owing to the limited device bandwidth. Moreover, the linear and nonlinear ISI is enhanced induced by the bandwidth limited effect. In this paper, an optical tilted filter is used to mitigate the effect of power fading, and improve the high frequency response of bandwidth limited device in Nyquist 4-ary pulse amplitude modulation (4-PAM) system. Furtherly, iterative technique is introduced to mitigate the nonlinear ISI caused by the combined effects of electrical Nyquist filter, limited device bandwidth, optical tilted filter, dispersion, and square-law photo-detection. Thus, the system's frequency response is greatly improved and the delivery distance can be extended.
Nonlinear Kalman Filtering in Affine Term Structure Models
DEFF Research Database (Denmark)
Christoffersen, Peter; Dorion, Christian; Jacobs, Kris;
When the relationship between security prices and state variables in dynamic term structure models is nonlinear, existing studies usually linearize this relationship because nonlinear fi…ltering is computationally demanding. We conduct an extensive investigation of this linearization and analyze...... Monte Carlo experiment demonstrates that the unscented Kalman fi…lter is much more accurate than its extended counterpart in fi…ltering the states and forecasting swap rates and caps. Our fi…ndings suggest that the unscented Kalman fi…lter may prove to be a good approach for a number of other problems...... in fi…xed income pricing with nonlinear relationships between the state vector and the observations, such as the estimation of term structure models using coupon bonds and the estimation of quadratic term structure models....
Design of Stable Circularly Symmetric Two-Dimensional GIC Digital Filters Using PLSI Polynomials
Directory of Open Access Journals (Sweden)
K. Ramar
2007-01-01
Full Text Available A method for designing stable circularly symmetric two-dimensional digital filters is presented. Two-dimensional discrete transfer functions of the rotated filters are obtained from stable one-dimensional analog-filter transfer functions by performing rotation and then applying the double bilinear transformation. The resulting filters which may be unstable due to the presence of nonessential singularities of the second kind are stabilized by using planar least-square inverse polynomials. The stabilized rotated filters are then realized by using the concept of generalized immittance converter. The proposed method is simple and straight forward and it yields stable digital filter structures possessing many salient features such as low noise, low sensitivity, regularity, and modularity which are attractive for VLSI implementation.
Directory of Open Access Journals (Sweden)
Nisha Haridas
2016-04-01
Full Text Available A low complexity digital hearing aid is designed using a set of subband filters, for various audiograms. It is important for the device to be made of simple hardware, so that the device becomes less bulky. Hence, a low complexity design of reconfigurable filter is proposed in this paper. The tunable filter structure is designed using Farrow based variable bandwidth filter. The coefficients of the filter are expressed in canonic signed digit format. The performance can be enhanced using optimization algorithm. Here, we have explored the strength of hybrid evolutionary algorithms and compared their various combinations to select a proper coefficient representation for the Farrow based filter, which results in low complexity implementation.
Control of underactuated robotic systems with the use of the derivative-free nonlinear Kalman filter
Rigatos, Gerasimos G.; Siano, Pierluigi
2013-10-01
The Derivative-free nonlinear Kalman Filter is used for developing a robust controller which can be applied to underactuated MIMO robotic systems. Using differential flatness theory it is shown that the model of a closed-chain 2-DOF robotic manipulator can be transformed to linear canonical form. For the linearized equivalent of the robotic system it is shown that a state feedback controller can be designed. Since certain elements of the state vector of the linearized system can not be measured directly, it is proposed to estimate them with the use of a novel filtering method, the so-called Derivative-free nonlinear Kalman Filter. Moreover, by redesigning the Kalman Filter as a disturbance observer, it is is shown that one can estimate simultaneously external disturbances terms that affect the robotic model or disturbance terms which are associated with parametric uncertainty.
Robust Filtering for a Class of Networked Nonlinear Systems With Switching Communication Channels.
Zhang, Lixian; Yin, Xunyuan; Ning, Zepeng; Ye, Dong
2016-02-15
This paper is concerned with the problem of robust filter design for a class of discrete-time networked nonlinear systems. The Takagi-Sugeno fuzzy model is employed to represent the underlying nonlinear dynamics. A multi-channel communication scheme that involves a channel switching phenomenon described by a Markov chain is proposed for data transmission. Two typical communication imperfections, network-induced time-varying delays and packet dropouts are considered in each channel. The objective of this paper is to design an admissible filter such that the filter error system is stochastically stable and ensures a prescribed disturbance attenuation level bound. Based on the Lyapunov-Krasovskii functional method and matrix inequality techniques, sufficient conditions on the existence of the desired filter are obtained. A numerical example is provided to illustrate the effectiveness of the proposed design approach.
Institute of Scientific and Technical Information of China (English)
Shuo Zhang,Yan Zhao,Min Li,; Jianhui Zhao
2015-01-01
The global y optimal recursive filtering problem is stu-died for a class of systems with random parameter matrices, stochastic nonlinearities, correlated noises and missing measure-ments. The stochastic nonlinearities are presented in the system model to reflect multiplicative random disturbances, and the addi-tive noises, process noise and measurement noise, are assumed to be one-step autocorrelated as wel as two-step cross-correlated. A series of random variables is introduced as the missing rates governing the intermittent measurement losses caused by un-favorable network conditions. The aim of the addressed filtering problem is to design an optimal recursive filter for the uncertain systems based on an innovation approach such that the filtering error is global y minimized at each sampling time. A numerical simulation example is provided to il ustrate the effectiveness and applicability of the proposed algorithm.
A class of high-pass digital MTI filters with nonuniform PRF
Prinsen, P.J.A.
1973-01-01
A class of digital feed-forward filters is developed, satisfying the requirement of a maximally flat stopband characteristic at zero frequency if the pulse-repetition frequency is modulated. A simple algorithm is given to obtain the filter coefficients. Some properties are summarized
Hybrid three-dimensional variation and particle filtering for nonlinear systems
Institute of Scientific and Technical Information of China (English)
Leng Hong-Ze; Song Jun-Qiang
2013-01-01
This work addresses the problem of estimating the states of nonlinear dynamic systems with sparse observations.We present a hybrid three-dimensional variation (3DVar) and particle piltering (PF) method,which combines the advantages of 3DVar and particle-based filters.By minimizing the cost function,this approach will produce a better proposal distribution of the state.Afterwards the stochastic resampling step in standard PF can be avoided through a deterministic scheme.The simulation results show that the performance of the new method is superior to the traditional ensemble Kalman filtering (EnKF) and the standard PF,especially in highly nonlinear systems.
A simple new filter for nonlinear high-dimensional data assimilation
Tödter, Julian; Kirchgessner, Paul; Ahrens, Bodo
2015-04-01
The ensemble Kalman filter (EnKF) and its deterministic variants, mostly square root filters such as the ensemble transform Kalman filter (ETKF), represent a popular alternative to variational data assimilation schemes and are applied in a wide range of operational and research activities. Their forecast step employs an ensemble integration that fully respects the nonlinear nature of the analyzed system. In the analysis step, they implicitly assume the prior state and observation errors to be Gaussian. Consequently, in nonlinear systems, the analysis mean and covariance are biased, and these filters remain suboptimal. In contrast, the fully nonlinear, non-Gaussian particle filter (PF) only relies on Bayes' theorem, which guarantees an exact asymptotic behavior, but because of the so-called curse of dimensionality it is exposed to weight collapse. This work shows how to obtain a new analysis ensemble whose mean and covariance exactly match the Bayesian estimates. This is achieved by a deterministic matrix square root transformation of the forecast ensemble, and subsequently a suitable random rotation that significantly contributes to filter stability while preserving the required second-order statistics. The forecast step remains as in the ETKF. The proposed algorithm, which is fairly easy to implement and computationally efficient, is referred to as the nonlinear ensemble transform filter (NETF). The properties and performance of the proposed algorithm are investigated via a set of Lorenz experiments. They indicate that such a filter formulation can increase the analysis quality, even for relatively small ensemble sizes, compared to other ensemble filters in nonlinear, non-Gaussian scenarios. Furthermore, localization enhances the potential applicability of this PF-inspired scheme in larger-dimensional systems. Finally, the novel algorithm is coupled to a large-scale ocean general circulation model. The NETF is stable, behaves reasonably and shows a good
Sequential nonlinear tracking filter without requirement of measurement decorrelation
Institute of Scientific and Technical Information of China (English)
Taifan Quan
2015-01-01
Sequential measurement processing is of benefit to both estimation accuracy and computational efficiency. When the noises are correlated across the measurement components, decorrelation based on covariance matrix factorization is required in the previous methods in order to perform sequential updates properly. A new sequential processing method, which carries out the sequential updates directly using the correlated measurement components, is proposed. And a typical sequential processing example is investigated, where the converted position measure-ments are used to estimate target states by standard Kalman filtering equations and the converted Doppler measurements are then incorporated into a minimum mean squared error (MMSE) estimator with the updated cross-covariance involved to account for the correlated errors. Numerical simulations demonstrate the superiority of the proposed new sequential processing in terms of better accuracy and consistency than the conventional sequential filter based on measurement decorrelation.
Design and Implementation of Digital Filter Bank to Reduce Noise and Reconstruct the Input Signals
Directory of Open Access Journals (Sweden)
Kawser Ahammed
2015-04-01
Full Text Available The main theme of this paper is to reduce noise from the noisy composite signal and reconstruct the input signals from the composite signal by designing FIR digital filter bank. In this work, three sinusoidal signals of different frequencies and amplitudes are combined to get composite signal and a low frequency noise signal is added with the composite signal to get noisy composite signal. Finally noisy composite signal is filtered by using FIR digital filter bank to reduce noise and reconstruct the input signals.
A Finitely Additive White Noise Approach to Nonlinear Filtering.
1982-10-01
processes, J. of Multivariate Analysis, 1 (1971). [181. J.L. Lions, Equation differentielles operationnelles et problemes aux limites, Springer-Verlag (1961...Verlag, (1979). [24]. J. Szpirglas, Sur l’equivalence d’equations differentielles stochastiques a valeurs mesures intervenant dans le filtrage Markovien...filtering.I Thi s re ea rch h s e u p p o rted by AF OSR Gran t No . 49620 82 r 0009 . 0. Introduction The theory of Ito stochastic differential equations
Real-time adaptive filtering of dental drill noise using a digital signal processor
2006-01-01
The application of noise reduction methods requires the integration of acoustics engineering and digital signal processing, which is well served by a mechatronic approach as described in this paper. The Normalised Least Mean Square (NLMS) algorithm is implemented on the Texas Instruments TMS320C6713 DSK Digital Signal Processor (DSP) as an adaptive digital filter for dental drill noise. Blocks within the Matlab/Simulink Signal Processing Blockset and the Embedded Target for TI C6000 DSP famil...
Optimal design study of high order FIR digital filters based on neural network algorithm
Institute of Scientific and Technical Information of China (English)
王小华; 何怡刚
2004-01-01
An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved,and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass,bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely . The presented optimal design approach of high order FIR digital filter is significantly effective.
AN ITERATIVE ALGORITHM FOR OPTIMAL DESIGN OF NON-FREQUENCY-SELECTIVE FIR DIGITAL FILTERS
Institute of Scientific and Technical Information of China (English)
Duan Miyi; Sun Chunlai; Liu Xin; Tian Xinguang
2008-01-01
This paper proposes a novel iterative algorithm for optimal design of non-frequency-se-lective Finite Impulse Response (FIR) digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter,the key idea of the algorithm is minimizing the approximation error by succes-sively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure,the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably,the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.
Directory of Open Access Journals (Sweden)
Y. Orlov
2002-01-01
Full Text Available The paper is intended to be of tutorial value for Schwartz' distributions theory in nonlinear setting. Mathematical models are presented for nonlinear systems which admit both standard and impulsive inputs. These models are governed by differential equations in distributions whose meaning is generalized to involve nonlinear, non single-valued operating over distributions. The set of generalized solutions of these differential equations is defined via closure, in a certain topology, of the set of the conventional solutions corresponding to standard integrable inputs. The theory is exemplified by mechanical systems with impulsive phenomena, optimal impulsive feedback synthesis, sampled-data filtering of stochastic and deterministic dynamic systems.
3D early embryogenesis image filtering by nonlinear partial differential equations.
Krivá, Z; Mikula, K; Peyriéras, N; Rizzi, B; Sarti, A; Stasová, O
2010-08-01
We present nonlinear diffusion equations, numerical schemes to solve them and their application for filtering 3D images obtained from laser scanning microscopy (LSM) of living zebrafish embryos, with a goal to identify the optimal filtering method and its parameters. In the large scale applications dealing with analysis of 3D+time embryogenesis images, an important objective is a correct detection of the number and position of cell nuclei yielding the spatio-temporal cell lineage tree of embryogenesis. The filtering is the first and necessary step of the image analysis chain and must lead to correct results, removing the noise, sharpening the nuclei edges and correcting the acquisition errors related to spuriously connected subregions. In this paper we study such properties for the regularized Perona-Malik model and for the generalized mean curvature flow equations in the level-set formulation. A comparison with other nonlinear diffusion filters, like tensor anisotropic diffusion and Beltrami flow, is also included. All numerical schemes are based on the same discretization principles, i.e. finite volume method in space and semi-implicit scheme in time, for solving nonlinear partial differential equations. These numerical schemes are unconditionally stable, fast and naturally parallelizable. The filtering results are evaluated and compared first using the Mean Hausdorff distance between a gold standard and different isosurfaces of original and filtered data. Then, the number of isosurface connected components in a region of interest (ROI) detected in original and after the filtering is compared with the corresponding correct number of nuclei in the gold standard. Such analysis proves the robustness and reliability of the edge preserving nonlinear diffusion filtering for this type of data and lead to finding the optimal filtering parameters for the studied models and numerical schemes. Further comparisons consist in ability of splitting the very close objects which
Design of Low Pass Digital FIR Filter Using Cuckoo Search Algorithm
Directory of Open Access Journals (Sweden)
Taranjit Singh
2014-08-01
Full Text Available This paper presents a novel approach of designing linear phase FIR low pass filter using cuckoo Search Algorithm (CSA. FIR filter design is a multi-modal optimization problem. The conventional optimization techniques are not efficient for digital filter design. An iterative method is introduced to find the best solution of FIR filter design problem.Flat passband and high stopband attenuation are the major characteristics required in FIR filter design. To achieve these characteristics, a Cuckoo Search algorithm (CSA is proposed in this paper. CSA have been used here for the design of linear phase finite impulse response (FIR filters. Results are presented in this paper that seems to be promising tool for FIR filter design
Design of efficient circularly symmetric two-dimensional variable digital FIR filters.
Bindima, Thayyil; Elias, Elizabeth
2016-05-01
Circularly symmetric two-dimensional (2D) finite impulse response (FIR) filters find extensive use in image and medical applications, especially for isotropic filtering. Moreover, the design and implementation of 2D digital filters with variable fractional delay and variable magnitude responses without redesigning the filter has become a crucial topic of interest due to its significance in low-cost applications. Recently the design using fixed word length coefficients has gained importance due to the replacement of multipliers by shifters and adders, which reduces the hardware complexity. Among the various approaches to 2D design, transforming a one-dimensional (1D) filter to 2D by transformation, is reported to be an efficient technique. In this paper, 1D variable digital filters (VDFs) with tunable cut-off frequencies are designed using Farrow structure based interpolation approach, and the sub-filter coefficients in the Farrow structure are made multiplier-less using canonic signed digit (CSD) representation. The resulting performance degradation in the filters is overcome by using artificial bee colony (ABC) optimization. Finally, the optimized 1D VDFs are mapped to 2D using generalized McClellan transformation resulting in low complexity, circularly symmetric 2D VDFs with real-time tunability.
A Nonlinear Entropic Variational Model for Image Filtering
Directory of Open Access Journals (Sweden)
Krim Hamid
2004-01-01
Full Text Available We propose an information-theoretic variational filter for image denoising. It is a result of minimizing a functional subject to some noise constraints, and takes a hybrid form of a negentropy variational integral for small gradient magnitudes and a total variational integral for large gradient magnitudes. The core idea behind this approach is to use geometric insight in helping to construct regularizing functionals and avoiding a subjective choice of a prior in maximum a posteriori estimation. Illustrative experimental results demonstrate a much improved performance of the approach in the presence of Gaussian and heavy-tailed noise.
Sequential Monte Carlo methods for nonlinear discrete-time filtering
Bruno, Marcelo GS
2013-01-01
In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable.We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in line
Variance-Constrained Multiobjective Control and Filtering for Nonlinear Stochastic Systems: A Survey
Directory of Open Access Journals (Sweden)
Lifeng Ma
2013-01-01
Full Text Available The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H2/H∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out.
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 st
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
Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel
2015-10-01
A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).
Astroza, Rodrigo; Ebrahimian, Hamed; Conte, Joel P.
2015-03-01
This paper describes a novel framework that combines advanced mechanics-based nonlinear (hysteretic) finite element (FE) models and stochastic filtering techniques to estimate unknown time-invariant parameters of nonlinear inelastic material models used in the FE model. Using input-output data recorded during earthquake events, the proposed framework updates the nonlinear FE model of the structure. The updated FE model can be directly used for damage identification and further used for damage prognosis. To update the unknown time-invariant parameters of the FE model, two alternative stochastic filtering methods are used: the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). A three-dimensional, 5-story, 2-by-1 bay reinforced concrete (RC) frame is used to verify the proposed framework. The RC frame is modeled using fiber-section displacement-based beam-column elements with distributed plasticity and is subjected to the ground motion recorded at the Sylmar station during the 1994 Northridge earthquake. The results indicate that the proposed framework accurately estimate the unknown material parameters of the nonlinear FE model. The UKF outperforms the EKF when the relative root-mean-square error of the recorded responses are compared. In addition, the results suggest that the convergence of the estimate of modeling parameters is smoother and faster when the UKF is utilized.
ESTIMATE ACCURACY OF NONLINEAR COEFFICIENTS OF SQUEEZEFILM DAMPER USING STATE VARIABLE FILTER METHOD
Institute of Scientific and Technical Information of China (English)
1998-01-01
The estimate model for a nonlinear system of squeeze-film damper (SFD) is described.The method of state variable filter (SVF) is used to estimate the coefficients of SFD.The factors which are critical to the estimate accuracy are discussed.
A Low Power Linear Phase Digital FIR Filter for Wearable ECG Devices.
Lian, Yong; Yu, Jianghong
2005-01-01
In this paper we present a low power linear phase digital FIR filter which is a part of an ECG-on-Chip. The ECG-on-Chip can be embedded into clothing to acquire the electrocardiogram (ECG) signal and send a warning message to a mobile phone or PDA if an abnormal ECG is detected. The proposed new filter structure significantly reduces the arithmetic operations for each sample which in turn lowers the power consumption. The filter is developed based on the interpolated finite impulse filter technique and is very attractive for a low cost and low power VLSI implementation.
A nonlinear filtering algorithm for denoising HR(S)TEM micrographs
Energy Technology Data Exchange (ETDEWEB)
Du, Hongchu, E-mail: h.du@fz-juelich.de [Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Jülich Research Centre, Jülich, 52425 (Germany); Central Facility for Electron Microscopy (GFE), RWTH Aachen University, Aachen 52074 (Germany); Peter Grünberg Institute, Jülich Research Centre, Jülich 52425 (Germany)
2015-04-15
Noise reduction of micrographs is often an essential task in high resolution (scanning) transmission electron microscopy (HR(S)TEM) either for a higher visual quality or for a more accurate quantification. Since HR(S)TEM studies are often aimed at resolving periodic atomistic columns and their non-periodic deviation at defects, it is important to develop a noise reduction algorithm that can simultaneously handle both periodic and non-periodic features properly. In this work, a nonlinear filtering algorithm is developed based on widely used techniques of low-pass filter and Wiener filter, which can efficiently reduce noise without noticeable artifacts even in HR(S)TEM micrographs with contrast of variation of background and defects. The developed nonlinear filtering algorithm is particularly suitable for quantitative electron microscopy, and is also of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM. - Highlights: • A nonlinear filtering algorithm for denoising HR(S)TEM images is developed. • It can simultaneously handle both periodic and non-periodic features properly. • It is particularly suitable for quantitative electron microscopy. • It is of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM.
Directory of Open Access Journals (Sweden)
E. L. Dmitrieva
2016-05-01
Full Text Available Basic peculiarities of nonlinear Kalman filtering algorithm applied to processing of interferometric signals are considered. Analytical estimates determining statistical characteristics of signal values prediction errors were obtained and analysis of errors histograms taking into account variations of different parameters of interferometric signal was carried out. Modeling of the signal prediction procedure with known fixed parameters and variable parameters of signal in the algorithm of nonlinear Kalman filtering was performed. Numerical estimates of prediction errors for interferometric signal values were obtained by formation and analysis of the errors histograms under the influence of additive noise and random variations of amplitude and frequency of interferometric signal. Nonlinear Kalman filter is shown to provide processing of signals with randomly variable parameters, however, it does not take into account directly the linearization error of harmonic function representing interferometric signal that is a filtering error source. The main drawback of the linear prediction consists in non-Gaussian statistics of prediction errors including cases of random deviations of signal amplitude and/or frequency. When implementing stochastic filtering of interferometric signals, it is reasonable to use prediction procedures based on local statistics of a signal and its parameters taken into account.
Shen, Zheqi; Tang, Youmin
2016-04-01
The ensemble Kalman particle filter (EnKPF) is a combination of two Bayesian-based algorithms, namely, the ensemble Kalman filter (EnKF) and the sequential importance resampling particle filter(SIR-PF). It was recently introduced to address non-Gaussian features in data assimilation for highly nonlinear systems, by providing a continuous interpolation between the EnKF and SIR-PF analysis schemes. In this paper, we first extend the EnKPF algorithm by modifying the formula for the computation of the covariancematrix, making it suitable for nonlinear measurement functions (we will call this extended algorithm nEnKPF). Further, a general form of the Kalman gain is introduced to the EnKPF to improve the performance of the nEnKPF when the measurement function is highly nonlinear (this improved algorithm is called mEnKPF). The Lorenz '63 model and Lorenz '96 model are used to test the two modified EnKPF algorithms. The experiments show that the mEnKPF and nEnKPF, given an affordable ensemble size, can perform better than the EnKF for the nonlinear systems with nonlinear observations. These results suggest a promising opportunity to develop a non-Gaussian scheme for realistic numerical models.
The Use of Nonlinear Constitutive Equations to Evaluate Draw Resistance and Filter Ventilation
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Eitzinger B
2014-12-01
Full Text Available This study investigates by nonlinear constitutive equations the influence of tipping paper, cigarette paper, filter, and tobacco rod on the degree of filter ventilation and draw resistance. Starting from the laws of conservation, the path to the theory of fluid dynamics in porous media and Darcy's law is reviewed and, as an extension to Darcy's law, two different nonlinear pressure drop-flow relations are proposed. It is proven that these relations are valid constitutive equations and the partial differential equations for the stationary flow in an unlit cigarette covering anisotropic, inhomogeneous and nonlinear behaviour are derived. From these equations a system of ordinary differential equations for the one-dimensional flow in the cigarette is derived by averaging pressure and velocity over the cross section of the cigarette. By further integration, the concept of an electrical analog is reached and discussed in the light of nonlinear pressure drop-flow relations. By numerical calculations based on the system of ordinary differential equations, it is shown that the influence of nonlinearities cannot be neglected because variations in the degree of filter ventilation can reach up to 20% of its nominal value.
Effects of Analog-to-Digital Converter Nonlinearities on Radar Range-Doppler Maps
Energy Technology Data Exchange (ETDEWEB)
Doerry, Armin Walter [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dubbert, Dale F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tise, Bertice L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-07-01
Radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. These throw off harmonic spurs that are sometimes detected as false alarms. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this report the relationship of INL to GMTI performance.
Nonlinear filtering techniques for noisy geophysical data: Using big data to predict the future
Moore, J. M.
2014-12-01
Chaos is ubiquitous in physical systems. Within the Earth sciences it is readily evident in seismology, groundwater flows and drilling data. Models and workflows have been applied successfully to understand and even to predict chaotic systems in other scientific fields, including electrical engineering, neurology and oceanography. Unfortunately, the high levels of noise characteristic of our planet's chaotic processes often render these frameworks ineffective. This contribution presents techniques for the reduction of noise associated with measurements of nonlinear systems. Our ultimate aim is to develop data assimilation techniques for forward models that describe chaotic observations, such as episodic tremor and slip (ETS) events in fault zones. A series of nonlinear filters are presented and evaluated using classical chaotic systems. To investigate whether the filters can successfully mitigate the effect of noise typical of Earth science, they are applied to sunspot data. The filtered data can be used successfully to forecast sunspot evolution for up to eight years (see figure).
Adaptive Non-Linear Bayesian Filter for ECG Denoising
Directory of Open Access Journals (Sweden)
Mitesh Kumar Sao
2014-06-01
Full Text Available The cycles of an electrocardiogram (ECG signal contain three components P-wave, QRS complex and the T-wave. Noise is present in cardiograph as signals being measured in which biological resources (muscle contraction, base line drift, motion noise and environmental resources (power line interference, electrode contact noise, instrumentation noise are normally pollute ECG signal detected at the electrode. Visu-Shrink thresholding and Bayesian thresholding are the two filters based technique on wavelet method which is denoising the PLI noisy ECG signal. So thresholding techniques are applied for the effectiveness of ECG interval and compared the results with the wavelet soft and hard thresholding methods. The outputs are evaluated by calculating the root mean square (RMS, signal to noise ratio (SNR, correlation coefficient (CC and power spectral density (PSD using MATLAB software. The clean ECG signal shows Bayesian thresholding technique is more powerful algorithm for denoising.
Undithering using linear filtering and non-linear diffusion techniques
Asha, V
2011-01-01
Data compression is a method of improving the efficiency of transmission and storage of images. Dithering, as a method of data compression, can be used to convert an 8-bit gray level image into a 1-bit / binary image. Undithering is the process of reconstruction of gray image from binary image obtained from dithering of gray image. In the present paper, I propose a method of undithering using linear filtering followed by anisotropic diffusion which brings the advantage of smoothing and edge enhancement. First-order statistical parameters, second-order statistical parameters, mean-squared error (MSE) between reconstructed image and the original image before dithering, and peak signal to noise ratio (PSNR) are evaluated at each step of diffusion. Results of the experiments show that the reconstructed image is not as sharp as the image before dithering but a large number of gray values are reproduced with reference to those of the original image prior to dithering.
Design of Digital IIR Filter with Conflicting Objectives Using Hybrid Gravitational Search Algorithm
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D. S. Sidhu
2015-01-01
Full Text Available In the recent years, the digital IIR filter design as a single objective optimization problem using evolutionary algorithms has gained much attention. In this paper, the digital IIR filter design is treated as a multiobjective problem by minimizing the magnitude response error, linear phase response error and optimal order simultaneously along with meeting the stability criterion. Hybrid gravitational search algorithm (HGSA has been applied to design the digital IIR filter. GSA technique is hybridized with binary successive approximation (BSA based evolutionary search method for exploring the search space locally. The relative performance of GSA and hybrid GSA has been evaluated by applying these techniques to standard mathematical test functions. The above proposed hybrid search techniques have been applied effectively to solve the multiparameter and multiobjective optimization problem of low-pass (LP, high-pass (HP, band-pass (BP, and band-stop (BS digital IIR filter design. The obtained results reveal that the proposed technique performs better than other algorithms applied by other researchers for the design of digital IIR filter with conflicting objectives.
Wang, Changyuan; Zhang, Jing; Mu, Jing
2012-01-01
A new filter named the maximum likelihood-based iterated divided difference filter (MLIDDF) is developed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation errors and nonlinearity of measurement equations. The MLIDDF algorithm is derivative-free and implemented only by calculating the functional evaluations. The MLIDDF algorithm involves the use of the iteration measurement update and the current measurement, and the iteration termination criterion based on maximum likelihood is introduced in the measurement update step, so the MLIDDF is guaranteed to produce a sequence estimate that moves up the maximum likelihood surface. In a simulation, its performance is compared against that of the unscented Kalman filter (UKF), divided difference filter (DDF), iterated unscented Kalman filter (IUKF) and iterated divided difference filter (IDDF) both using a traditional iteration strategy. Simulation results demonstrate that the accumulated mean-square root error for the MLIDDF algorithm in position is reduced by 63% compared to that of UKF and DDF algorithms, and by 7% compared to that of IUKF and IDDF algorithms. The new algorithm thus has better state estimation accuracy and a fast convergence rate.
Directory of Open Access Journals (Sweden)
Changyuan Wang
2012-06-01
Full Text Available A new filter named the maximum likelihood-based iterated divided difference filter (MLIDDF is developed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation errors and nonlinearity of measurement equations. The MLIDDF algorithm is derivative-free and implemented only by calculating the functional evaluations. The MLIDDF algorithm involves the use of the iteration measurement update and the current measurement, and the iteration termination criterion based on maximum likelihood is introduced in the measurement update step, so the MLIDDF is guaranteed to produce a sequence estimate that moves up the maximum likelihood surface. In a simulation, its performance is compared against that of the unscented Kalman filter (UKF, divided difference filter (DDF, iterated unscented Kalman filter (IUKF and iterated divided difference filter (IDDF both using a traditional iteration strategy. Simulation results demonstrate that the accumulated mean-square root error for the MLIDDF algorithm in position is reduced by 63% compared to that of UKF and DDF algorithms, and by 7% compared to that of IUKF and IDDF algorithms. The new algorithm thus has better state estimation accuracy and a fast convergence rate.
Directory of Open Access Journals (Sweden)
Šaponjić Đorđe
2009-01-01
Full Text Available By applying the well known dualism: mean count rate - mean time between successive pulses - the equivalence between an IIR digital filter and a preset count digital rate meter has been demonstrated. By using a bank of four second order IIR filters and an optimized automated algorithm for filter selection, a practical realization of a preset count rate meter giving good tradeoff between statistical fluctuations and speed of response, particularly at low count rates such as background monitoring, is presented. The presented solution is suitable for designing portable count rate meters. The designed prototype is capable of operating up to 3600 pulses per second with an accuracy of over 4% in steady-state and response times of 1 second for the rising edge and 2 seconds for the falling edge of the mean count rate step-change.
Digital Signal Processing Filtering Algorithm : Audio Equalization Using Matlab
Chaguaro Aldaz, Daniel
2015-01-01
The contemporary domain of Digital Signal Processing is in constant influx and trying to find new applications that will benefit the everyday life of ordinary people. In modern technology, most of the electronic processes use DSP algorithms in order to collect analogue information that is continually present all around us and convert it into a digital form. The need of understanding the basics of how these processes occur, has inspired to implement a DSP application for educational and testin...
Energy Technology Data Exchange (ETDEWEB)
McWilliams, T.; Widdoes, Jr., L. C.; Wood, L.
1976-09-30
The design of an extremely high performance programmable digital filter of novel architecture, the LLL Programmable Digital Filter, is described. The digital filter is a high-performance multiprocessor having general purpose applicability and high programmability; it is extremely cost effective either in a uniprocessor or a multiprocessor configuration. The architecture and instruction set of the individual processor was optimized with regard to the multiple processor configuration. The optimal structure of a parallel processing system was determined for addressing the specific Navy application centering on the advanced digital filtering of passive acoustic ASW data of the type obtained from the SOSUS net. 148 figures. (RWR)
Discrete-time filtering for nonlinear polynomial systems over linear observations
Hernandez-Gonzalez, M.; Basin, M. V.
2014-07-01
This paper designs a discrete-time filter for nonlinear polynomial systems driven by additive white Gaussian noises over linear observations. The solution is obtained by computing the time-update and measurement-update equations for the state estimate and the error covariance matrix. A closed form of this filter is obtained by expressing the conditional expectations of polynomial terms as functions of the estimate and the error covariance. As a particular case, a third-degree polynomial is considered to obtain the finite-dimensional filtering equations. Numerical simulations are performed for a third-degree polynomial system and an induction motor model. Performance of the designed filter is compared with the extended Kalman one to verify its effectiveness.
Nonlinear Inverse Problem for an Ion-Exchange Filter Model: Numerical Recovery of Parameters
Directory of Open Access Journals (Sweden)
Balgaisha Mukanova
2015-01-01
Full Text Available This paper considers the problem of identifying unknown parameters for a mathematical model of an ion-exchange filter via measurement at the outlet of the filter. The proposed mathematical model consists of a material balance equation, an equation describing the kinetics of ion-exchange for the nonequilibrium case, and an equation for the ion-exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion-exchange and several parameters. First, a numerical solution of the direct problem, the calculation of the impurities concentration at the outlet of the filter, is provided. Then, the inverse problem, finding the parameters of the ion-exchange process in nonequilibrium conditions, is formulated. A method for determining the approximate values of these parameters from the impurities concentration measured at the outlet of the filter is proposed.
A digital filtering scheme for SQUID based magnetocardiography
Institute of Scientific and Technical Information of China (English)
Zhu Xue-Min; Ren Yu-Feng; Yu Hong-Wei; Zhao Shi-Ping; Chen Geng-Hua; Zhang Li-Hua; Yang Qian-Sheng
2006-01-01
Considering the properties of slow change and quasi-periodicity of magnetocardiography (MCG) signal, we use an integrated technique of adaptive and low-pass filtering in dealing with two-channel MCG data measured by high Tc SQUIDs, The adaptive filter in the time domain is based on a noise feedback normalized least-mean-square (NLMS) algorithm, and the low-pass filter with a cutoff at 100Hz in the frequency domain characterized by Gaussian functions is combined with a notch at the power line frequency. In this way, both relevant and irrelevant noises in original MCG data are largely eliminated. The method may also be useful for other slowly varying quasi-periodical signals.
Nonlinear Kalman Filtering for acoustic emission source localization in anisotropic panels.
Dehghan Niri, E; Farhidzadeh, A; Salamone, S
2014-02-01
Nonlinear Kalman Filtering is an established field in applied probability and control systems, which plays an important role in many practical applications from target tracking to weather and climate prediction. However, its application for acoustic emission (AE) source localization has been very limited. In this paper, two well-known nonlinear Kalman Filtering algorithms are presented to estimate the location of AE sources in anisotropic panels: the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). These algorithms are applied to two cases: velocity profile known (CASE I) and velocity profile unknown (CASE II). The algorithms are compared with a more traditional nonlinear least squares method. Experimental tests are carried out on a carbon-fiber reinforced polymer (CFRP) composite panel instrumented with a sparse array of piezoelectric transducers to validate the proposed approaches. AE sources are simulated using an instrumented miniature impulse hammer. In order to evaluate the performance of the algorithms, two metrics are used: (1) accuracy of the AE source localization and (2) computational cost. Furthermore, it is shown that both EKF and UKF can provide a confidence interval of the estimated AE source location and can account for uncertainty in time of flight measurements.
Luo, Xiaodong
2014-10-01
The ensemble Kalman filter (EnKF) is an efficient algorithm for many data assimilation problems. In certain circumstances, however, divergence of the EnKF might be spotted. In previous studies, the authors proposed an observation-space-based strategy, called residual nudging, to improve the stability of the EnKF when dealing with linear observation operators. The main idea behind residual nudging is to monitor and, if necessary, adjust the distances (misfits) between the real observations and the simulated ones of the state estimates, in the hope that by doing so one may be able to obtain better estimation accuracy. In the present study, residual nudging is extended and modified in order to handle nonlinear observation operators. Such extension and modification result in an iterative filtering framework that, under suitable conditions, is able to achieve the objective of residual nudging for data assimilation problems with nonlinear observation operators. The 40-dimensional Lorenz-96 model is used to illustrate the performance of the iterative filter. Numerical results show that, while a normal EnKF may diverge with nonlinear observation operators, the proposed iterative filter remains stable and leads to reasonable estimation accuracy under various experimental settings.
Characterization of Periodically Poled Nonlinear Materials Using Digital Image Processing
2008-04-01
minimize noise. A wiener image filter is a low-pass adaptive filter that using statistics from the underlying image to estimate the noise in the image, in...t = t parameter function y = Gaussian(x,y,t) y = 1/(2.*pi.*t).*exp(-(x.^2+y.^2)/(2.*t)); Listing 2.2: GaussFilter.m % Applies Gaussian image ... filter % I = image % m = Size of filter on a side divided by 2 % t = t parameter % % Creates the specified Gaussian filter and then % applies
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.
Exploitation of Digital Filters to Advance the Single-Phase T/4 Delay PLL System
DEFF Research Database (Denmark)
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
2016-01-01
is demonstrated on a T/4 Delay Phase Locked Loop (PLL) system for a single-phase grid-connected inverter. The T/4 Delay PLL requires to cascade 50 unit delays when implemented (for a 50-Hz system with 10 kHz sampling frequency). Furthermore, digital frequency adaptive comb filters are adopted to enhance...... the performance of the T/4 Delay PLL when the grid suffers from harmonics. Experimental results have confirmed the effectiveness of the digital filters for advanced control systems....
Panourgias, Konstantinos T.; Ekaterinaris, John A.
2016-12-01
The nonlinear filter introduced by Yee et al. (1999) [27] and extensively used in the development of low dissipative well-balanced high order accurate finite-difference schemes is adapted to the finite element context of discontinuous Galerkin (DG) discretizations. The filter operator is constructed in the canonical computational domain for the standard cubical element where it is applied to the computed conservative variables in a direction per direction basis. Filtering becomes possible for all element types in unstructured meshes using collapsed coordinate transformations. The performance of the proposed nonlinear filter for DG discretizations is demonstrated and evaluated for different orders of expansions for one-dimensional and multidimensional problems with exact solutions. It is shown that for higher order discretizations discontinuity resolution within the cell is achieved and the design order of accuracy is preserved. The filter is applied for a number of standard inviscid flow test problems including strong shocks interactions to demonstrate that the proposed dissipative mechanism for DG discretizations yields superior results compared to the results obtained with the total variation bounded (TVB) limiter and high-order hierarchical limiting. The proposed approach is suitable for p-adaptivity in order to locally enhance resolution of three-dimensional flow simulations that include discontinuities and complex flow features.
Ferragina, V.; Frassone, A.; Ghittori, N.; Malcovati, P.; Vigna, A.
2005-06-01
The behavioral analysis and the design in a 0.13 μm CMOS technology of a digital interpolator filter for wireless applications are presented. The proposed block is designed to be embedded in the baseband part of a reconfigurable transmitter (WLAN 802.11a, UMTS) to operate as a sampling frequency boost between the digital signal processor (DSP) and the digital-to-analog converter (DAC). In recent trends the DAC of such transmitters usually operates at high conversion frequencies (to allow a relaxed implementation of the following analog reconstruction filter), while the DSP output flows at low frequencies (typically Nyquist rate). Thus a block able to increase the digital data rate, like the one proposed, is needed before the DAC. For example, in the WLAN case, an interpolation factor of 4 has been used, allowing the digital data frequency to raise from 20 MHz to 80 MHz. Using a time-domain model of the TX chain, a behavioral analysis has been performed to determine the impact of the filter performance on the quality of the signal at the antenna. This study has led to the evaluation of the z-domain filter transfer function, together with the specifications concerning a finite precision implementation. A VHDL description has allowed an automatic synthesis of the circuit in a 0.13 μm CMOS technology (with a supply voltage of 1.2 V). Post-synthesis simulations have confirmed the effectiveness of the proposed study.
A Modulated Hybrid Filter Bank for Wide-Band Analog-to-Digital Converters
Directory of Open Access Journals (Sweden)
Chunyan Yuan
2014-04-01
Full Text Available It is difficult to use a single analog-to-digital conversion (ADC to satisfy the requirements for conversion of an ultra-wideband signal. A parallel architecture for high bandwidth ADC, named cosine modulated hybrid filter bank, is presented to address this problem. First, the proposed architecture shifts the input signal spectrum by means of mixers. The modulated signal is channelized into smaller frequency subband signals using identical lowpass analog filters. Then the subband signals are digitized through identical narrowband ADCs, respectively. Finally, the digitized signals are up-sampled, then filtered and combined to reconstruct the digital representation of the original wide-band input signal. The digital filters are designed to use the eigenfilter method based on total least squares error criterion. Since the sample-and-hold circuits needed are only identical narrowband baseband circuits, the simplicity of the system makes the design easier and cheaper. Several design examples are used to illustrate the performance of the proposed system.
Design of Semi-Adaptive 190-200 KHz Digital Band Pass Filters for SAR Applications
Directory of Open Access Journals (Sweden)
P Yadav
2013-04-01
Full Text Available Technologies have advanced rapidly in the field of digital signal processing due to advances made in high speed, low cost digital integrated chips. These technologies have further stimulated ever increasing use of signal representation in digital form for purposes of transmission, measurement, control and storage. Design of digital filters especially adaptive or semi adaptive is the necessity of the hour for SAR applications. The aim of this research work is to design and performance evaluation of 380-400 KHz Bartlett, Blackman and Chebyshev digital semi adaptive filters. For this work XILINX and MATLAB softwares were used for the design. As pert of practical research work these designs were translated using FPGA hardware SPARTAN-3E kit. These were optimized, analyzed, compared and evaluated keeping the sampling frequency at 5 MHz for 64 order. Both these filters designed using software and hardware were tested by passing a sinusoidal test signal of 381 KHz along with noise and the filtered output signals are presented.
Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang
2016-07-21
The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.
A novel nonlinear adaptive filter using a pipelined second-order Volterra recurrent neural network.
Zhao, Haiquan; Zhang, Jiashu
2009-12-01
To enhance the performance and overcome the heavy computational complexity of recurrent neural networks (RNN), a novel nonlinear adaptive filter based on a pipelined second-order Volterra recurrent neural network (PSOVRNN) is proposed in this paper. A modified real-time recurrent learning (RTRL) algorithm of the proposed filter is derived in much more detail. The PSOVRNN comprises of a number of simple small-scale second-order Volterra recurrent neural network (SOVRNN) modules. In contrast to the standard RNN, these modules of a PSOVRNN can be performed simultaneously in a pipelined parallelism fashion, which can lead to a significant improvement in its total computational efficiency. Moreover, since each module of the PSOVRNN is a SOVRNN in which nonlinearity is introduced by the recursive second-order Volterra (RSOV) expansion, its performance can be further improved. Computer simulations have demonstrated that the PSOVRNN performs better than the pipelined recurrent neural network (PRNN) and RNN for nonlinear colored signals prediction and nonlinear channel equalization. However, the superiority of the PSOVRNN over the PRNN is at the cost of increasing computational complexity due to the introduced nonlinear expansion of each module.
A NEW SQP-FILTER METHOD FOR SOLVING NONLINEAR PROGRAMMING PROBLEMS
Institute of Scientific and Technical Information of China (English)
Duoquan Li
2006-01-01
In [4],Fletcher and Leyffer present a new method that solves nonlinear programming problems without a penalty function by SQP-Filter algorithm. It has attracted much attention due to its good numerical results. In this paper we propose a new SQP-Filter method which can overcome Maratos effect more effectively. We give stricter acceptant criteria when the iterative points are far from the optimal points and looser ones vice-versa. About this new method,the proof of global convergence is also presented under standard assumptions. Numerical results show that our method is efficient.
DEFF Research Database (Denmark)
Arlunno, Valeria; Zhang, Xu; Larsen, Knud J.
2011-01-01
We experimentally demonstrate that digital non-linear equalization allows for using independent tunable DFB lasers spaced at 12.5 GHz for ultradense WDM PM-QPSK flexible capacity channels for metro core networking.......We experimentally demonstrate that digital non-linear equalization allows for using independent tunable DFB lasers spaced at 12.5 GHz for ultradense WDM PM-QPSK flexible capacity channels for metro core networking....
Dimensional Reduction for Filters of Nonlinear Systems with Time-Scale Separation
2013-03-01
Rapp, Edwin Kreuzer and N. Sri Namachchivaya, “Reduced Nor- mal Forms for Nonlinear Control of Underactuated Hoisting Systems ,” Archive of Applied Mechanics , Vol.82, 2012, pp. 297 - 315. 7 ... Mechanics , Vol. 78(6), 2011, pp. 61001-1 - 61001-10. 8. Lee DeVille, N. Sri Namachchivaya and Zoi Rapti, “Noisy Two Dimensional Non-Hamiltonian System ...AFRL-OSR-VA-TR-2013-0009 Dimensional Reduction for Filters of Nonlinear Systems with Time- Scale Separation Namachchivaya, N
Stent enhancement using a locally adaptive unsharp masking filter in digital x-ray fluoroscopy
Jiang, Yuhao; Ekanayake, Eranda
2014-03-01
Low exposure X-ray fluoroscopy is used to guide some complicate interventional procedures. Due to the inherent high levels of noise, improving the visibility of some interventional devices such as stent will greatly benefit those interventional procedures. Stent, which is made up of tiny steel wires, is also suffered from contrast dilutions of large flat panel detector pixels. A novel adaptive unsharp masking filter has been developed to improve stent contrast in real-time applications. In unsharp masking processing, the background is estimated and subtracted from the original input image to create a foreground image containing objects of interest. A background estimator is therefore critical in the unsharp masking processing. In this specific study, orientation filter kernels are used as the background estimator. To make the process simple and fast, the kernels average along a line of pixels. A high orientation resolution of 18° is used. A nonlinear operator is then used to combine the information from the images generated from convolving the original background and noise only images with orientation filters. A computerized Monte Carlo simulation followed by ROC study is used to identify the best nonlinear operator. We then apply the unsharp masking filter to the images with stents present. It is shown that the locally adaptive unsharp making filter is an effective filter for improving stent visibility in the interventional fluoroscopy. We also apply a spatio-temporal channelized human observer model to quantitatively optimize and evaluate the filter.
The PLSI Method of Stabilizing Two-Dimensional Nonsymmetric Half-Plane Recursive Digital Filters
Gangatharan N; Reddy PS
2003-01-01
Two-dimensional (2D) recursive digital filters find applications in image processing as in medical X-ray processing. Nonsymmetric half-plane (NSHP) filters have definitely positive magnitude characteristics as opposed to quarter-plane (QP) filters. In this paper, we provide methods for stabilizing the given 2D NSHP polynomial by the planar least squares inverse (PLSI) method. We have proved in this paper that if the given 2D unstable NSHP polynomial and its PLSI are of the same degree, the P...
Huang, Guanghui; Wan, Jianping; Chen, Hui
2013-02-01
Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error.
Differential Neural Networks for Identification and Filtering in Nonlinear Dynamic Games
Directory of Open Access Journals (Sweden)
Emmanuel García
2014-01-01
Full Text Available This paper deals with the problem of identifying and filtering a class of continuous-time nonlinear dynamic games (nonlinear differential games subject to additive and undesired deterministic perturbations. Moreover, the mathematical model of this class is completely unknown with the exception of the control actions of each player, and even though the deterministic noises are known, their power (or their effect is not. Therefore, two differential neural networks are designed in order to obtain a feedback (perfect state information pattern for the mentioned class of games. In this way, the stability conditions for two state identification errors and for a filtering error are established, the upper bounds of these errors are obtained, and two new learning laws for each neural network are suggested. Finally, an illustrating example shows the applicability of this approach.
Polak, Josef; Jerabek, Jan; Langhammer, Lukas; Sotner, Roman; Dvorak, Jan; Panek, David
2016-07-01
This paper presents the simulations results in comparison with the measured results of the practical realization of the multifunctional second order frequency filter with a Digitally Adjustable Current Amplifier (DACA) and two Dual-Output Controllable Current Conveyors (CCCII +/-). This filter is designed for use in current mode. The filter was designed of the single input multiple outputs (SIMO) type, therefore it has only one input and three outputs with individual filtering functions. DACA element used in a newly proposed circuit is present in form of an integrated chip and the current conveyors are implemented using the Universal Current Conveyor (UCC) chip with designation UCC-N1B. Proposed frequency filter enables independent control of the pole frequency using parameters of two current conveyors and also independent control of the quality factor by change of a current gain of DACA.
High-Speed Superconductive Decimation Filter for Sigma-Delta Analog to Digital Converter
Wakamatsu, Tomu; Yamanashi, Yuki; Yoshikawa, Nobuyuki
2017-07-01
A superconducting decimation filter is required to convert high-speed output data from a superconducting sigma-delta analog to digital (A/D) modulator to low-speed data for data acquisition by room-temperature electronics. Because the operating frequency of the conventional superconducting decimation filter is lower than that of the maximum operation frequency of A/D modulator, the system performance of the superconducting A/D converter is limited by the decimation filter. We propose a decimation filter that can operate at the sampling frequency of the A/D modulator by hybridizing a shift-register-based and a counter-based decimation filters. The investigated decimation filter can be implemented with a practical circuit area. We designed and tested the investigated decimation filter. The simulation result indicates that the maximum operation frequency of the designed decimation filter is 39.8 GHz assuming the 2.5 kA/cm2 Nb fabrication process. We experimentally confirmed the low-speed operation of the designed decimation filter with the bias margin of 93.8%-110.8%.
3-D zebrafish embryo image filtering by nonlinear partial differential equations.
Rizzi, Barbara; Campana, Matteo; Zanella, Cecilia; Melani, Camilo; Cunderlik, Robert; Krivá, Zuzana; Bourgine, Paul; Mikula, Karol; Peyriéras, Nadine; Sarti, Alessandro
2007-01-01
We discuss application of nonlinear PDE based methods to filtering of 3-D confocal images of embryogenesis. We focus on the mean curvature driven and the regularized Perona-Malik equations, where standard as well as newly suggested edge detectors are used. After presenting the related mathematical models, the practical results are given and discussed by visual inspection and quantitatively using the mean Hausdorff distance.
Directory of Open Access Journals (Sweden)
B. Shank
2014-11-01
Full Text Available We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs connected to quasiparticle (qp traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
Recovery of systems with a linear filter and nonlinear delay feedback in periodic regimes.
Ponomarenko, V I; Prokhorov, M D
2008-12-01
We propose a set of methods for the estimation of the parameters of time-delay systems with a linear filter and nonlinear delay feedback performing periodic oscillations. The methods are based on an analysis of the system response to regular external perturbations and are valid only for systems whose dynamics can be perturbed. The efficiency of the methods is illustrated using both numerical and experimental data.
Direct heuristic dynamic programming for nonlinear tracking control with filtered tracking error.
Yang, Lei; Si, Jennie; Tsakalis, Konstantinos S; Rodriguez, Armando A
2009-12-01
This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.
Shank, B; Cabrera, B; Kreikebaum, J M; Moffatt, R; Redl, P; Young, B A; Brink, P L; Cherry, M; Tomada, A
2014-01-01
We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs) connected to quasiparticle (qp) traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search) Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
The effect of compression on tuning estimates in a simple nonlinear auditory filter model
DEFF Research Database (Denmark)
Marschall, Marton; MacDonald, Ewen; Dau, Torsten
2013-01-01
, there is evidence that human frequency-selectivity estimates depend on whether an iso-input or an iso-response measurement paradigm is used (Eustaquio-Martin et al., 2011). This study presents simulated tuning estimates using a simple compressive auditory filter model, the bandpass nonlinearity (BPNL), which......, then compression alone may explain a large part of the behaviorally observed differences in tuning between simultaneous and forward-masking conditions....
Exploitation of Digital Filters to Advance the Single-Phase T/4 Delay PLL System
DEFF Research Database (Denmark)
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
2016-01-01
will violate this design rule and it can become a major challenge for digital controllers. To deal with the above issue, this paper first exploits a virtual unit delay (z_v^-1) to emulate the viable sampling behavior in practical digital signal processors with a fixed sampling rate. This exploitation...... is demonstrated on a T/4 Delay Phase Locked Loop (PLL) system for a single-phase grid-connected inverter. The T/4 Delay PLL requires to cascade 50 unit delays when implemented (for a 50-Hz system with 10 kHz sampling frequency). Furthermore, digital frequency adaptive comb filters are adopted to enhance...
Digital Filtering Performance in the ATLAS Level-1 Calorimeter Trigger
Hadley, D R; The ATLAS collaboration
2010-01-01
The ATLAS Level-1 Calorimeter Trigger is a hardware-based system designed to identify high-pT jets, elec- tron/photon and tau candidates, and to measure total and missing ET in the ATLAS Liquid Argon and Tile calorimeters. It is a pipelined processor system, with a new set of inputs being evaluated every 25ns. The overall trigger decision has a latency budget of 2µs, including all transmission delays. The calorimeter trigger uses about 7200 reduced granularity analogue signals, which are ﬁrst digitized at the 40 MHz LHC bunch-crossing frequency, before being passed to a digital Finite Impulse Re- sponse (FIR) ﬁlter. Due to latency and chip real-estate constraints, only a simple 5-element ﬁlter with limited precision can be used. Nevertheless, this ﬁlter achieves a signiﬁcant reduction in noise, along with improving the bunch-crossing assignment and energy resolution for small signals. The context in which digital ﬁlters are used for the ATLAS Level-1 Calorimeter Trigger is presented, before descr...
Wenguang, Pan; Chengyan, Ma; Yebing, Gan; Tianchun, Ye
2010-09-01
The design of a digitally-tunable sixth-order reconfigurable OTA-C filter in a 0.18-μm RFCMOS process is proposed. The filter can be configured as a complex band pass filter or two real low pass filters. An improved digital automatic frequency tuning scheme based on the voltage controlled oscillator technique is adopted to compensate for process variations. An extended tuning range (above 8:1) is obtained by using widely continuously tunable transcon-ductors based on digital techniques. In the complex band pass mode, the bandwidth can be tuned from 3 to 24 MHz and the center frequency from 3 to 16 MHz.
Aguirre, Luis Antonio; Billings, S. A.
This paper investigates the identification of global models from chaotic data corrupted by additive noise. It is verified that noise has a strong influence on the identification of chaotic systems. In particular, there seems to be a critical noise level beyond which the accurate estimation of polynomial models from chaotic data becomes very difficult. Similarities with the estimation of the largest Lyapunov exponent from noisy data suggest that part of the problem might be related to the limited ability of predicting the data records when these are chaotic. A nonlinear filtering scheme is suggested in order to reduce the noise in the data and thereby enable the estimation of good models. This prediction-based filtering incorporates a resetting mechanism which enables the filtering of chaotic data and which is also applicable to non-chaotic data.
Gaussian Sum PHD Filtering Algorithm for Nonlinear Non-Gaussian Models
Institute of Scientific and Technical Information of China (English)
Yin Jianjun; Zhang Jianqiu; Zhuang Zesen
2008-01-01
A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density (GSPHD) filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaussiaa sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival probability, and detection probability are all Gaussian sums. The analysis also shows that the existing Gaassian mixture probability hypothesis density (GMPHD) filter, which is unsuitable for handling the non-Gaussian noise cases, is no more than a special ease of the proposed algorithm, which fills the shortage of incapability of treating non-Gaussian noise. The multi-target tracking simulation results verify the effectiveness of the proposed GSPHD.
Si(Li) x-ray spectrometer with signal processing system based on digital filtering
Energy Technology Data Exchange (ETDEWEB)
Lakatos, T. (Magyar Tudomanyos Akademia, Debrecen. Atommag Kutato Intezete)
1985-01-01
A new signal processing system is under development at ATOMKI, Debrecen, Hungary, based on digital filtering by a microprocessor. The advantages of the new method are summarized. Dead time can be decreased and the speed of signal processing can be increased. Computer simulations verified the theoretical conclusions.
A Temperature-to-Digital Converter Based on an Optimized Electrothermal Filter
Kashmiri, S.M.; Xia, S.; Makinwa, K.A.A.
2009-01-01
This paper describes the design of a CMOS temperature-to-digital converter (TDC). It operates by measuring the temperature-dependent phase shift of an electrothermal filter (ETF). Compared to previous work, this TDC employs an ETF whose layout has been optimized to minimize the thermal phase spread
Target tracking by distributed autonomous vessels using the derivative-free nonlinear Kalman filter
Rigatos, Gerasimos; Siano, Pierluigi; Raffo, Guilerme
2015-12-01
In this paper a distributed control problem for unmanned surface vessels (USVs) is formulated as follows: there are N USVs which pursue another vessel (moving target). At each time instant each USV can obtain measurements of the target's cartesian coordinates. The objective is to make the USVs converge in a synchronized manner towards the target, while avoiding collisions between them and avoiding collisions with obstacles in their motion plane. A distributed control law is developed for the USVs which enables not only convergence of the USVs to the goal position, but also makes possible to maintain the cohesion of the USVs fleet. Moreover, distributed filtering is performed, so as to obtain an estimate of the target vessel's state vector. This provides the desirable state vector to be tracked by each one of the USVs. To this end, a new distributed nonlinear filtering method of improved accuracy and computation speed is introduced. This filtering approach, under the name Derivative-free distributed nonlinear Kalman Filter is based on differential flatness theory and on an exact linearization of the target vessel's dynamic/kinematic model.
A derivative-free distributed filtering approach for sensorless control of nonlinear systems
Rigatos, Gerasimos G.
2012-09-01
This article examines the problem of sensorless control for nonlinear dynamical systems with the use of derivative-free Extended Information Filtering (EIF). The system is first subject to a linearisation transformation and next state estimation is performed by applying the standard Kalman Filter to the linearised model. At a second level, the standard Information Filter is used to fuse the state estimates obtained from local derivative-free Kalman filters running at the local information processing nodes. This approach has significant advantages because unlike the EIF (i) is not based on local linearisation of the nonlinear dynamics (ii) does not assume truncation of higher order Taylor expansion terms thus preserving the accuracy and robustness of the performed estimation and (iii) does not require the computation of Jacobian matrices. As a case study a robotic manipulator is considered and a cameras network consisting of multiple vision nodes is assumed to provide the visual information to be used in the control loop. A derivative-free implementation of the EIF is used to produce the aggregate state vector of the robot by processing local state estimates coming from the distributed vision nodes. The performance of the considered sensorless control scheme is evaluated through simulation experiments.
New cardiac MRI gating method using event-synchronous adaptive digital filter.
Park, Hodong; Park, Youngcheol; Cho, Sungpil; Jang, Bongryoel; Lee, Kyoungjoung
2009-11-01
When imaging the heart using MRI, an artefact-free electrocardiograph (ECG) signal is not only important for monitoring the patient's heart activity but also essential for cardiac gating to reduce noise in MR images induced by moving organs. The fundamental problem in conventional ECG is the distortion induced by electromagnetic interference. Here, we propose an adaptive algorithm for the suppression of MR gradient artefacts (MRGAs) in ECG leads of a cardiac MRI gating system. We have modeled MRGAs by assuming a source of strong pulses used for dephasing the MR signal. The modeled MRGAs are rectangular pulse-like signals. We used an event-synchronous adaptive digital filter whose reference signal is synchronous to the gradient peaks of MRI. The event detection processor for the event-synchronous adaptive digital filter was implemented using the phase space method-a sort of topology mapping method-and least-squares acceleration filter. For evaluating the efficiency of the proposed method, the filter was tested using simulation and actual data. The proposed method requires a simple experimental setup that does not require extra hardware connections to obtain the reference signals of adaptive digital filter. The proposed algorithm was more effective than the multichannel approach.
Partially resonant active filter using the digital PWM control circuit with the DSP
Energy Technology Data Exchange (ETDEWEB)
Matsuo, Hirofumi; Kurokawa, Fujio; Luo, Zongxin; Makino, Yutaka; Ishizuka, Yoichi [Nagasaki Univ. (Japan); Oshikata, Tetsuya [Shindengen Elect. Mfg. Co. Ltd. (Japan)
2000-07-01
The partially resonant active filter, as a pre-regulator, using the digital PWM control circuit with the DSP is proposed to improve the power factor and input current harmonic distortion factor. The steady-state and dynamic characteristics of this active filter are analysed and the relationship among the circuit parameters, variables and performance characteristics such as the pre-regulation of the output voltage, input power factor, input current harmonic distortion, boundaries of stability and so forth are defined. Using the partially resonant active filter, the high power efficiency over 91% is obtained and the high frequency switching noise is suppressed. Also, the digital control with the DSP is versatile and consequently, the power factor over 0.99 and total harmonic distortion factor less than 1% are easily realized. (orig.)
Directory of Open Access Journals (Sweden)
I.Kullayamma
2016-05-01
Full Text Available Digital watermarking is the art of hiding of information or data in documents, where the embedded information or data can be extracted to resist copyright violation or to verify the uniqueness of a document which leads to security. Protecting the digital content has become a major issue for content owners and service providers. Watermarking using gradient direction quantization is based on the uniform quantization of the direction of gradient vectors, which is called gradient direction watermarking (GDWM. In GDWM, the watermark bits are embedded by quantizing the angles of significant gradient vectors at multiple wavelet scales. The proposed scheme has the advantages of increased invisibility and robustness to amplitude scaling effects. The DWT coefficients are modified to quantize the gradient direction based on the on the derived relationship between the changes in the coefficients and the change in the gradient direction. In this paper, we propose a novel explicit image filter called guided filter. It is derived from a local linear model that computes the filtering output using the content of guidance image, which can be the input image itself or any other different image. The guided filter naturally has a fast and non approximate linear time algorithm, regardless of the kernel size and the intensity range. Finally, we show simulation results of denoising method using guided image filtering over bilateral filtering
Improved Performance by Parametrizing Wavelet Filters for Digital Image Watermarking
Directory of Open Access Journals (Sweden)
Mangaiyarkarasi Palanivel
2012-03-01
Full Text Available In recent years, watermarking has become an attractive field in areas like copyright protection, imageauthentication and biomedical engineering. Many literatures have reported about discrete wavelet transform (DWT watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks. In this paper, an attempt is made to develop a scheme based on Redundant Discrete Wavelet Transform (RDWT. The robustness and security of the proposed RDWT scheme is improved by parametrizing the scaling and wavelet filters by Pollen’s parametrizing technique. An Independent Component Analysis (ICA based detector is also applied, whichextracts watermark directly in spatial domain rather than in transform domain. The unique feature of ICA is that it does not require any transformation during extraction. The results reveal that the proposedscheme produces high peak signal to noise ratio (PSNR values and similarity measure under various image processing attacks.
Recovering the nonlinear density field from the galaxy distribution with a Poisson-Lognormal filter
Kitaura, Francisco S; Metcalf, R Benton
2009-01-01
We present a general expression for a lognormal filter given an arbitrary nonlinear galaxy bias. We derive this filter as the maximum a posteriori solution assuming a lognormal prior distribution for the matter field with a given mean field and modeling the observed galaxy distribution by a Poissonian process. We have performed a three-dimensional implementation of this filter with a very efficient Newton-Krylov inversion scheme. Furthermore, we have tested it with a dark matter N-body simulation assuming a unit galaxy bias relation and compared the results with previous density field estimators like the inverse weighting scheme and Wiener filtering. Our results show good agreement with the underlying dark matter field for overdensities even above delta~1000 which exceeds by one order of magnitude the regime in which the lognormal is expected to be valid. The reason is that for our filter the lognormal assumption enters as a prior distribution function, but the maximum a posteriori solution is also conditione...
Improved particle size estimation in digital holography via sign matched filtering.
Lu, Jiang; Shaw, Raymond A; Yang, Weidong
2012-06-04
A matched filter method is provided for obtaining improved particle size estimates from digital in-line holograms. This improvement is relative to conventional reconstruction and pixel counting methods for particle size estimation, which is greatly limited by the CCD camera pixel size. The proposed method is based on iterative application of a sign matched filter in the Fourier domain, with sign meaning the matched filter takes values of ±1 depending on the sign of the angular spectrum of the particle aperture function. Using simulated data the method is demonstrated to work for particle diameters several times the pixel size. Holograms of piezoelectrically generated water droplets taken in the laboratory show greatly improved particle size measurements. The method is robust to additive noise and can be applied to real holograms over a wide range of matched-filter particle sizes.
Liu, Yajuan; Park, Ju H; Guo, Bao-Zhu
2016-07-01
In this paper,the problem of H∞ filtering for a class of nonlinear discrete-time delay systems is investigated. The time delay is assumed to be belonging to a given interval, and the designed filter includes additive gain variations which are supposed to be random and satisfy the Bernoulli distribution. By the augmented Lyapunov functional approach, a sufficient condition is developed to ensure that the filtering error system is asymptotically mean-square stable with a prescribed H∞ performance. In addition, an improved result of H∞ filtering for linear system is also derived. The filter parameters are obtained by solving a set of linear matrix inequalities. For nonlinear systems, the applicability of the developed filtering result is confirmed by a longitudinal flight system, and an additional example for linear system is presented to demonstrate the less conservativeness of the proposed design method.
Energy Technology Data Exchange (ETDEWEB)
Harlim, John, E-mail: jharlim@psu.edu [Department of Mathematics and Department of Meteorology, the Pennsylvania State University, University Park, PA 16802, Unites States (United States); Mahdi, Adam, E-mail: amahdi@ncsu.edu [Department of Mathematics, North Carolina State University, Raleigh, NC 27695 (United States); Majda, Andrew J., E-mail: jonjon@cims.nyu.edu [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 (United States)
2014-01-15
A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partial noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.
VLSI Implementation of Fixed-Point Lattice Wave Digital Filters for Increased Sampling Rate
Directory of Open Access Journals (Sweden)
M. Agarwal
2016-12-01
Full Text Available Low complexity and high speed are the key requirements of the digital filters. These filters can be realized using allpass filters. In this paper, design and minimum multiplier implementation of a fixed point lattice wave digital filter (WDF based on three port parallel adaptor allpass structure is proposed. Here, the second-order allpass sections are implemented with three port parallel adaptor allpass structures. A design-level area optimization is done by converting constant multipliers into shifts and adds using canonical signed digit (CSD techniques. The proposed implementation reduces the latency of the critical loop by reducing the number of components (adders and multipliers. Three design examples are included to analyze the effectiveness of the proposed approach. These are implemented in verilog HDL language and mapped to a standard cell library in a 0.18 μm CMOS process. The functionality of the implementations have been verified by applying number of different input vectors. Results and simulations demonstrate that the proposed design method leads to an efficient lattice WDF in terms of maximum sampling frequency. The cost to pay is small area overhead. The postlayout simulations have been done by HSPICE with CMOS transistors.
Institute of Scientific and Technical Information of China (English)
TAO Hua-xue (陶华学); GUO Jin-yun (郭金运)
2003-01-01
Data are very important to build the digital mine. Data come from many sources, have different types and temporal states. Relations between one class of data and the other one, or between data and unknown parameters are more nonlinear. The unknown parameters are non-random or random, among which the random parameters often dynamically vary with time. Therefore it is not accurate and reliable to process the data in building the digital mine with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method to process data in building the digital mine is put forward. In the meantime, the corresponding mathematical model is also given. The generalized nonlinear least squares problem is more complex than the common nonlinear least squares problem and its solution is more difficultly obtained because the dimensions of data and parameters in the former are bigger. So a new solution model and the method are put forward to solve the generalized nonlinear dynamic least squares problem. In fact, the problem can be converted to two sub-problems, each of which has a single variable. That is to say, a complex problem can be separated and then solved. So the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations. The method lessens the calculating load and opens up a new way to process the data in building the digital mine, which have more sources, different types and more temporal states.
Miao, Zhiyong; Shi, Hongyang; Zhang, Yi; Xu, Fan
2017-10-01
In this paper, a new variational Bayesian adaptive cubature Kalman filter (VBACKF) is proposed for nonlinear state estimation. Although the conventional VBACKF performs better than cubature Kalman filtering (CKF) in solving nonlinear systems with time-varying measurement noise, its performance may degrade due to the uncertainty of the system model. To overcome this drawback, a multilayer feed-forward neural network (MFNN) is used to aid the conventional VBACKF, generalizing it to attain higher estimation accuracy and robustness. In the proposed neural-network-aided variational Bayesian adaptive cubature Kalman filter (NN-VBACKF), the MFNN is used to turn the state estimation of the VBACKF adaptively, and it is used for both state estimation and in the online training paradigm simultaneously. To evaluate the performance of the proposed method, it is compared with CKF and VBACKF via target tracking problems. The simulation results demonstrate that the estimation accuracy and robustness of the proposed method are better than those of the CKF and VBACKF.
Denoising of single-trial matrix representations using 2D nonlinear diffusion filtering.
Mustaffa, I; Trenado, C; Schwerdtfeger, K; Strauss, D J
2010-01-15
In this paper we present a novel application of denoising by means of nonlinear diffusion filters (NDFs). NDFs have been successfully applied for image processing and computer vision areas, particularly in image denoising, smoothing, segmentation, and restoration. We apply two types of NDFs for the denoising of evoked responses in single-trials in a matrix form, the nonlinear isotropic and the anisotropic diffusion filters. We show that by means of NDFs we are able to denoise the evoked potentials resulting in a better extraction of physiologically relevant morphological features over the ongoing experiment. This technique offers the advantage of translation-invariance in comparison to other well-known methods, e.g., wavelet denoising based on maximally decimated filter banks, due to an adaptive diffusion feature. We compare the proposed technique with a wavelet denoising scheme that had been introduced before for evoked responses. It is concluded that NDFs represent a promising and useful approach in the denoising of event related potentials. Novel NDF applications of single-trials of auditory brain responses (ABRs) and the transcranial magnetic stimulation (TMS) evoked electroencephalographic responses denoising are presented in this paper.
Zha, Yikun; Wei, Jingsong; Gan, Fuxi
2013-04-01
With the continuous development of the field of information technology, there has been a demand for recording mark size of optical data storage, optical imaging resolving power, and characteristic linewidth of photolithography to reach nanoscale. However, it is very difficult to realize the goal due to the optical diffraction limit restrictions. Much interest has focused on the study of optical far-field super-resolution spot by using pupil filters. However, common concerns have continued to plague super-resolving pupil filters based on either scalar diffraction theory or vector diffraction theory. These concerns include the fact that the side lobe becomes non-negligible when the central lobe is squeezed to a certain extent. Moreover, it is difficult to reduce the super-resolving spot to nanoscale. In this work, we proposed a novel method to combine the super-resolving pupil filters with nonlinear saturable absorption thin films to reduce the central spot size to nanoscale, lower the intensity ratio of side lobe to central lobe, and elongate the depth of focus or tunable tolerance distance between the super-resolving spot and sample. The simulated results indicate that by using the three-zone annular binary phase filter as the super-resolving pupil filter and Sb2Te3 as the nonlinear saturable absorption thin films, the central spot size can be reduced to nanoscale, the side lobe intensity is squeezed to about 10% of the central lobe intensity, and the tunable tolerance distance between the super-resolving spot and the sample is about two times that of the depth of focus of the diffraction limited spot at the incident laser wavelength of 405 nm and the numerical aperture of focusing lens of 0.95. The combination of the super-resolving pupil filters with the nonlinear saturable absorption thin films is very useful for nano-optical data storage, maskless nanolithography, and nano-optical imaging. It is also easy to use in actual applications because of the operation
Performance of digital radiography with enhancement filters for the diagnosis of proximal caries
Directory of Open Access Journals (Sweden)
Manuella Dias Furtado Belém
2013-06-01
Full Text Available Enhancement filters are potentially supposed to improve the diagnostic performance of digital images. Thus, the aim of this study was to compare the performance of digital radiography with and without enhancement filters for the detection of induced proximal caries lesions. The total sample consisted of 120 sound human teeth (40 premolars, 80 molars. Enamel subsurface demineralization was induced in one of the proximal surfaces of 60 teeth. Standardized radiographs of all teeth were acquired after the demineralization phase using the Digora-Optime® system. Four radiologists examined the digital radiographs and applied the following filters provided by the Digora® for Windows 2.6 package: Negative, Sharpen and both (Negative plus Sharpen. Validation of radiographic diagnosis was carried out by Knoop cross-sectional micro-hardness profiling on the proximal surfaces. Intraobserver agreement was estimated using Kappa statistics (k. Sensitivity, specificity and over-all accuracy were compared using ANOVA/Tukey test (α = 5%. Intraobserver agreement ranged from good to very good/optimal (k: 0.65–0.83. Although not statistically significant, the highest sensitivity (0.68 ± 0.22 and accuracy (0.76 ± 0.16 values were observed using the Sharpen filter as opposed to the Negative filter, which presented the lowest performance indices (0.57 ± 0.13 and 0.70 ± 0.10, respectively. Specificity ranged from 0.84 to 0.85, considering all imaging modalities (p > 0.05. Insofar as the Sharpen filter had the highest performance indices, it may be considered a useful adjunct for detecting subtle proximal caries lesions.
Fir Filter Design Using The Signed-Digit Number System and Carry Save Adders – A Comparison
Directory of Open Access Journals (Sweden)
Hesham Altwaijry
2013-01-01
Full Text Available This work looks at optimizing finite impulse response (FIR filters from an arithmetic perspective. Since the main two arithmetic operations in the convolution equations are addition and multiplication, they are the targets of the optimization. Therefore, considering carry-propagate-free addition techniques should enhance the addition operation of the filter. The signed-digit number system is utilized to speedup addition in the filter. An alternative carry propagate free fast adder, carry-save adder, is also used here to compare its performance to the signed-digit adder. For multiplication, Booth encoding is used to reduce the number of partial products. The two filters are modeled in VHDL, synthesized and place-and-routed. The filters are deployed on a development board to filter digital images. The resultant hardware is analyzed for speed and logic utilization
Noise impact of single-event upsets on an FPGA-based digital filter
Energy Technology Data Exchange (ETDEWEB)
Morgan, Keith S [Los Alamos National Laboratory; Caffrey, Michael P [Los Alamos National Laboratory; Graham, Paul S [Los Alamos National Laboratory; Pratt, Brian H [Los Alamos National Laboratory; Wirthlin, Michael J [BYU
2009-01-01
Field-programmable gate arrays are well-suited to DSP and digital communications applications. SRAM-based FPGAs, however, are susceptible to radiation-induced single-event upsets (SEUs) when deployed in space environments. These effects are often handled with the area and power-intensive TMR mitigation technique. This paper evaluates the effects of SEUs in the FPGA configuration memory as noise in a digital filter, showing that many SEUs in a digital communications system cause effects that could be considered noise rather than circuit failure. Since DSP and digital communications applications are designed to withstand certain types of noise, SEU mitigation techniques that are less costly than TMR may be applicable. This could result in large savings in area and power when implementing a reliable system. Our experiments show that, of the SEUs that affected the digital filter with a 20 dB SNR input signal, less than 14% caused an SNR loss of more than 1 dB at the output.
Identification of parameters in nonlinear geotechnical models using extenden Kalman filter
Directory of Open Access Journals (Sweden)
Nestorović Tamara
2014-01-01
Full Text Available Direct measurement of relevant system parameters often represents a problem due to different limitations. In geomechanics, measurement of geotechnical material constants which constitute a material model is usually a very diffcult task even with modern test equipment. Back-analysis has proved to be a more effcient and more economic method for identifying material constants because it needs measurement data such as settlements, pore pressures, etc., which are directly measurable, as inputs. Among many model parameter identification methods, the Kalman filter method has been applied very effectively in recent years. In this paper, the extended Kalman filter – local iteration procedure incorporated with finite element analysis (FEA software has been implemented. In order to prove the effciency of the method, parameter identification has been performed for a nonlinear geotechnical model.
State estimation of nonlinear stochastic systems using a novel meta-heuristic particle filter
DEFF Research Database (Denmark)
Ahmadi, Mohamadreza; Mojallali, Hamed; Izadi-Zamanabadi, Roozbeh
2012-01-01
This paper proposes a new version of the particle filtering (PF) algorithm based on the invasive weed optimization (IWO) method. The sub-optimality of the sampling step in the PF algorithm is prone to estimation errors. In order to avert such approximation errors, this paper suggests applying...... the IWO algorithm by translating the sampling step into a nonlinear optimization problem. By introducing an appropriate fitness function, the optimization problem is properly treated. The validity of the proposed method is evaluated against three distinct examples: the stochastic volatility estimation...... problem in finance, the severely nonlinear waste water sludge treatment plant, and the benchmark target tracking on re-entry problem. By simulation analysis and evaluation, it is verified that applying the suggested IWO enhanced PF algorithm (PFIWO) would contribute to significant estimation performance...
Design of robust fault detection filter for nonlinear time-delay systems
Institute of Scientific and Technical Information of China (English)
BAI Lei-shi; HE Li-ming; TIAN Zuo-hua; SHI Song-jiao
2006-01-01
In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. First, a reference residual model is introduced to formulate the RFDF design problem as an H∞model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the RFDF for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.
Institute of Scientific and Technical Information of China (English)
Juming CHEN; Feng LIU; Shengwei MEI
2006-01-01
Active power filter (APF) based on voltage source inverter (VSI) is one of the important measures for handling the power quality problem. Mathematically, the APF model in a power grid is a typical nonlinear one. The idea of passivity is a powerful tool to study the stabilization of such a nonlinear system. In this paper, a state-space model of the four-leg APF is derived, based on which a new H-infinity controller for current tracking is proposed from the passivity point of view. It can achieve not only asymptotic tracking, but also disturbance attenuation in the sense of L2-gain. Subsequently,a sufficient condition to guarantee the boundedness and desired mean of the DC voltage is also given. This straightforward condition is consistent with the power-balancing law of electrical circuits. Simulations performed on PSCAD platform verify the validity of the new approach.
Non-linear DSGE Models and The Central Difference Kalman Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
solved up to third order. A Monte Carlo study shows that this QML estimator is basically unbiased and normally distributed infi…nite samples for DSGE models solved using a second order or a third order approximation. These results hold even when structural shocks are Gaussian, Laplace distributed......This paper introduces a Quasi Maximum Likelihood (QML) approach based on the Cen- tral Difference Kalman Filter (CDKF) to estimate non-linear DSGE models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models...
Cubic generalized B-splines for interpolation and nonlinear filtering of images
Tshughuryan, Heghine
1997-04-01
This paper presents the introduction and using of the generalized or parametric B-splines, namely the cubic generalized B-splines, in various signal processing applications. The theory of generalized B-splines is briefly reviewed and also some important properties of generalized B-splines are investigated. In this paper it is shown the use of generalized B-splines as a tool to solve the quasioptimal algorithm problem for nonlinear filtering. Finally, the experimental results are presented for oscillatory and other signals and images.
Spatio-Temporal Nonlinear Filtering With Applications to Information Assurance and Counter Terrorism
2011-11-14
International Conference on Infor- mation Fusion, Hyatt Regency Hotel , Cologne, Germany, 2008, pp. 878-885 (Invited). 7. A.G. Tartakovsky, M. Pollak, and...probability kernel Qt (x, y) and v̇t is white noise. For example, if the state process is given by the noisy kinematic equation ẋt = a (t, xt) + σε̇t, where...targets with evolving appearance in noisy and cluttered environments. Our method is based on combination of nonlinear filtering for interacting
Fuzzy predictive filtering in nonlinear economic model predictive control for demand response
DEFF Research Database (Denmark)
Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.;
2016-01-01
The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...... problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...
Sun, Xiaodian; Jin, Li; Xiong, Momiao
2008-01-01
It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.
Set-membership fuzzy filtering for nonlinear discrete-time systems.
Yang, Fuwen; Li, Yongmin
2010-02-01
This paper is concerned with the set-membership filtering (SMF) problem for discrete-time nonlinear systems. We employ the Takagi-Sugeno (T-S) fuzzy model to approximate the nonlinear systems over the true value of state and to overcome the difficulty with the linearization over a state estimate set rather than a state estimate point in the set-membership framework. Based on the T-S fuzzy model, we develop a new nonlinear SMF estimation method by using the fuzzy modeling approach and the S-procedure technique to determine a state estimation ellipsoid that is a set of states compatible with the measurements, the unknown-but-bounded process and measurement noises, and the modeling approximation errors. A recursive algorithm is derived for computing the ellipsoid that guarantees to contain the true state. A smallest possible estimate set is recursively computed by solving the semidefinite programming problem. An illustrative example shows the effectiveness of the proposed method for a class of discrete-time nonlinear systems via fuzzy switch.
Possibilities for transverse feedback phase adjustment by means of digital filters
Kotzian, G.
2017-07-01
In transverse feedback systems a phase adjustment is generally required to convert a beam position signal from a pick-up into a momentum correction signal used by a transverse kicker. In this paper we outline several possibilities for phase adjustments using only single pickups or the vector combination of two pick-ups. Analytical expressions are given as a function of the fractional tune and the betatron phase advance between the pick-up location and the kicker. The shortest possible digital filter is formulated, including a notch for closed orbit suppression and a free parameter to adjust for betatron phase. We introduce a novel, fully parametrized digital filter with the feature to be insensitive to variations in fractional tune. Examples are given for the SPS transverse feedback system and compared with measurements.
DEFF Research Database (Denmark)
Porto da Silva, Edson
Digital signal processing (DSP) has become one of the main enabling technologies for the physical layer of coherent optical communication networks. The DSP subsystems are used to implement several functionalities in the digital domain, from synchronization to channel equalization. Flexibility...... nonlinearity compensation, (II) spectral shaping, and (III) adaptive equalization. For (I), original contributions are presented to the study of the nonlinearity compensation (NLC) with digital backpropagation (DBP). Numerical and experimental performance investigations are shown for different application...... scenarios. Concerning (II), it is demonstrated how optical and electrical (digital) pulse shaping can be allied to improve the spectral confinement of a particular class of optical time-division multiplexing (OTDM) signals that can be used as a building block for fast signaling single-carrier transceivers...
PROCESSING ECG SIGNAL WITH KAISER WINDOW- BASED FIR DIGITAL FILTERS BY
Directory of Open Access Journals (Sweden)
Mbachu C.B
2011-08-01
Full Text Available Heart attacks mostly occur in people who suffer from heart or heart-relate diseases if these diseases are not detected early enough and treated. There is therefore the need for a reliable means of detecting these diseases to save the patients from these attacks which are increasing in proportion all over the world. Electrocardiography (ECG, which is the electrical activity of the heart, generates a signal referred to as ECG signal or simply ECG and the shape of this signal tells much about the condition of the heart of a patient. Naturally the ECG signal gets distorted by different artifacts which must be removed otherwise it will convey an incorrect information regarding the patients heart condition. The work in this paper is the design of FIR digital filters with Kaiser Window to remove the interferences or the artifacts. Three filters are considered: low pass, high pass and notch filters. Each filter is used to filter the raw noisy ECG signal after which the three filters are used in cascade. Results are observed and recorded in each case, using FDA tool.
AN ADAPTIVELY TRAINED KERNEL-BASED NONLINEAR REPRESENTOR FOR HANDWRITTEN DIGIT CLASSIFICATION
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In practice, retraining a trained classifier is necessary when novel data become available. This paper adopts an incremental learning procedure to adaptively train a Kernel-based Nonlinear Representor(KNR), a recently presented nonlinear classifier for optimal pattern representation, so that its generalization ability may be evaluated in time-variant situation and a sparser representation is obtained for computationally intensive tasks. The addressed techniques are applied to handwritten digit classification to illustrate the feasibility for pattern recognition.
2015-01-01
The present article relates in general to digital demodulation of Binary Frequency Shift Keying (BFSK). The objective of the present research is to obtain a new processing method for demodulating BFSK-signals in order to reduce hardware complexity in comparison with other methods reported. The solution proposed here makes use of the matched filter theory and curve segmentation algorithms. This paper describes the integration and configuration of a Sampler Correlator and curve segmentation blo...
The use of variable-step delta modulation in digital filtering and correlation analysis
Pogribnoi, V. A.
1985-11-01
General expressions are obtained for convolutions and correlation functions using variable-quantization-step DM in conjunction with PCM, making it possible to realize low-cost processor circuits. Algorithms for the operation of processors for digital filtering and correlation analysis on the basis of this type of modulation are proposed. In addition, they are compared with algorithms for the operation of processors with linear PCM, DM, and delta-sigma modulation.
1981-07-01
1p^^i-J\\\\^3^\\\\^. TECHNICAL LIBRARY AD^y^.q ijg. TECHNICAL REPORT ARBRL-TR-02346 COMPUTER ALGORITHMS FOR THE DESIGN AND IMPLEMENTATION OF LINEAR...INSTRUCTIONS BEFORE COMPLETI?>G FORM 1. REPORT NUMBER TECHNICAL REPORT ARBRL-TR-n2.^46 i. GOVT ACCESSION NO. *. TITLE fand Sijfam;»; COMPUTER ... ALGORITHMS FOR THE DESIGN AND IMPLEMENTATION OF LINEAR PHASE FINPTE IMPULSE RESPONSE DIGITAL FILTERS 7. AUTHORf*; James N. Walbert 9
Rigatos, Gerasimos G
2016-06-01
It is proven that the model of the p53-mdm2 protein synthesis loop is a differentially flat one and using a diffeomorphism (change of state variables) that is proposed by differential flatness theory it is shown that the protein synthesis model can be transformed into the canonical (Brunovsky) form. This enables the design of a feedback control law that maintains the concentration of the p53 protein at the desirable levels. To estimate the non-measurable elements of the state vector describing the p53-mdm2 system dynamics, the derivative-free non-linear Kalman filter is used. Moreover, to compensate for modelling uncertainties and external disturbances that affect the p53-mdm2 system, the derivative-free non-linear Kalman filter is re-designed as a disturbance observer. The derivative-free non-linear Kalman filter consists of the Kalman filter recursion applied on the linearised equivalent of the protein synthesis model together with an inverse transformation based on differential flatness theory that enables to retrieve estimates for the state variables of the initial non-linear model. The proposed non-linear feedback control and perturbations compensation method for the p53-mdm2 system can result in more efficient chemotherapy schemes where the infusion of medication will be better administered.
The PLSI Method of Stabilizing Two-Dimensional Nonsymmetric Half-Plane Recursive Digital Filters
Directory of Open Access Journals (Sweden)
Gangatharan N
2003-01-01
Full Text Available Two-dimensional (2D recursive digital filters find applications in image processing as in medical X-ray processing. Nonsymmetric half-plane (NSHP filters have definitely positive magnitude characteristics as opposed to quarter-plane (QP filters. In this paper, we provide methods for stabilizing the given 2D NSHP polynomial by the planar least squares inverse (PLSI method. We have proved in this paper that if the given 2D unstable NSHP polynomial and its PLSI are of the same degree, the PLSI polynomial is always stable, irrespective of whether the coefficients of the given polynomial have relationship among its coefficients or not. Examples are given for 2D first-order and second-order cases to prove our results. The generalization is done for the th order polynomial.
Two dimensional recursive digital filters for near real time image processing
Olson, D.; Sherrod, E.
1980-01-01
A program was designed toward the demonstration of the feasibility of using two dimensional recursive digital filters for subjective image processing applications that require rapid turn around. The concept of the use of a dedicated minicomputer for the processor for this application was demonstrated. The minicomputer used was the HP1000 series E with a RTE 2 disc operating system and 32K words of memory. A Grinnel 256 x 512 x 8 bit display system was used to display the images. Sample images were provided by NASA Goddard on a 800 BPI, 9 track tape. Four 512 x 512 images representing 4 spectral regions of the same scene were provided. These images were filtered with enhancement filters developed during this effort.
Directory of Open Access Journals (Sweden)
Wilton Mitsunari Takeshita
2013-01-01
Full Text Available Background: To compare the diagnostic accuracy of three different imaging systems: Direct digital radiography system (DDR-CMOS, four types of filtered images, and a priori and a posteriori registration of digital subtraction radiography (DSR in the diagnosis of proximal defects. Materials and Methods: The teeth were arranged in pairs in 10 blocks of vinyl polysiloxane, and proximal defects were performed with drills of 0.25, 0.5, and 1 mm diameter. Kodak RVG 6100 sensor was used to capture the images. A posteriori DSR registrations were done with Regeemy 0.2.43 and subtraction with Image Tool 3.0. Filtered images were obtained with Kodak Dental Imaging 6.1 software. Images (n = 360 were evaluated by three raters, all experts in dental radiology. Results: Sensitivity and specificity of the area under the receiver operator characteristic (ROC curve (Az were higher for DSR images with all three drills (Az = 0.896, 0.979, and 1.000 for drills 0.25, 0.5, and 1 mm, respectively. The highest values were found for 1-mm drills and the lowest for 0.25-mm drills, with negative filter having the lowest values of all (Az = 0.631. Conclusion: The best method of diagnosis was by using a DSR. The negative filter obtained the worst results. Larger drills showed the highest sensitivity and specificity values of the area under the ROC curve.
Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques
Deasy, Joseph O.
2000-07-01
The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to-voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions.
Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques
Energy Technology Data Exchange (ETDEWEB)
Deasy, Joseph O. [Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 So. Kingshighway Blvd, St Louis, MO 63110 (United States). E-mail: deasy at radonc.wustl.edu
2000-07-01
The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to-voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions. (author)
Lei, Shaw-Min; Yao, Kung
1990-01-01
A class of infinite impulse response (IIR) digital filters with a systolizable structure is proposed and its synthesis is investigated. The systolizable structure consists of pipelineable regular modules with local connections and is suitable for VLSI implementation. It is capable of achieving high performance as well as high throughput. This class of filter structure provides certain degrees of freedom that can be used to obtain some desirable properties for the filter. Techniques of evaluating the internal signal powers and the output roundoff noise of the proposed filter structure are developed. Based upon these techniques, a well-scaled IIR digital filter with minimum output roundoff noise is designed using a local optimization approach. The internal signals of all the modes of this filter are scaled to unity in the l2-norm sense. Compared to the Rao-Kailath (1984) orthogonal digital filter and the Gray-Markel (1973) normalized-lattice digital filter, this filter has better scaling properties and lower output roundoff noise.
High-speed decimation filter for a delta-sigma analog-to-digital converter
Xie, Yiqun
1998-10-01
A decimation filter is a key component in a delta-sigma analog-to-digital converter system. The importance of the design of the decimation filter for the delta-sigma converter is due to several factors. The first, high resolution, which is the major advantage of the delta-sigma converter, can only be possible if the decimation filter can remove the high-frequency noise generated by the quantizer, without introducing significant distortion of the signals. The second is that a decimation filter occupies the dominant portion of the area and consumes the dominant portion of power in a delta-sigma converter; therefore, a well designed decimation filter can significantly save power and area for the converter and reduce production cost. The third is that the first-stage decimation filter has to operate in a very high frequency, equal to the sampling frequency of the delta-sigma converter. The circuit complexity and high-speed operation pose challenges to the design of a decimation filter. A superconductive decimation filter has the advantage of allowing sampling the analog signal at an ultra-high frequency in the modulator. This dissertation presents a superconductive decimation filter designed with voltage-state logic, which has the advantage of robustness, being relatively insensitive to clock timing, and easier to interface with semiconductor circuitry than other prevailing superconductive logic families. A structure of a multi-channel-input filter is developed to improve the speed performance. The filter is aimed to work at 16 Gbit/s or higher with state-of-the-art niobium technology. Extensive simulation is performed to optimize the circuit design. Circuit yield is predicted by Monte Carlo simulation using the knowledge of existing process variations. To improve yield, the circuit is simplified by using an accumulate-and-dump structure. A novel XOR gate is invented and used in the circuit to reduce gate count even further. A single-rail operation of signals, rather
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
Online digital filter and QRS detector applicable in low resource ECG monitoring systems.
Tabakov, Serafim; Iliev, Ivo; Krasteva, Vessela
2008-11-01
The present work describes fast computation methods for real-time digital filtration and QRS detection, both applicable in autonomous personal ECG systems for long-term monitoring. Since such devices work under considerable artifacts of intensive body and electrode movements, the input filtering should provide high-quality ECG signals supporting the accurate ECG interpretation. In this respect, we propose a combined high-pass and power-line interference rejection filter, introducing the simple principle of averaging of samples with a predefined distance between them. In our implementation (sampling frequency of 250 Hz), we applied averaging over 17 samples distanced by 10 samples (Filter10x17), thus realizing a comb filter with a zero at 50 Hz and high-pass cut-off at 1.1 Hz. Filter10x17 affords very fast filtering procedure at the price of minimal computing resources. Another benefit concerns the small ECG distortions introduced by the filter, providing its powerful application in the preprocessing module of diagnostic systems analyzing the ECG morphology. Filter10x17 does not attenuate the QRS amplitude, or introduce significant ST-segment elevation/depression. The filter output produces a constant error, leading to uniform shifting of the entire P-QRS-T segment toward about 5% of the R-peak amplitude. Tests with standardized ECG signals proved that Filter10x17 is capable to remove very strong baseline wanderings, and to fully suppress 50 Hz interferences. By changing the number of the averaged samples and the distance between them, a filter design with different cut-off and zero frequency could be easily achieved. The real-time QRS detector is designed with simplified computations over single channel, low-resolution ECGs. It relies on simple evaluations of amplitudes and slopes, including history of their mean values estimated over the preceding beats, smart adjustable thresholds, as well as linear logical rules for identification of the R-peaks in real
Rigatos, G; Rigatou, E; Djida, J D
2015-01-01
The derivative-free nonlinear Kalman filter is proposed for state estimation and fault diagnosis in distributed parameter systems of the wave-type and particularly in the Peyrard-Bishop-Dauxois model of DNA dynamics. At a first stage, a nonlinear filtering approach is introduced for estimating the dynamics of the Peyrard-Bishop-Dauxois 1D nonlinear wave equation, through the processing of a small number of measurements. It is shown that the numerical solution of the associated partial differential equation results in a set of nonlinear ordinary differential equations. With the application of a diffeomorphism that is based on differential flatness theory it is shown that an equivalent description of the system is obtained in the linear canonical (Brunovsky) form. This transformation enables to obtain local estimates about the state vector of the DNA model through the application us of the standard Kalman filter recursion. At a second stage, the local statistical approach to fault diagnosis is used to perform fault diagnosis for this distributed parameter system by processing with statistical tools the differences (residuals) between the output of the Kalman filter and the measurements obtained from the distributed parameter system. Optimal selection of the fault threshold is succeeded by using the local statistical approach to fault diagnosis. The efficiency of the proposed filtering approach in the problem of fault diagnosis for parametric change detection, in nonlinear wave-type models of DNA dynamics, is confirmed through simulation experiments.
Optimization and realization of IIR digital filter based on immune algorithms%基于免疫算法的IIR数字滤波器优化与实现
Institute of Scientific and Technical Information of China (English)
倪龙
2011-01-01
由于IIR数字滤波器设计实质上是一个非线性高维复杂函数优化问题,文中提出基于具有全局搜索能力强,收敛速度快特点的免疫算法实现IIR数字滤波器优化设计的新方法,给出了IIR滤波器优化设计的数学模型,描述了应用免疫算法优化设计IIR数字滤波器的具体实现步骤.通过低通和高通IIR数字滤波器设计的仿真结果表明方法的有效性和高效性.%Based on optimization design for IIR digital filters being a non-linear and high-dimension complex function optimization problem, immune algorithms (IA) , which has the characteristics of more powerful global and rpider convergence is applied on IIR digital filter optimization design in this paper.Firstly, the maths model of IIR digital filter optimization design is proposed. Secondly, the process of optimization design for IIR digital filters on the basis ofIA is described in detail, finally, the validity and effectivenss of the introduced method are demonstrated by experimental results on the lowpass and highpass IIR digital filters.
Nalegaev, Sergey S.; Belashov, Andrey V.; Petrov, Nikolay V.
2017-07-01
The methodology of Photothermal Interferometry implemented through off-axis digital holography for the nonlinear refractive index measurements of optical media with the thermal mechanism of nonlinearity is presented. An experimental appraisal is done on the example of chlorophyllin 1% solution in ethyl alcohol. It allows us to estimate the effective value of nonlinear refractive index as - 0.65 ·10-3 cm2/W. The comparison of the experimental result with data obtained by means of a reference approach was performed. Possible errors lead to a mismatch between them are highlighted and analyzed.
Improving the phase measurement by the apodization filter in the digital holography
Chang, Shifeng; Wang, Dayong; Wang, Yunxin; Zhao, Jie; Rong, Lu
2012-11-01
Due to the finite size of the hologram aperture in digital holography, high frequency intensity and phase fluctuations along the edges of the images, which reduce the precision of phase measurement. In this paper, the apodization filters are applied to improve the phase measurement in the digital holography. Firstly, the experimental setup of the lensless Fourier transform digital holography is built, where the sample is a standard phase grating with the grating constant of 300μm and the depth of 150nm. Then, apodization filters are applied to phase measurement of the sample with three kinds of the window functions: Tukey window, Hanning window and Blackman window, respectively. Finally, the results were compared to the detection data given by the commercial white-light interferometer. It is shown that aperture diffraction effects can be reduced by the digital apodization, and the phase measurement with the apodization is more accurate than in the unapodized case. Meanwhile, the Blackman window function produces better effect than the other two window functions in the measurement of the standard phase grating.
Design of minimum multiplier fractional order differentiator based on lattice wave digital filter.
Barsainya, Richa; Rawat, Tarun Kumar; Kumar, Manjeet
2017-01-01
In this paper, a novel design of fractional order differentiator (FOD) based on lattice wave digital filter (LWDF) is proposed which requires minimum number of multiplier for its structural realization. Firstly, the FOD design problem is formulated as an optimization problem using the transfer function of lattice wave digital filter. Then, three optimization algorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO) and cuckoo search algorithm (CSA) are applied to determine the optimal LWDF coefficients. The realization of FOD using LWD structure increases the design accuracy, as only N number of coefficients are to be optimized for Nth order FOD. Finally, two design examples of 3rd and 5th order lattice wave digital fractional order differentiator (LWDFOD) are demonstrated to justify the design accuracy. The performance analysis of the proposed design is carried out based on magnitude response, absolute magnitude error (dB), root mean square (RMS) magnitude error, arithmetic complexity, convergence profile and computation time. Simulation results are attained to show the comparison of the proposed LWDFOD with the published works and it is observed that an improvement of 29% is obtained in the proposed design. The proposed LWDFOD approximates the ideal FOD and surpasses the existing ones reasonably well in mid and high frequency range, thereby making the proposed LWDFOD a promising technique for the design of digital FODs. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Effective number of samples and pseudo-random nonlinear distortions in digital OFDM coded signal
Rudziński, Adam
2013-01-01
This paper concerns theoretical modeling of degradation of signal with OFDM coding caused by pseudo-random nonlinear distortions introduced by an analog-to-digital or digital-to-analog converter. A new quantity, effective number of samples, is defined and used for derivation of accurate expressions for autocorrelation function and the total power of the distortions. The derivation is based on probabilistic model of the signal and its transition probability. It is shown, that for digital (discrete and quantized) signals the effective number of samples replaces the total number of samples and is the proper quantity defining their properties.
Two-dimensional nonlinear geophysical data filtering using the multidimensional EEMD method
Chen, Chih-Sung; Jeng, Yih
2014-12-01
A variety of two-dimensional (2D) empirical mode decomposition (EMD) methods have been proposed in the last decade. Furthermore, the multidimensional EMD algorithm and its parallel class, multivariate EMD (MEMD), are available in recent years. From those achievements, it is possible to design an efficient 2D nonlinear filter for geophysical data processing. We introduce a robust 2D nonlinear filter which can be applied to enhance the signal of 2D geophysical data or to highlight the feature component on an image. We did this by replacing the conventionally used smooth interpolation in the ensemble empirical mode decomposition (EEMD) algorithm with a piecewise interpolation method. The one-dimensional (1D) EEMD procedures were consecutively performed in all directions, and then the comparable minimal scale combination technique was applied to the decomposed components. The theoretical derivation, model simulation, and real data applications are demonstrated in this paper. The proposed filtering method is effective in improving the image resolution by suppressing the random noise added in the simulation example and strong low frequency track corrugation noise bands with background noise in the field example. Furthermore, the algorithm can be easily extended to higher dimensions by repeating the same procedure in the succeeding dimension. To evaluate the proposed method, one data set is processed separately by using the enhanced analytic signal method and the multivariate EMD (MEMD) algorithm, and the results from these two methods are compared with that of the proposed method. A general equation for generating three-dimensional (3D) EEMD components based on the comparable minimal scale combination principle is derived for further applications.
Nonlinear filtering for autonomous navigation of spacecraft in highly elliptical orbit
Vigneron, Adam C.; de Ruiter, Anton H. J.; Burlton, Bruce V.; Soh, Warren K. H.
2016-05-01
In support of Canada's proposed Polar Communication and Weather mission, this study examined the accuracy to which GPS-based autonomous navigation might be realized for spacecraft in a Molniya orbit. A navigation algorithm based on the Extended Kalman Filter was demonstrated to achieve a three-dimensional root-mean-square accuracy of 58.9 m over a Molniya orbit with 500 km and 40,000 km perigee and apogee altitudes, respectively. Despite the inclusion of biased and non-white error models in the generated GPS pseudorange measurements - a first for navigation studies in this orbital regime - algorithms based on the Unscented Kalman Filter and the Cubature Kalman Filter were not found to improve this result; their benefits were eclipsed due to the accurate pseudorange measurements which were available during periods of highly nonlinear dynamics. This study revealed receiver clock bias error to be a significant source of navigation solution error. For reasons of geometry, the navigation algorithm is not able to differentiate between this error and a radial position error. A novel dual-mode dynamic clock model was proposed and implemented as a means to minimize receiver clock bias error over the entire orbital regime.
Detection of broken rotor bars in induction motors using nonlinear Kalman filters.
Karami, Farzaneh; Poshtan, Javad; Poshtan, Majid
2010-04-01
This paper presents a model-based fault detection approach for induction motors. A new filtering technique using Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) is utilized as a state estimation tool for on-line detection of broken bars in induction motors based on rotor parameter value estimation from stator current and voltage processing. The hypothesis on which the detection is based is that the failure events are detected by jumps in the estimated parameter values of the model. Both UKF and EKF are used to estimate the value of rotor resistance. Upon breaking a bar the estimated rotor resistance is increased instantly, thus providing two values of resistance after and before bar breakage. In order to compare the estimation performance of the EKF and UKF, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions. Computer simulations are carried out for a squirrel cage induction motor. The results show the superiority of UKF over EKF in nonlinear system (such as induction motors) as it provides better estimates for rotor fault detection.
Penalized Ensemble Kalman Filters for High Dimensional Non-linear Systems
Hou, Elizabeth; Hero, Alfred O
2016-01-01
The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a non-linear system. It does so by using an empirical approximation to the well-known Kalman filter. Unfortunately, its performance suffers when the ensemble size is smaller than the state space, as is often the case for computationally burdensome models. This scenario means that the empirical estimate of the state covariance is not full rank and possibly quite noisy. To solve this problem in this high dimensional regime, a computationally fast and easy to implement algorithm called the penalized ensemble Kalman filter (PEnKF) is proposed. Under certain conditions, it can be proved that the PEnKF does not require more ensemble members than state dimensions in order to have good performance. Further, the proposed approach does not require special knowledge of the system such as is used by localization methods. These theoretical results are supported with superior...
Wallace, G. R.; Weathers, G. D.; Graf, E. R.
1973-01-01
The statistics of filtered pseudorandom digital sequences called hybrid-sum sequences, formed from the modulo-two sum of several maximum-length sequences, are analyzed. The results indicate that a relation exists between the statistics of the filtered sequence and the characteristic polynomials of the component maximum length sequences. An analysis procedure is developed for identifying a large group of sequences with good statistical properties for applications requiring the generation of analog pseudorandom noise. By use of the analysis approach, the filtering process is approximated by the convolution of the sequence with a sum of unit step functions. A parameter reflecting the overall statistical properties of filtered pseudorandom sequences is derived. This parameter is called the statistical quality factor. A computer algorithm to calculate the statistical quality factor for the filtered sequences is presented, and the results for two examples of sequence combinations are included. The analysis reveals that the statistics of the signals generated with the hybrid-sum generator are potentially superior to the statistics of signals generated with maximum-length generators. Furthermore, fewer calculations are required to evaluate the statistics of a large group of hybrid-sum generators than are required to evaluate the statistics of the same size group of approximately equivalent maximum-length sequences.
Automatic computerized analysis of heart rate variability with digital filtering of ectopic beats.
Storck, N; Ericson, M; Lindblad, L; Jensen-Urstad, M
2001-01-01
Analysis of heart rate variability (HRV) has been used in studies of autonomic function and risk assessment in different patient groups such as in patients with diabetes mellitus, after myocardial infarction (MI) and other cardiovascular disease. Ectopic beats can, however, interfere with HRV analysis and give erroneous results. We have therefore studied the impact of ectopic beats on HRV analysis and the ability of a filter algorithm to correct this. Power spectral analysis of synthetic data with an increasing proportion of ectopic beats and 24-h Holter recordings from 98 healthy subjects and 93 post MI patients was done with and without digital filtering and interpolation of errors in the data stream. The analysis of HRV was seriously hampered by less than 1% of ectopic beats. A filter algorithm based on detection and linear interpolation of ectopic beats and other noise in the data stream corrected effectively for this in the synthetic data employed. In the healthy subjects and the post MI patients, filtering markedly reduced the extra variability related to non-normal beats. The software could automatically analyse over one hundred 24-h files in one batch. HRV analysis should include filtering for ectopic beats even with a small number of such beats. It is possible to make a fast analysis automatically even in huge clinical series, which makes it possible to use the method both clinically and in epidemiological studies.
Low-complexity nonlinear adaptive filter based on a pipelined bilinear recurrent neural network.
Zhao, Haiquan; Zeng, Xiangping; He, Zhengyou
2011-09-01
To reduce the computational complexity of the bilinear recurrent neural network (BLRNN), a novel low-complexity nonlinear adaptive filter with a pipelined bilinear recurrent neural network (PBLRNN) is presented in this paper. The PBLRNN, inheriting the modular architectures of the pipelined RNN proposed by Haykin and Li, comprises a number of BLRNN modules that are cascaded in a chained form. Each module is implemented by a small-scale BLRNN with internal dynamics. Since those modules of the PBLRNN can be performed simultaneously in a pipelined parallelism fashion, it would result in a significant improvement of computational efficiency. Moreover, due to nesting module, the performance of the PBLRNN can be further improved. To suit for the modular architectures, a modified adaptive amplitude real-time recurrent learning algorithm is derived on the gradient descent approach. Extensive simulations are carried out to evaluate the performance of the PBLRNN on nonlinear system identification, nonlinear channel equalization, and chaotic time series prediction. Experimental results show that the PBLRNN provides considerably better performance compared to the single BLRNN and RNN models.
Directory of Open Access Journals (Sweden)
M. Manimozhi
2014-05-01
Full Text Available Fault Detection and Isolation (FDI using Linear Kalman Filter (LKF is not sufficient for effective monitoring of nonlinear processes. Most of the chemical plants are nonlinear in nature while operating the plant in a wide range of process variables. In this study we present an approach for designing of Multi Model Adaptive Linear Kalman Filter (MMALKF for Fault Detection and Isolation (FDI of a nonlinear system. The uses a bank of adaptive Kalman filter, with each model based on different fault hypothesis. In this study the effectiveness of the MMALKF has been demonstrated on a spherical tank system. The proposed method is detecting and isolating the sensor and actuator soft faults which occur sequentially or simultaneously.
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...
Directory of Open Access Journals (Sweden)
P.R. Benchimol-Barbosa
2002-11-01
Full Text Available Ventricular late potentials are low-amplitude signals originating from damaged myocardium and detected on the body surface by ECG filtering and averaging. Digital filters present in commercial equipment may interfere with the ability of arrhythmia stratification. We compared 40-Hz BiSpec (BI and classical 40- to 250-Hz band-pass Butterworth bidirectional (BD filters in terms of impact on time domain variables and diagnostic properties. In a transverse retrospective age-adjusted case-control study, 221 subjects with sinus rhythm without bundle branch block were divided into three groups after signal-averaged ECG acquisition: GI (N = 40, clinically normal controls, GII (N = 158, subjects with coronary heart disease without sustained monomorphic ventricular tachycardia (SMVT, and GIII (N = 23, subjects with heart disease and documented SMVT. Conventional variables analyzed from vector magnitude data after averaging to 0.3 µV final noise were obtained by application of each filter to the averaged signal, and evaluated in pairs by numerical comparison and by diagnostic agreement assessment, using conventional and optimized thresholds of normality. Significant differences were found between BI and BD variables in all groups, with diagnostic results showing significant disagreement between both filters [kappa value of 0.61 (P<0.05 for GII and 0.31 for GIII (P = NS]. Sensitivity for SMVT was lower with BI than with BD (65.2 vs 91.3%, respectively, P<0.05. Filters provided significantly different numerical and diagnostic results and the BI filter showed only limited clinical application to risk stratification of ventricular arrhythmia.
A Nonlinear Digital Control Solution for a DC/DC Power Converter
Zhu, Minshao
2002-01-01
A digital Nonlinear Proportional-Integral-Derivative (NPID) control algorithm was proposed to control a 1-kW, PWM, DC/DC, switching power converter. The NPID methodology is introduced and a practical hardware control solution is obtained. The design of the controller was completed using Matlab (trademark) Simulink, while the hardware-in-the-loop testing was performed using both the dSPACE (trademark) rapid prototyping system, and a stand-alone Texas Instruments (trademark) Digital Signal Processor (DSP)-based system. The final Nonlinear digital control algorithm was implemented and tested using the ED408043-1 Westinghouse DC-DC switching power converter. The NPID test results are discussed and compared to the results of a standard Proportional-Integral (PI) controller.
Development of a digital method for neutron/gamma-ray discrimination based on matched filtering
Korolczuk, S.; Linczuk, M.; Romaniuk, R.; Zychor, I.
2016-09-01
Neutron/gamma-ray discrimination is crucial for measurements with detectors sensitive to both neutron and gamma-ray radiation. Different techniques to discriminate between neutrons and gamma-rays based on pulse shape analysis are widely used in many applications, e.g., homeland security, radiation dosimetry, environmental monitoring, fusion experiments, nuclear spectroscopy. A common requirement is to improve a radiation detection level with a high detection reliability. Modern electronic components, such as high speed analog to digital converters and powerful programmable digital circuits for signal processing, allow us to develop a fully digital measurement system. With this solution it is possible to optimize digital signal processing algorithms without changing any electronic components in an acquisition signal path. We report on results obtained with a digital acquisition system DNG@NCBJ designed at the National Centre for Nuclear Research. A 2'' × 2'' EJ309 liquid scintillator was used to register mixed neutron and gamma-ray radiation from PuBe sources. A dedicated algorithm for pulse shape discrimination, based on real-time filtering, was developed and implemented in hardware.
Directory of Open Access Journals (Sweden)
Dalei Song
2012-10-01
Full Text Available The adaptive extended set‐membership filter (AESMF for nonlinear ellipsoidal estimation suffers a mismatch between real process noise and its set boundaries, which may result in unstable estimation. In this paper, a MIT method‐based adaptive set‐membership filter, for the optimization of the set boundaries of process noise, is developed and applied to the nonlinear joint estimation of both time‐varying states and parameters. As a result of using the proposed MIT‐AESMF, the estimation effectiveness and boundary accuracy of traditional AESMF are substantially improved. Simulation results have shown the efficiency and robustness of the proposed method.
Ge, Shuang-Chao; Deng, Ming; Chen, Kai; Li, Bin; Li, Yuan
2016-12-01
Time-domain induced polarization (TDIP) measurement is seriously affected by power line interference and other field noise. Moreover, existing TDIP instruments generally output only the apparent chargeability, without providing complete secondary field information. To increase the robustness of TDIP method against interference and obtain more detailed secondary field information, an improved dataprocessing algorithm is proposed here. This method includes an efficient digital notch filter which can effectively eliminate all the main components of the power line interference. Hardware model of this filter was constructed and Vhsic Hardware Description Language code for it was generated using Digital Signal Processor Builder. In addition, a time-location method was proposed to extract secondary field information in case of unexpected data loss or failure of the synchronous technologies. Finally, the validity and accuracy of the method and the notch filter were verified by using the Cole-Cole model implemented by SIMULINK software. Moreover, indoor and field tests confirmed the application effect of the algorithm in the fieldwork.
Nonlinear Imaging of Microbubble Contrast Agent Using the Volterra Filter: In Vivo Results.
Du, Juan; Liu, Dalong; Ebbini, Emad S
2016-12-01
A nonlinear filtering approach to imaging the dynamics of microbubble ultrasound contrast agents (UCAs) in microvessels is presented. The approach is based on the adaptive third-order Volterra filter (TVF), which separates the linear, quadratic, and cubic components from beamformed pulse-echo ultrasound data. The TVF captures polynomial nonlinearities utilizing the full spectral components of the echo data and not from prespecified bands, e.g., second or third harmonics. This allows for imaging using broadband pulse transmission to preserve the axial resolution and the SNR. In this paper, we present the results from imaging the UCA activity in a 200- [Formula: see text] cellulose tube embedded in a tissue-mimicking phantom using a linear array diagnostic probe. The contrast enhancement was quantified by computing the contrast-to-tissue ratio (CTR) for the different imaging components, i.e., B-mode, pulse inversion (PI), and the TVF components. The temporal mean and standard deviation of the CTR values were computed for all frames in a given data set. Quadratic and cubic images, referred to as QB-mode and CB-mode, produced higher mean CTR values than B-mode, which showed improved sensitivity. Compared with PI, they produced similar or higher mean CTR values with greater spatial specificity. We also report in vivo results from imaging UCA activity in an implanted LNCaP tumor with heterogeneous perfusion. The temporal means and standard deviations of the echogenicity were evaluated in small regions with different perfusion levels in the presence and absence of UCA. The in vivo measurements behaved consistently with the corresponding calculations obtained under microflow conditions in vitro. Specifically, the nonlinear VF components produced larger increases in the temporal mean and standard deviation values compared with B-mode in regions with low to relatively high perfusion. These results showed that polynomial filters such as the TVF can provide an important tool
Chan, Heang-Ping; Vyborny, Carl J.; MacMahon, Heber; Metz, Charles E.; Doi, Kunio; Sickles, Edward A.
1986-06-01
We have conducted a study to assess the effects of digitization and unsharp-mask filtering on the ability of observers to detect subtle microcalcifications in mammograms. Thirty-two conventional screen-film mammograms were selected from patient files by two experienced mammographers. Twelve of the mammograms contained a suspicious cluster of microcalcifications in patients who subsequently underwent biopsy. Twenty of the mammograms were normal cases which were initially interpreted as being free of clustered microcalcifications and did not demonstrate such on careful review. The mammograms were digitized with a high-quality Fuji image processing/simulation system. The system consists of two drum scanners with which an original radiograph can be digitized, processed by a minicomputer, and reconstituted on film. In this study, we employed a sampling aperture of 0.1 mm X 0.1 mm and a sampling distance of 0.1 mm. The density range from 0.2 to 2.75 was digitized to 1024 grey levels per pixel. The digitized images were printed on a single emulsion film with a display aperture having the same size as the sampling aperture. The system was carefully calibrated so that the density and contrast of a digitized image were closely matched to those of the original radiograph. Initially, we evaluated the effects of the weighting factor and the mask size of a unsharp-mask filter on the appearance of mammograms for various types of breasts. Subjective visual comparisons suggested that a mask size of 91 X 91 pixels (9.1 mm X 9.1 mm) enhances the visibility of microcalcifications without excessively increasing the high-frequency noise. Further, a density-dependent weighting factor that increases linearly from 1.5 to 3.0 in the density range of 0.2 to 2.5 enhances the contrast of microcalcifications without introducing many potentially confusing artifacts in the low-density areas. An unsharp-mask filter with these parameters was used to process the digitized mammograms. We conducted
Fadillah, Azhar
2014-01-01
Nowadays, the use of image as form of information is currently increasing. Poor quality of image can reduce its information contained in image. For example, the image contains noise so the information that contained in the image are not clear. Noise on the digital image can be either Gaussian noise, Salt and Pepper Noise, Speckle Noise, and Exponential Noise. One of the mechanisms used to reduce the noise is filtering. Mean Filter method and Median Filter method are a very good method to redu...
Decentralized neural identifier and control for nonlinear systems based on extended Kalman filter.
Castañeda, Carlos E; Esquivel, P
2012-07-01
A time-varying learning algorithm for recurrent high order neural network in order to identify and control nonlinear systems which integrates the use of a statistical framework is proposed. The learning algorithm is based in the extended Kalman filter, where the associated state and measurement noises covariance matrices are composed by the coupled variance between the plant states. The formulation allows identification of interactions associate between plant state and the neural convergence. Furthermore, a sliding window-based method for dynamical modeling of nonstationary systems is presented to improve the neural identification in the proposed methodology. The efficiency and accuracy of the proposed method is assessed to a five degree of freedom (DOF) robot manipulator where based on the time-varying neural identifier model, the decentralized discrete-time block control and sliding mode techniques are used to design independent controllers and develop the trajectory tracking for each DOF.
An inertia-free filter line-search algorithm for large-scale nonlinear programming
Energy Technology Data Exchange (ETDEWEB)
Chiang, Nai-Yuan; Zavala, Victor M.
2016-02-15
We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.
[Selection of digital filtering in the escaping ammonia monitoring with TDLAS].
Zou, De-Bao; Chen, Wen-Liang; Du, Zhen-Hui; Jia, Hao; Qi, Ru-Bin; Li, Hong-Lian; Zhen, Yang; Hou, Yan-Xia; Xu, Ke-Xin
2012-09-01
Tunable diode laser absorption spectroscopy technology (TDLAS), with its advantages of high selectivity and accuracy, provides a reliable approach to the on-line detection of escaping ammonia. Firstly, the present paper introduces the TDLAS principle, experimental system and the analyses of system noise. Then with the concentration of 90 x 10(-6) and 30 x 10(-6) NH3 for example, we used TDLAS system to collect their second harmonic original spectrum with all kinds of noise interference. To improve the signal spectrum, five types of digital filtering methods were respectively used to filter the original spectrum. Finally we did the NH3 experiments of concentration gradient and the long time monitoring: NH3 experiment of 20 x 10(-6). The analysis indicated that the averaging-wavelet filtering is validated to be more accurate than the other filtering methods in the noise reduction, which can improve the precision of the monitoring system from 10 x 10(-6) to 1.25 x 10(-6) and the SNR also increases by 14 times. It provides an effective pretreatment during the monitoring of escaping ammonia of extremely low concentration.
Energy Technology Data Exchange (ETDEWEB)
Park, Yeonok; Park, Chulkyu; Cho, Hyosung; Je, Uikyu; Hong, Daeki; Lee, Minsik; Cho, Heemoon; Choi, Sungil; Koo, Yangseo [Yonsei University, Wonju (Korea, Republic of)
2014-09-15
Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10-30 projections over a limited angle range of 15 - 60 .deg. with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.
Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy
He, Xuefei; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R; Williams, Richard J; Rug, Melanie; Maier, Alexander G; Lee, Woei Ming
2016-01-01
Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected re...
Houts, R. C.; Vaughn, G. L.
1974-01-01
Three algorithms are developed for designing finite impulse response digital filters to be used for pulse shaping and channel equalization. The first is the Minimax algorithm which uses linear programming to design a frequency-sampling filter with a pulse shape that approximates the specification in a minimax sense. Design examples are included which accurately approximate a specified impulse response with a maximum error of 0.03 using only six resonators. The second algorithm is an extension of the Minimax algorithm to design preset equalizers for channels with known impulse responses. Both transversal and frequency-sampling equalizer structures are designed to produce a minimax approximation of a specified channel output waveform. Examples of these designs are compared as to the accuracy of the approximation, the resultant intersymbol interference (ISI), and the required transmitted energy. While the transversal designs are slightly more accurate, the frequency-sampling designs using six resonators have smaller ISI and energy values.
Short term wave forecasting, using digital filters, for improved control of Wave Energy Converters
DEFF Research Database (Denmark)
Tedd, James; Frigaard, Peter
2007-01-01
experimentally. Results are shown form measurements taken on the Wave Dragon prototype device, a floating overtopping device situated in Northern Denmark. In this case the method is able to accurately predict the surface elevation at the device 11.2 seconds before the measurement is made. This is sufficient......This paper presents a Digital Filter method for real time prediction of waves incident upon a Wave Energy device. The method transforms waves measured at a point ahead of the device, to expected waves incident on the device. The relationship between these incident waves and power capture is derived...
DEFF Research Database (Denmark)
Zou, Zhixiang; Wang, Zheng; Cheng, Ming;
2012-01-01
This paper presents an digital dual-mode-structure repetitive control approach for the single-phase shunt active power filter (APF), which aims to enhance the tracking ability and eliminate arbitrary order harmonic. The proposed repetitive control scheme blends the characteristics of both odd......-harmonic repetitive control and even-harmonic repetitive control. Moreover, the convergence rate is faster than conventional repetitive controller. Additionally, the parameters have been designed and optimized for the dual-mode structure repetitive control to improve the performance of APF system. Experimental...... results on a laboratory setup are given to verify the proposed control scheme....
DEFF Research Database (Denmark)
Misaridis, Thanasis; Jensen, Jørgen Arendt
1999-01-01
performed with the program Field II. A commercial scanner (B-K Medical 3535) was modified and interfaced to an arbitrary function generator along with an RF power amplifier (Ritec). Hydrophone measurements in water were done to establish excitation voltage and corresponding intensity levels (I-sptp and I......This paper presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression filter designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, optimal Chebyshev windows efficiently weight a nearly...
Horiguchi, Kenichi; Matsunaga, Naoko; Yamauchi, Kazuhisa; Hayashi, Ryoji; Miyazaki, Moriyasu; Nojima, Toshio
This paper presents a digital predistorter with a wideband memory effect compensator for a Doherty power amplifier (PA). A simple memory-predistortion model, which consists of a look-up-table (LUT) and an adaptive filter equalizing memory effects, and a new memory effect estimation algorithm using a direct-learning architecture are proposed. The proposed estimation algorithm has an advantage that a transfer function of a feedback circuit does not affect the learning process. The predistorter is implemented in a field programmable gate array (FPGA) and a digital signal processor (DSP). The transmitter has achieved distortion level of -50.8dBr at signal bandwidth away from the carrier, and PA module efficiency of 24% with output power of 43dBm at 2595MHz under a 20MHz-bandwidth orthogonal frequency division multiplexing (OFDM) signal using laterally diffused metal oxide semiconductor (LDMOS) FETs.
Directory of Open Access Journals (Sweden)
Zhaohui Chen
2013-01-01
Full Text Available The delay-dependent exponential L2-L∞ performance analysis and filter design are investigated for stochastic systems with mixed delays and nonlinear perturbations. Based on the delay partitioning and integral partitioning technique, an improved delay-dependent sufficient condition for the existence of the L2-L∞ filter is established, by choosing an appropriate Lyapunov-Krasovskii functional and constructing a new integral inequality. The full-order filter design approaches are obtained in terms of linear matrix inequalities (LMIs. By solving the LMIs and using matrix decomposition, the desired filter gains can be obtained, which ensure that the filter error system is exponentially stable with a prescribed L2-L∞ performance γ. Numerical examples are provided to illustrate the effectiveness and significant improvement of the proposed method.
Li, Tao; Yuan, Gannan; Li, Wang
2016-03-15
The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD) system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM) can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS) sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM) by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF) and Kalman filter (KF). The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.
Directory of Open Access Journals (Sweden)
Tao Li
2016-03-01
Full Text Available The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF and Kalman filter (KF. The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.
Mode Coupling and Nonlinear Resonances of MEMS Arch Resonators for Bandpass Filters
Hajjaj, Amal Z.
2017-01-30
We experimentally demonstrate an exploitation of the nonlinear softening, hardening, and veering phenomena (near crossing), where the frequencies of two vibration modes get close to each other, to realize a bandpass filter of sharp roll off from the passband to the stopband. The concept is demonstrated based on an electrothermally tuned and electrostatically driven MEMS arch resonator operated in air. The in-plane resonator is fabricated from a silicon-on-insulator wafer with a deliberate curvature to form an arch shape. A DC current is applied through the resonator to induce heat and modulate its stiffness, and hence its resonance frequencies. We show that the first resonance frequency increases up to twice of the initial value while the third resonance frequency decreases until getting very close to the first resonance frequency. This leads to the phenomenon of veering, where both modes get coupled and exchange energy. We demonstrate that by driving both modes nonlinearly and electrostatically near the veering regime, such that the first and third modes exhibit softening and hardening behavior, respectively, sharp roll off from the passband to the stopband is achievable. We show a flat, wide, and tunable bandwidth and center frequency by controlling the electrothermal actuation voltage.
Application of adaptive non-linear 2D and 3D postprocessing filters for reduced dose abdominal CT.
Borgen, Lars; Kalra, Mannudeep K; Laerum, Frode; Hachette, Isabelle W; Fredriksson, Carina H; Sandborg, Michael; Smedby, Orjan
2012-04-01
Abdominal computed tomography (CT) is a frequently performed imaging procedure, resulting in considerable radiation doses to the patient population. Postprocessing filters are one of several dose reduction measures that might help to reduce radiation doses without loss of image quality. To assess and compare the effect of two- and three-dimensional (2D, 3D) non-linear adaptive filters on reduced dose abdominal CT images. Two baseline abdominal CT image series with a volume computer tomography dose index (CTDI (vol)) of 12 mGy and 6 mGy were acquired for 12 patients. Reduced dose images were postprocessed with 2D and 3D filters. Six radiologists performed blinded randomized, side-by-side image quality assessments. Objective noise was measured. Data were analyzed using visual grading regression and mixed linear models. All image quality criteria were rated as superior for 3D filtered images compared to reduced dose baseline and 2D filtered images (P 0.05). There were no significant variations of objective noise between standard dose and 2D or 3D filtered images. The quality of 3D filtered reduced dose abdominal CT images is superior compared to reduced dose unfiltered and 2D filtered images. For patients with BMI < 30 kg/m(2), 3D filtered images are comparable to standard dose images.
Institute of Scientific and Technical Information of China (English)
孙成发
2013-01-01
Based on optimization design for IIR digital filters being a multi-parameters and non-linear complex function optimization problem,a novel method of IIR digital filters optimization design is proposed,its core is that read-coded quantum evolutionary algorithms(RQEA)is applied on optimizing the interrelated parameters of IIR digital filters.In this paper, firstly,the maths model of IIR digital filter optimization design is proposed;secondly,the process of optimization design for IIR digital filters on the basis of RQEA is described in detail,final y,the validity and effectivenss of the introduced method are demonstrated by experimental results on the lowpass and highpass IIR digital filters.% IIR数字滤波器设计的本质是求解多参数非线性复杂函数优化问题，提出应用实数编码量子进化算法优化IIR数字滤波器的相关参数，进而形成一种新的IIR数字滤波器优化设计方法。文中给出了IIR滤波器优化设计的数学模型，描述了应用实数编码量子进化算法优化设计IIR数字滤波器的具体实现步骤，并通过低通和高通IIR数字滤波器设计的仿真结果表明该方法的有效性和高效性。
Energy Technology Data Exchange (ETDEWEB)
Brito, Helio Glauco Ferreira
1996-12-31
This work introduces an analysis and a comparative study of some of the techniques for digital filtering of the voltage and current waveforms from faulted transmission lines. This study is of fundamental importance for the development of algorithms applied to digital protection of electric power systems. The techniques studied are based on the Discrete Fourier Transform theory, the Walsh functions and the Kalman filter theory. Two aspects were emphasized in this study: Firstly, the non-recursive techniques were analysed with the implementation of filters based on Fourier theory and the Walsh functions. Secondly, recursive techniques were analyzed, with the implementation of the filters based on the Kalman theory and once more on the Fourier theory. (author) 56 refs., 25 figs., 16 tabs.
Arlunno, Valeria; Zhang, Xu; Larsen, Knud J; Zibar, Darko; Monroy, Idelfonso Tafur
2011-12-12
An experimental demonstration of Ultradense WDM with advanced digital signal processing is presented. The scheme proposed allows the use of independent tunable DFB lasers spaced at 12.5 GHz for ultradense WDM PM-QPSK flexible capacity channels for metro core networking. To allocate extremely closed carriers, we demonstrate that a digital non-linear equalization allow to mitigate inter-channel interference and improve overall system performance in terms of OSNR. Evaluation of the algorithm and comparison with an ultradense WDM system with coherent carriers generated from a single laser are also reported. © 2011 Optical Society of America
DEFF Research Database (Denmark)
Arlunno, Valeria; Zhang, Xu; Larsen, Knud J.
2011-01-01
An experimental demonstration of Ultradense WDM with advanced digital signal processing is presented. The scheme proposed allows the use of independent tunable DFB lasers spaced at 12.5 GHz for ultradense WDM PM-QPSK flexible capacity channels for metro core networking. To allocate extremely closed...... carriers, we demonstrate that a digital non-linear equalization allow to mitigate inter-channel interference and improve overall system performance in terms of OSNR. Evaluation of the algorithm and comparison with an ultradense WDM system with coherent carriers generated from a single laser are also...
Tseng, Chien-Hsun
2015-02-01
The technique of multidimensional wave digital filtering (MDWDF) that builds on traveling wave formulation of lumped electrical elements, is successfully implemented on the study of dynamic responses of symmetrically laminated composite plate based on the first order shear deformation theory. The philosophy applied for the first time in this laminate mechanics relies on integration of certain principles involving modeling and simulation, circuit theory, and MD digital signal processing to provide a great variety of outstanding features. Especially benefited by the conservation of passivity gives rise to a nonlinear programming problem (NLP) for the issue of numerical stability of a MD discrete system. Adopting the augmented Lagrangian genetic algorithm, an effective optimization technique for rapidly achieving solution spaces of NLP models, numerical stability of the MDWDF network is well received at all time by the satisfaction of the Courant-Friedrichs-Levy stability criterion with the least restriction. In particular, optimum of the NLP has led to the optimality of the network in terms of effectively and accurately predicting the desired fundamental frequency, and thus to give an insight into the robustness of the network by looking at the distribution of system energies. To further explore the application of the optimum network, more numerical examples are engaged in efforts to achieve a qualitative understanding of the behavior of the laminar system. These are carried out by investigating various effects based on different stacking sequences, stiffness and span-to-thickness ratios, mode shapes and boundary conditions. Results are scrupulously validated by cross referencing with early published works, which show that the present method is in excellent agreement with other numerical and analytical methods.
Kypraios, Ioannis; Young, Rupert C. D.; Birch, Philip M.; Chatwin, Christopher R.
2003-08-01
The various types of synthetic discriminant function (sdf) filter result in a weighted linear superposition of the training set images. Neural network training procedures result in a non-linear superposition of the training set images or, effectively, a feature extraction process, which leads to better interpolation properties than achievable with the sdf filter. However, generally, shift invariance is lost since a data dependant non-linear weighting function is incorporated in the input data window. As a compromise, we train a non-linear superposition filter via neural network methods with the constraint of a linear input to allow for shift invariance. The filter can then be used in a frequency domain based optical correlator. Simulation results are presented that demonstrate the improved training set interpolation achieved by the non-linear filter as compared to a linear superposition filter.
Digital image analysis of cigarette filter staining to estimate smoke exposure.
O'Connor, Richard J; Kozlowski, Lynn T; Hammond, David; Vance, Tammy T; Stitt, Joseph P; Cummings, K Michael
2007-08-01
Sufficient variation exists in how people smoke each cigarette that the number of cigarettes smoked daily and the years of smoking represent only crude measures of exposure to the toxins in tobacco smoke. Previous research has shown that spent cigarette filters can provide information about how individuals smoke cigarettes. Digital image analysis has been used to identify filter vent blocking and may also provide an inexpensive, unobtrusive index of overall smoke exposure. A total of 1,124 cigarette butts smoked by 53 participants in a smoking topography study were imaged and analyzed. Imaging showed test-retest reliability of more than 95% among those smoking their own brand. Mean color scores (CIELAB system) showed acceptable stability (>.60) across days, paralleling the basic stability of smoking topography measures across waves. A principal components scoring showed that center tar staining, edge tar staining, and their interaction were significantly related to total smoke volume, accounting for 73% of the variation. Estimated smoke volume was a significant predictor of salivary cotinine when accounting for cigarettes smoked per day. These data suggest that digital image analysis of spent cigarette butts can serve as a reliable proxy measure of total smoke volume.
Numerical solution of a nonlinear least squares problem in digital breast tomosynthesis
Landi, G.; Loli Piccolomini, E.; Nagy, J. G.
2015-11-01
In digital tomosynthesis imaging, multiple projections of an object are obtained along a small range of different incident angles in order to reconstruct a pseudo-3D representation (i.e., a set of 2D slices) of the object. In this paper we describe some mathematical models for polyenergetic digital breast tomosynthesis image reconstruction that explicitly takes into account various materials composing the object and the polyenergetic nature of the x-ray beam. A polyenergetic model helps to reduce beam hardening artifacts, but the disadvantage is that it requires solving a large-scale nonlinear ill-posed inverse problem. We formulate the image reconstruction process (i.e., the method to solve the ill-posed inverse problem) in a nonlinear least squares framework, and use a Levenberg-Marquardt scheme to solve it. Some implementation details are discussed, and numerical experiments are provided to illustrate the performance of the methods.
Rimell, Andrew N; Mansfield, Neil J; Paddan, Gurmail S
2015-01-01
Many workers are exposed to noise in their industrial environment. Excessive noise exposure can cause health problems and therefore it is important that the worker's noise exposure is assessed. This may require measurement by an equipment manufacturer or the employer. Human exposure to noise may be measured using microphones; however, weighting filters are required to correlate the physical noise sound pressure level measurements to the human's response to an auditory stimulus. IEC 61672-1 and ANSI S1.43 describe suitable weighting filters, but do not explain how to implement them for digitally recorded sound pressure level data. By using the bilinear transform, it is possible to transform the analogue equations given in the standards into digital filters. This paper describes the implementation of the weighting filters as digital IIR (Infinite Impulse Response) filters and provides all the necessary formulae to directly calculate the filter coefficients for any sampling frequency. Thus, the filters in the standards can be implemented in any numerical processing software (such as a spreadsheet or programming language running on a PC, mobile device or embedded system).
Sullivan, Shane Z.; Schmitt, Paul D.; DeWalt, Emma L.; Muir, Ryan D.; Simpson, Garth J.
2013-03-01
Photon counting represents the Poisson limit in signal to noise, but can often be complicated in imaging applications by detector paralysis, arising from the finite rise / fall time of the detector upon photon absorption. We present here an approach for reducing dead-time by generating a deconvolution digital filter based on optimizing the Fisher linear discriminant. In brief, two classes are defined, one in which a photon event is initiated at the origin of the digital filter, and one in the photon event is non-coincident with the filter origin. Linear discriminant analysis (LDA) is then performed to optimize the digital filter that best resolves the coincident and non-coincident training set data.1 Once trained, implementation of the filter can be performed quickly, significantly reducing dead-time issues and measurement bias in photon counting applications. Experimental demonstration of the LDA-filter approach was performed in fluorescence microscopy measurements using a highly convolved impulse response with considerable ringing. Analysis of the counts supports the capabilities of the filter in recovering deconvolved impulse responses under the conditions considered in the study. Potential additional applications and possible limitations are also considered.
A New Mutated Quantum-Behaved Particle Swarm Optimizer for Digital IIR Filter Design
Directory of Open Access Journals (Sweden)
Wenbo Xu
2009-01-01
Full Text Available Adaptive infinite impulse response (IIR filters have shown their worth in a wide range of practical applications. Because the error surface of IIR filters is multimodal in most cases, global optimization techniques are required for avoiding local minima. In this paper, we employ a global optimization algorithm, Quantum-behaved particle swarm optimization (QPSO that was proposed by us previously, and its mutated version in the design of digital IIR filter. The mechanism in QPSO is based on the quantum behaviour of particles in a potential well and particle swarm optimization (PSO algorithm. QPSO is characterized by fast convergence, good search ability, and easy implementation. The mutated QPSO (MuQPSO is proposed in this paper by using a random vector in QPSO to increase the randomness and to enhance the global search ability. Experimental results on three examples show that QPSO and MuQPSO are superior to genetic algorithm (GA, differential evolution (DE algorithm, and PSO algorithm in quality, convergence speed, and robustness.
Digital high-pass deconvolution by means of an infinite impulse response filter
Födisch, P; Lange, B; Schönherr, J; Enghardt, W; Kaever, P
2016-01-01
In the application of semiconductor detectors, the charge-sensitive amplifier is widely used in the front-end electronics. Thus, the output signal is shaped by a typical exponential decay. Depending on the feedback network, this type of front-end electronics suffers from the ballistic deficit problem or an increased rate of pulse pile-ups. Moreover, spectroscopy applications require a correction of the pulse-height, whereas a shortened pulse-width is desirable for high-throughput applications. For both objectives, the digital deconvolution of the exponential decay is convenient. With a general method and the signals of our custom charge-sensitive amplifier for cadmium zinc telluride detectors, we show how the transfer function of an amplifier is adapted to an infinite impulse response (IIR) filter. Therefore, we investigate different design methods for an IIR filter in the discrete-time domain and verify the obtained filter coefficients with respect to the equivalent continuous-time frequency response. Finall...
Directory of Open Access Journals (Sweden)
G. Wu
2014-04-01
Full Text Available The Ensemble Transform Kalman Filter (ETKF assimilation scheme has recently seen rapid development and wide application. As a specific implementation of the Ensemble Kalman Filter (EnKF, the ETKF is computationally more efficient than the conventional EnKF. However, the current implementation of the ETKF still has some limitations when the observation operator is strongly nonlinear. One problem is that the nonlinear operator and its tangent-linear operator are iteratively calculated in the minimization of a nonlinear objective function similar to 4DVAR, which may be computationally expensive. Another problem is that it uses the tangent-linear approximation of the observation operator to estimate the multiplicative inflation factor of the forecast errors, which may not be sufficiently accurate. This study seeks a way to avoid these problems. First, we apply the second-order Taylor approximation of the nonlinear observation operator to avoid iteratively calculating the operator and its tangent-linear operator. The related computational cost is also discussed. Second, we propose a scheme to estimate the inflation factor when the observation operator is strongly nonlinear. Experimentation with the Lorenz-96 model shows that using the second-order Taylor approximation of the nonlinear observation operator leads to a reduction of the analysis error compared with the traditional linear approximation. Similarly, the proposed inflation scheme leads to a reduction of the analysis error compared with the procedure using the traditional inflation scheme.
Subramanian, Aneesh C.
2012-11-01
This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slaved modes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinear model where fast and slow variables modulate each other. This suggests that the analysis step in the PFs maintains the balance in both variables much better than the EnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.
Application of adaptive non-linear 2D and 3D postprocessing filters for reduced dose abdominal CT
Energy Technology Data Exchange (ETDEWEB)
Borgen, Lars (Dept. of Radiology, Drammen Hospital, Drammen and Buskerud Univ. College, Drammen (Norway)), Email: lars.borgen@vestreviken.no; Kalra, Mannudeep K. (Massachusetts General Hospital Imaging, Harvard Medical School, Massachusetts General Hospital, Boston (United States)); Laerum, Frode (Dept. of Radiology, Akershus Univ. Hospital, Loerenskog (Norway)); Hachette, Isabelle W.; Fredriksson, Carina H. (ContextVision AB, Linkoeping (Sweden)); Sandborg, Michael (Dept. of Medical Physics, IMH, Faculty of Health Sciences, Linkoeping Univ., County Council of Oestergoetland, Linkoeping (Sweden); Center for Medical Image Science and Visualization, Linkoeping (Sweden)); Smedby, Oerjan (Center for Medical Image Science and Visualization, Linkoeping (Sweden); Dept. of Radiology, Linkoeping Univ., Linkoeping (Sweden))
2012-04-15
Background: Abdominal computed tomography (CT) is a frequently performed imaging procedure, resulting in considerable radiation doses to the patient population. Postprocessing filters are one of several dose reduction measures that might help to reduce radiation doses without loss of image quality. Purpose: To assess and compare the effect of two- and three-dimensional (2D, 3D) non-linear adaptive filters on reduced dose abdominal CT images. Material and Methods: Two baseline abdominal CT image series with a volume computer tomography dose index (CTDI{sub vol}) of 12 mGy and 6 mGy were acquired for 12 patients. Reduced dose images were postprocessed with 2D and 3D filters. Six radiologists performed blinded randomized, side-by-side image quality assessments. Objective noise was measured. Data were analyzed using visual grading regression and mixed linear models. Results: All image quality criteria were rated as superior for 3D filtered images compared to reduced dose baseline and 2D filtered images (P < 0.01). Standard dose images had better image quality than reduced dose 3D filtered images (P < 0.01), but similar image noise. For patients with body mass index (BMI) < 30 kg/m2 however, 3D filtered images were rated significantly better than normal dose images for two image criteria (P < 0.05), while no significant difference was found for the remaining three image criteria (P > 0.05). There were no significant variations of objective noise between standard dose and 2D or 3D filtered images. Conclusion: The quality of 3D filtered reduced dose abdominal CT images is superior compared to reduced dose unfiltered and 2D filtered images. For patients with BMI < 30 kg/m2, 3D filtered images are comparable to standard dose images
Novel Design of Recursive Differentiator Based on Lattice Wave Digital Filter
Directory of Open Access Journals (Sweden)
R. Barsainya
2017-04-01
Full Text Available In this paper, a novel design of third and fifth order differentiator based on lattice wave digital filter (LWDF, established on optimizing L_1-error approximation function using cuckoo search algorithm (CSA is proposed. We present a novel realization of minimum multiplier differentiator using LWD structure leading to requirement of optimizing only N coefficients for Nth order differentiator. The gamma coefficients of lattice wave digital differentiator (LWDD are computed by minimizing the L_1-norm fitness function leading to a flat response. The superiority of the proposed LWDD is evident by comparing it with other differentiators mentioned in the literature. The magnitude response of the designed LWDD is found to be of high accuracy with flat response in a wide frequency range. The simulation and statistical results validates that the designed minimum multiplier LWDD circumvents the existing one in terms of minimum absolute magnitude error, mean relative error (dB and efficient structural realization, thereby making the proposed LWDD a promising approach to digital differentiator design.
Detecting curvatures in digital images using filters derived from differential geometry
Toro Giraldo, Juanita
2015-09-01
Detection of curvature in digital images is an important theoretical and practical problem in image processing. Many important features in an image are associated with curvature and the detection of such features is reduced to detection and characterization of curvatures. Differential geometry studies many kinds of curvature operators and from these curvature operators is possible to derive powerful filters for image processing which are able to detect curvature in digital images and videos. The curvature operators are formulated in terms of partial differential operators which can be applied to images via convolution with generalized kernels derived from the the Korteweg- de Vries soliton . We present an algorithm for detection of curvature in digital images which is implemented using the Maple package ImageTools. Some experiments were performed and the results were very good. In a future research will be interesting to compare the results using the Korteweg-de Vries soliton with the results obtained using Airy derivatives. It is claimed that the resulting curvature detectors could be incorporated in standard programs for image processing.
基于Matlab的IIR数字滤波器设计%Design of IIR digital filter based on Matlab
Institute of Scientific and Technical Information of China (English)
李敏; 徐艳
2016-01-01
数字滤波是数字信号处理的重要内容，可分为FIR和IIR两大类。文章介绍了基于MATLAB的IIR 数字滤波器设计方法。先确定性能参数，再按照映射规则（冲激响应不变法或双线性变换法）变换成模拟滤波器的性能参数，然后采用一定的逼近方法（巴特沃斯型或切比雪夫型）设计模拟滤波器，最后将模拟滤波器按照映射规则转变成数字滤波器。通过Matlab实验仿真，成功地设计出了满足预定指标的IIR数字滤波器。%The digital filter is one of the most important parts in digital signal processing, it can be divided into two kinds, the finite impulse response and the infinite impulse response. The design method of IIR digital filter based on Matlab is introduced in this paper. First,the performance requirements are determined,and then they are converted into analog filter performance requirements according to the mapping rules(impulse response method or bilinear transformation method),and then analog filter is designed using some approximation method(Butterworth type or Chebyshev type),and at Last analog filter is transformed into digital filter according to the same mapping rules. In this paper, through simulation experiments in Matlab,IIR digital filter that meets scheduled performance requirements are designed successfully.
Khaki, Mehdi; Forootan, Ehsan; Kuhn, Michael; Awange, Joseph; Pattiaratchi, Charitha
2016-04-01
Quantifying large-scale (basin/global) water storage changes is essential to understand the Earth's hydrological water cycle. Hydrological models have usually been used to simulate variations in storage compartments resulting from changes in water fluxes (i.e., precipitation, evapotranspiration and runoff) considering physical or conceptual frameworks. Models however represent limited skills in accurately simulating the storage compartments that could be the result of e.g., the uncertainty of forcing parameters, model structure, etc. In this regards, data assimilation provides a great chance to combine observational data with a prior forecast state to improve both the accuracy of model parameters and to improve the estimation of model states at the same time. Various methods exist that can be used to perform data assimilation into hydrological models. The one more frequently used particle-based algorithms suitable for non-linear systems high-dimensional systems is the Ensemble Kalman Filtering (EnKF). Despite efficiency and simplicity (especially in EnKF), this method indicate some drawbacks. To implement EnKF, one should use the sample covariance of observations and model state variables to update a priori estimates of the state variables. The sample covariance can be suboptimal as a result of small ensemble size, model errors, model nonlinearity, and other factors. Small ensemble can also lead to the development of correlations between state components that are at a significant distance from one another where there is no physical relation. To investigate the under-sampling issue raise by EnKF, covariance inflation technique in conjunction with localization was implemented. In this study, a comparison between latest methods used in the data assimilation framework, to overcome the mentioned problem, is performed. For this, in addition to implementing EnKF, we introduce and apply the Local Ensemble Kalman Filter (LEnKF) utilizing covariance localization to remove
Directory of Open Access Journals (Sweden)
Rozita Teymourzadeh
2010-01-01
Full Text Available Problem statement: The need for high performance transceiver with high Signal to Noise Ratio (SNR has driven the communication system to utilize latest technique identified as over sampling systems. It was the most economical modulator and decimation in communication system. It has been proven to increase the SNR and is used in many high performance systems such as in the Analog to Digital Converter (ADC for wireless transceiver. Approach: This research presented the design of the novel class of decimation and its VLSI implementation which was the sub-component in the over sampling technique. The design and realization of main unit of decimation stage that was the Cascaded Integrator Comb (CIC filter, the associated half band filters and the droop correction are also designed. The Verilog HDL code in Xilinx ISE environment has been derived to describe the proposed advanced CIC filter properties. Consequently, Virtex-II FPGA board was used to implement and test the design on the real hardware. The ASIC design implementation was performed accordingly and resulted power and area measurement on chip core layout. Results: The proposed design focused on the trade-off between the high speed and the low power consumption as well as the silicon area and high resolution for the chip implementation which satisfies wireless communication systems. The synthesis report illustrates the maximum clock frequency of 332 MHz with the active core area of 0.308×0.308 mm2. Conclusion: It can be concluded that VLSI implementation of proposed filter architecture is an enabler in solving problems that affect communication capability in DSP application.
Directory of Open Access Journals (Sweden)
Muammar Sadrawi
2016-01-01
Full Text Available Good quality cardiopulmonary resuscitation (CPR is the mainstay of treatment for managing patients with out-of-hospital cardiac arrest (OHCA. Assessment of the quality of the CPR delivered is now possible through the electrocardiography (ECG signal that can be collected by an automated external defibrillator (AED. This study evaluates a nonlinear approximation of the CPR given to the asystole patients. The raw ECG signal is filtered using ensemble empirical mode decomposition (EEMD, and the CPR-related intrinsic mode functions (IMF are chosen to be evaluated. In addition, sample entropy (SE, complexity index (CI, and detrended fluctuation algorithm (DFA are collated and statistical analysis is performed using ANOVA. The primary outcome measure assessed is the patient survival rate after two hours. CPR pattern of 951 asystole patients was analyzed for quality of CPR delivered. There was no significant difference observed in the CPR-related IMFs peak-to-peak interval analysis for patients who are younger or older than 60 years of age, similarly to the amplitude difference evaluation for SE and DFA. However, there is a difference noted for the CI (p<0.05. The results show that patients group younger than 60 years have higher survival rate with high complexity of the CPR-IMFs amplitude differences.
Mustaffa, Izadora; Trenado, Carlos; Schwerdtfeger, Karsten; Strauss, Daniel J
2008-01-01
Recent progress in mathematical image processing shows a remarkable success when applying numerical methods to ill-posed partial differential equations (PDE). In particular, nonlinear diffusion filtering (NDF)process is an approach that belongs to such family of differential equations. It has been successfully applied in many recent methods for image processing and computer vision areas, particularly in denoising, smoothing, segmentation, and restoration. In this paper we focus on a novel NDF application, namely denoising of single-trials of auditory brainstem responses (ABRs) and the analysis of transcranial magnetic stimulation (TMS) responses.We show that by applying NDF on a matrix-form image of single-trials, we were able to denoise the single-trials, resulting in a better extraction of information over the ongoing experiment; morphology, eg. the latency of the single-trials according to different stimuli paradigms at different stimulation intensity levels. It is concluded that NDF represents a novel and useful approach for the analysis of single-trials in brain imaging.
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Hongjian Wang
2014-01-01
Full Text Available We present a support vector regression-based adaptive divided difference filter (SVRADDF algorithm for improving the low state estimation accuracy of nonlinear systems, which are typically affected by large initial estimation errors and imprecise prior knowledge of process and measurement noises. The derivative-free SVRADDF algorithm is significantly simpler to compute than other methods and is implemented using only functional evaluations. The SVRADDF algorithm involves the use of the theoretical and actual covariance of the innovation sequence. Support vector regression (SVR is employed to generate the adaptive factor to tune the noise covariance at each sampling instant when the measurement update step executes, which improves the algorithm’s robustness. The performance of the proposed algorithm is evaluated by estimating states for (i an underwater nonmaneuvering target bearing-only tracking system and (ii maneuvering target bearing-only tracking in an air-traffic control system. The simulation results show that the proposed SVRADDF algorithm exhibits better performance when compared with a traditional DDF algorithm.
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Yi-Ming Chen
2017-01-01
Full Text Available Noninvasive medical procedures are usually preferable to their invasive counterparts in the medical community. Anemia examining through the palpebral conjunctiva is a convenient noninvasive procedure. The procedure can be automated to reduce the medical cost. We propose an anemia examining approach by using a Kalman filter (KF and a regression method. The traditional KF is often used in time-dependent applications. Here, we modified the traditional KF for the time-independent data in medical applications. We simply compute the mean value of the red component of the palpebral conjunctiva image as our recognition feature and use a penalty regression algorithm to find a nonlinear curve that best fits the data of feature values and the corresponding levels of hemoglobin (Hb concentration. To evaluate the proposed approach and several relevant approaches, we propose a risk evaluation scheme, where the entire Hb spectrum is divided into high-risk, low-risk, and doubtful intervals for anemia. The doubtful interval contains the Hb threshold, say 11 g/dL, separating anemia and nonanemia. A suspect sample is the sample falling in the doubtful interval. For the anemia screening purpose, we would like to have as less suspect samples as possible. The experimental results show that the modified KF reduces the number of suspect samples significantly for all the approaches considered here.
Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro
2015-01-01
Objective Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography. PMID:26811553
Edge-Directed Error Diffused Digital Halftoning: A Steerable Filter Approach
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Pardeep Garg
2009-09-01
Full Text Available In this paper the edge-directed error diffused digital halftoning in noisy media is analyzed. It is known that there occurs error in transmitting data through a communication channel due toaddition of noise, generally additive white Gaussian noise (AWGN. The proposed work employs Steerable stochastic error diffusion (SSED approach, a hybrid scheme that utilizes the advantages of Steerable filter for edge detection purpose and five neighbor stochastic error diffusion (FNSED approach for error diffusion purpose. Analysis of different methods of edgedetectionand error diffusion in the presence of zero mean AWGN with different values of variance has also been made. The results show that the proposed scheme produces halftones of better quality in the presence of even large value of noise variance compared to other approaches of edge detection and error diffusion.
Short term wave forecasting, using digital filters, for improved control of Wave Energy Converters
Energy Technology Data Exchange (ETDEWEB)
Tedd, J.; Frigaard, P. [Department of Civil Engineering, Aalborg University, Aalborg (Denmark)
2007-07-01
This paper presents a Digital Filter method for real time prediction of waves incident upon a Wave Energy device. The method transforms waves measured at a point ahead of the device, to expected waves incident on the device. The relationship between these incident waves and power capture is derived experimentally. Results are shown form measurements taken on the Wave Dragon prototype device, a floating overtopping device situated in Northern Denmark. In this case the method is able to accurately predict the surface elevation at the device 11.2 seconds before the measurement is made. This is sufficient to allow advanced control systems to be developed using this knowledge to significantly improve power capture.
Kee, Chul-Sik; Lee, Yeong Lak; Lee, Jongmin
2008-04-28
We investigate electro- and thermo-optic effects on multi-wavelength Solc filters based on chi(2) nonlinear quasi-periodic photonic crystals. The multi-wavelength Solc filters are composed of two building blocks A and B, in which each containing a pair of antiparallel poled domains, arranged as a Fibonacci sequence. The transmittances at filtering wavelengths can be modulated from 0 to 100% by applying an external voltage but the filtering wave-lengths are unchanged. The filtering wavelengths can be tuned by varying temperature. As temperature decreases, the filtering wavelengths increase (approximately -0.45 nm/degrees C).
Aboutabikh, Kamal; Aboukerdah, Nader
2015-07-01
In this paper, we propose a practical way to synthesize and filter an ECG signal in the presence of four types of interference signals: (1) those arising from power networks with a fundamental frequency of 50Hz, (2) those arising from respiration, having a frequency range from 0.05 to 0.5Hz, (3) muscle signals with a frequency of 25Hz, and (4) white noise present within the ECG signal band. This was done by implementing a multiband digital filter (seven bands) of type FIR Multiband Least Squares using a digital programmable device (Cyclone II EP2C70F896C6 FPGA, Altera), which was placed on an education and development board (DE2-70, Terasic). This filter was designed using the VHDL language in the Quartus II 9.1 design environment. The proposed method depends on Direct Digital Frequency Synthesizers (DDFS) designed to synthesize the ECG signal and various interference signals. So that the synthetic ECG specifications would be closer to actual ECG signals after filtering, we designed in a single multiband digital filter instead of using three separate digital filters LPF, HPF, BSF. Thus all interference signals were removed with a single digital filter. The multiband digital filter results were studied using a digital oscilloscope to characterize input and output signals in the presence of differing sinusoidal interference signals and white noise.
Shrestha, Suman; Vedantham, Srinivasan; Karellas, Andrew
2017-03-01
In digital breast tomosynthesis and digital mammography, the x-ray beam filter material and thickness vary between systems. Replacing K-edge filters with Al was investigated with the intent to reduce exposure duration and to simplify system design. Tungsten target x-ray spectra were simulated with K-edge filters (50 µm Rh; 50 µm Ag) and Al filters of varying thickness. Monte Carlo simulations were conducted to quantify the x-ray scatter from various filters alone, scatter-to-primary ratio (SPR) with compressed breasts, and to determine the radiation dose to the breast. These data were used to analytically compute the signal-difference-to-noise ratio (SDNR) at unit (1 mGy) mean glandular dose (MGD) for W/Rh and W/Ag spectra. At SDNR matched between K-edge and Al filtered spectra, the reductions in exposure duration and MGD were quantified for three strategies: (i) fixed Al thickness and matched tube potential in kilovolts (kV); (ii) fixed Al thickness and varying the kV to match the half-value layer (HVL) between Al and K-edge filtered spectra; and, (iii) matched kV and varying the Al thickness to match the HVL between Al and K-edge filtered spectra. Monte Carlo simulations indicate that the SPR with and without the breast were not different between Al and K-edge filters. Modelling for fixed Al thickness (700 µm) and kV matched to K-edge filtered spectra, identical SDNR was achieved with 37-57% reduction in exposure duration and with 2-20% reduction in MGD, depending on breast thickness. Modelling for fixed Al thickness (700 µm) and HVL matched by increasing the kV over (0,4) range, identical SDNR was achieved with 62-65% decrease in exposure duration and with 2-24% reduction in MGD, depending on breast thickness. For kV and HVL matched to K-edge filtered spectra by varying Al filter thickness over (700, 880) µm range, identical SDNR was achieved with 23-56% reduction in exposure duration and 2-20% reduction in MGD, depending on breast thickness. These
Directory of Open Access Journals (Sweden)
Mahavir Dhoka
2014-06-01
Full Text Available In recent years, data protection is one of important aspect because of cases like piracy, copyright and ownership issues. Digital watermark seems to be solution to the problem. In our paper, we proposed a method of invisible watermark to medical image using Biorthogonal wavelet filter and transformed domain watermark embedding. Generally watermark is embedded in original image either directly or in transform of original image. In our method, we transformed both original image and watermark using discrete wavelet transform and Biorthogonal wavelet filter coefficients. We specifically follow this method considering the case of medical images. As medical images are low contrast images and are taken at high precision with special equipment, so it is not expected that any one will claim for its ownership. Hence we tried to develop a method which will recover watermark through medical image considering any kind of attacks. We tested our method on multiple medical images and listed down results and comparison is made on basis of PSNR and normalised correlation (NC. From the values of NC, we concluded that our method gives better recovery of watermark from watermarked image.
Application of digital tomosynthesis (DTS) of optimal deblurring filters for dental X-ray imaging
Energy Technology Data Exchange (ETDEWEB)
Oh, J. E.; Cho, H. S.; Kim, D. S.; Choi, S. I.; Je, U. K. [Yonsei University, Wonju (Korea, Republic of)
2012-04-15
Digital tomosynthesis (DTS) is a limited-angle tomographic technique that provides some of the tomographic benefits of computed tomography (CT) but at reduced dose and cost. Thus, the potential for application of DTS to dental X-ray imaging seems promising. As a continuation of our dental radiography R and D, we developed an effective DTS reconstruction algorithm and implemented it in conjunction with a commercial dental CT system for potential use in dental implant placement. The reconstruction algorithm employed a backprojection filtering (BPF) method based upon optimal deblurring filters to suppress effectively both the blur artifacts originating from the out-focus planes and the high-frequency noise. To verify the usefulness of the reconstruction algorithm, we performed systematic simulation works and evaluated the image characteristics. We also performed experimental works in which DTS images of enhanced anatomical resolution were successfully obtained by using the algorithm and were promising to our ongoing applications to dental X-ray imaging. In this paper, our approach to the development of the DTS reconstruction algorithm and the results are described in detail.
Simulation study of beam extraction from a synchrotron using colored noise with digital filter
Nakanishi, Tetsuya; Tsuruha, Kohei
2009-09-01
A simulation program is developed for a slow-extraction method using a fast Q magnet (FQ) and an RF-knockout. In this extraction method, after the separatrix is produced with excitation of sextupole magnets, a required quantity of circulating beam is extracted by shrinking the separatrix with excitation of the FQ. Then the emittance of circulating beam is diffused to an original size with the RF-knockout. This process is repeated with required timing until the entire circulating beam is completely extracted. An algorithm using a digital filter and white noise is proposed for a colored noise as a signal source for the RF-knockout. Spill structures with the present computing method were similar to the results obtained using a conventional algorithm with the sum of cosines of many frequency components. The results are also in agreement with the experimental results using the HIMAC synchrotron. The computing time of colored noise for simulation of 10 6 turns was 0.5 h for the filter method and 5.0 h for the conventional one. It is indicated that a colored noise with a wider frequency bandwidth gives a better spill structure that smoothly increases with time.
On the structural limitations of recursive digital filters for base flow estimation
Su, Chun-Hsu; Costelloe, Justin F.; Peterson, Tim J.; Western, Andrew W.
2016-06-01
Recursive digital filters (RDFs) are widely used for estimating base flow from streamflow hydrographs, and various forms of RDFs have been developed based on different physical models. Numerical experiments have been used to objectively evaluate their performance, but they have not been sufficiently comprehensive to assess a wide range of RDFs. This paper extends these studies to understand the limitations of a generalized RDF method as a pathway for future field calibration. Two formalisms are presented to generalize most existing RDFs, allowing systematic tuning of their complexity. The RDFs with variable complexity are evaluated collectively in a synthetic setting, using modeled daily base flow produced by Li et al. (2014) from a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation reveals that there are optimal RDF complexities in reproducing base flow simulations but shows that there is an inherent physical inconsistency within the RDF construction. Even under the idealized setting where true base flow data are available to calibrate the RDFs, there is persistent disagreement between true and estimated base flow over catchments with small base flow components, low saturated hydraulic conductivity of the soil and larger surface runoff. The simplest explanation is that low base flow "signal" in the streamflow data is hard to distinguish, although more complex RDFs can improve upon the simpler Eckhardt filter at these catchments.
High-resolution image digitizing through 12x3-bit RGB-filtered CCD camera
Cheng, Andrew Y. S.; Pau, Michael C. Y.
1996-09-01
A high resolution computer-controlled CCD image capturing system is developed by using a 12 bits 1024 by 1024 pixels CCD camera and motorized RGB filters to grasp an image with color depth up to 36 bits. The filters distinguish the major components of color and collect them separately while the CCD camera maintains the spatial resolution and detector filling factor. The color separation can be done optically rather than electronically. The operation is simply by placing the capturing objects like color photos, slides and even x-ray transparencies under the camera system, the necessary parameters such as integration time, mixing level and light intensity are automatically adjusted by an on-line expert system. This greatly reduces the restrictions of the capturing species. This unique approach can save considerable time for adjusting the quality of image, give much more flexibility of manipulating captured object even if it is a 3D object with minimal setup fixers. In addition, cross sectional dimension of a 3D capturing object can be analyzed by adapting a fiber optic ring light source. It is particularly useful in non-contact metrology of a 3D structure. The digitized information can be stored in an easily transferable format. Users can also perform a special LUT mapping automatically or manually. Applications of the system include medical images archiving, printing quality control, 3D machine vision, and etc.
Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-05-23
This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level.
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Muhammad Ilyas
2016-05-01
Full Text Available This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF and Unscented Kalman filter (UKF were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level.
Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-01-01
This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. PMID:27223293
Digital tapped delay lines for HWIL testing of matched filter radar receivers
Olson, Richard F.; Braselton, William J.; Mohlere, Richard D.
2009-05-01
Matched filter processing for pulse compression of phase coded waveforms is a classic method for increasing radar range measurement resolution. A generic approach for simulating high resolution range extended radar scenes in a Hardware in the Loop (HWIL) test environment is to pass the phase coded radar transmit pulse through an RF tapped delay line comprised of individually amplitude- and phase-weighted output taps. In the generic approach, the taps are closely spaced relative to time intervals equivalent to the range resolution of the compressed radar pulse. For a range-extended high resolution clutter scene, the increased number of these taps can make an analog implementation of an RF tapped delay system impractical. Engineers at the U.S. Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) have addressed this problem by transferring RF tapped delay line signal operations to the digital domain. New digital tapped delay line (DTDL) systems have been designed and demonstrated which are physically compact compared to analog RF TDLs, leverage low cost FPGA and data converter technology, and may be readily expanded using open slots in a VME card cage. In initial HWIL applications, the new DTDLs have been shown to produce better dynamic range in pulse compressed range profiles than their analog TDL predecessors. This paper describes the signal requirements and system architecture for digital tapped delay lines. Implementation, performance, and HWIL simulation integration issues for AMRDEC's first generation DTDLs are addressed. The paper concludes with future requirements and plans for ongoing DTDL technology development at AMRDEC.
Sajedi, Salar; Kamal Asl, Alireza; Ay, Mohammad R; Farahani, Mohammad H; Rahmim, Arman
2013-06-01
Applications in imaging and spectroscopy rely on pulse processing methods for appropriate data generation. Often, the particular method utilized does not highly impact data quality, whereas in some scenarios, such as in the presence of high count rates or high frequency pulses, this issue merits extra consideration. In the present study, a new approach for pulse processing in nuclear medicine imaging and spectroscopy is introduced and evaluated. The new non-linear recursive filter (NLRF) performs nonlinear processing of the input signal and extracts the main pulse characteristics, having the powerful ability to recover pulses that would ordinarily result in pulse pile-up. The filter design defines sampling frequencies lower than the Nyquist frequency. In the literature, for systems involving NaI(Tl) detectors and photomultiplier tubes (PMTs), with a signal bandwidth considered as 15 MHz, the sampling frequency should be at least 30 MHz (the Nyquist rate), whereas in the present work, a sampling rate of 3.3 MHz was shown to yield very promising results. This was obtained by exploiting the known shape feature instead of utilizing a general sampling algorithm. The simulation and experimental results show that the proposed filter enhances count rates in spectroscopy. With this filter, the system behaves almost identically as a general pulse detection system with a dead time considerably reduced to the new sampling time (300 ns). Furthermore, because of its unique feature for determining exact event times, the method could prove very useful in time-of-flight PET imaging.
Zhabitsky, V. M.
2010-12-01
The stability of an ion beam in synchrotrons with digital filters in the feedback loop of a transverse damper is treated. A transverse feedback system (TFS) is required in synchrotrons to stabilize the high intensity ion beams against transverse instabilities and to damp the beam injection errors. The TFS damper kicker (DK) corrects the transverse momentum of a bunch in proportion to its displacement from the closed orbit at the location of the beam position monitor (BPM). The digital signal processing unit in the feedback loop between BPM and DK ensures a condition to achieve optimal damping. Damping rates of the feedback systems with digital filters are analysed in comparison with those in an ideal feedback system.
Qiu, Meng; Zhuge, Qunbi; Chagnon, Mathieu; Gao, Yuliang; Xu, Xian; Morsy-Osman, Mohamed; Plant, David V
2014-07-28
In this work we experimentally investigate the improved intra-channel fiber nonlinearity tolerance of digital subcarrier multiplexed (SCM) signals in a single-channel coherent optical transmission system. The digital signal processing (DSP) for the generation and reception of the SCM signals is described. We show experimentally that the SCM signal with a nearly-optimum number of subcarriers can extend the maximum reach by 23% in a 24 GBaud DP-QPSK transmission with a BER threshold of 3.8 × 10(-3) and by 8% in a 24 GBaud DP-16-QAM transmission with a BER threshold of 2 × 10(-2). Moreover, we show by simulations that the improved performance of SCM signals is observed over a wide range of baud rates, further indicating the merits of SCM signals in baud-rate flexible agile transmissions and future high-speed optical transport systems.
Input-Dependent Integral Nonlinearity Modeling for Pipelined Analog-Digital Converters
Samer Medawar; Peter Händel; Niclas Björsell; Magnus Jansson
2010-01-01
Integral nonlinearity (INL) for pipelined analog-digital converters (ADCs) operating at RF is measured and characterized. A parametric model for the INL of pipelined ADCs is proposed, and the corresponding least-squares problem is formulated and solved. The INL is modeled both with respect to the converter output code and the frequency stimuli, which is dynamic modeling. The INL model contains a static and a dynamic part. The former comprises two 1-D terms in ADC code that are a sequence of z...
On Power Factor Improvement by Lossless Linear Filters in the Nonlinear Nonsinusoidal Case
Puerto-Flores, Dunstano del; Scherpen, Jacquelien M.A.; Ortega, Romeo
2010-01-01
Recently, it has been established that the problem of power factor compensation (PFC) for nonlinear loads with non-sinusoidal source voltage can be recast in terms of the property of cyclodissipativity. Using this framework we study the PFC for nonlinear loads containing a memoryless nonlinearity. W
On Power Factor Improvement by Lossless Linear Filters in the Nonlinear Nonsinusoidal Case
Puerto-Flores, Dunstano del; Scherpen, Jacquelien M.A.; Ortega, Romeo
2010-01-01
Recently, it has been established that the problem of power factor compensation (PFC) for nonlinear loads with non-sinusoidal source voltage can be recast in terms of the property of cyclodissipativity. Using this framework we study the PFC for nonlinear loads containing a memoryless nonlinearity.
Aguirre, Luis Antonio; Teixeira, Bruno Otávio S.; Tôrres, Leonardo Antônio B.
2005-08-01
This paper addresses the problem of state estimation for nonlinear systems by means of the unscented Kalman filter (UKF). Compared to the traditional extended Kalman filter, the UKF does not require the local linearization of the system equations used in the propagation stage. Important results using the UKF have been reported recently but in every case the system equations used by the filter were considered known. Not only that, such models are usually considered to be differential equations, which requires that numerical integration be performed during the propagation phase of the filter. In this paper the dynamical equations of the system are taken to be difference equations—thus avoiding numerical integration—and are built from data without prior knowledge. The identified models are subsequently implemented in the filter in order to accomplish state estimation. The paper discusses the impact of not knowing the exact equations and using data-driven models in the context of state and joint state-and-parameter estimation. The procedure is illustrated by means of examples that use simulated and measured data.
DEFF Research Database (Denmark)
Yu, Jianjun; Jeppesen, Palle
2001-01-01
Using cross-phase modulation in a 1-km high-nonlinearity dispersion-shifted fiber with subsequent filtering by a tunable optical filter, 80-Gb/s pulsewidth maintained wavelength conversion is realized. Penalty-free transmission over 80-km conventional single-mode fiber and 12-km dispersion...
Applications of Kalman filters based on non-linear functions to numerical weather predictions
Directory of Open Access Journals (Sweden)
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Three different criteria for the design of two-dimensional zero phase FIR digital filters
DEFF Research Database (Denmark)
Gislason, E.; Johansen, M.; Conradsen, Knut
1993-01-01
An error criterion for the design of FIR filters is proposed. Filters with relatively many free filter coefficients are designed using the Chebyshev, the weighted-least-squares (WLS), and a new partitioned minimax error criterion, and the performance of the filters is compared. A general and fast...
Directory of Open Access Journals (Sweden)
Deepa Yagain
2014-01-01
Full Text Available Retiming is a transformation which can be applied to digital filter blocks that can increase the clock frequency. This transformation requires computation of critical path and shortest path at various stages. In literature, this problem is addressed at multiple points. However, very little attention is given to path solver blocks in retiming transformation algorithm which takes up most of the computation time. In this paper, we address the problem of optimizing the speed of path solvers in retiming transformation by introducing high level synthesis of path solver algorithm architectures on FPGA and a computer aided design tool. Filters have their combination blocks as adders, multipliers, and delay elements. Avoiding costly multipliers is very much needed for filter hardware implementation. This can be achieved efficiently by using multiplierless MCM technique. In the present work, retiming which is a high level synthesis optimization method is combined with multiplierless filter implementations using MCM algorithm. It is seen that retiming multiplierless designs gives better performance in terms of operating frequency. This paper also compares various retiming techniques for multiplierless digital filter design with respect to VLSI performance metrics such as area, speed, and power.
Institute of Scientific and Technical Information of China (English)
陶华学; 郭金运
2003-01-01
Data coming from different sources have different types and temporal states. Relations between one type of data and another ones, or between data and unknown parameters are almost nonlinear. It is not accurate and reliable to process the data in building the digital earth with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method was put forward to process data in building the digital earth. A separating solution model and the iterative calculation method were used to solve the generalized nonlinear dynamic least squares problem. In fact, a complex problem can be separated and then solved by converting to two sub-problems, each of which has a single variable. Therefore the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations.
Olarte, Omar E.; Licea-Rodriguez, Jacob; Palero, Jonathan A.; Gualda, Emilio J.; Artigas, David; Mayer, Jürgen; Swoger, Jim; Sharpe, James; Rocha-Mendoza, Israel; Rangel-Rojo, Raul; Loza-Alvarez, Pablo
2012-01-01
We present the implementation of a combined digital scanned light-sheet microscope (DSLM) able to work in the linear and nonlinear regimes under either Gaussian or Bessel beam excitation schemes. A complete characterization of the setup is performed and a comparison of the performance of each DSLM imaging modality is presented using in vivo Caenorhabditis elegans samples. We found that the use of Bessel beam nonlinear excitation results in better image contrast over a wider field of view. PMID:22808423
Zenteno, Efrain; Piazza, Roberto; M. R. Bhavani Shankar; Rönnow, Daniel; Ottersten, Björn
2015-01-01
A digital predistortion (DPD) scheme is presented for non-linear distortion mitigation in multi-carrier satellite communication channels. The proposed DPD has a multiple-input multiple-output architecture similar to data DPD schemes. However, it enhances the mitigation performance of data DPDs using a multi-rate processing algorithm to achieve spectrum broadening of non-linear operators. Compared to single carrier (single-input single-output) signal (waveform) DPD schemes, the proposed DPD ha...
DEFF Research Database (Denmark)
Lu, Xiaonan; Sun, Kai; Huang, Lipei
2014-01-01
to the conventional active damping approaches, the biquad filter based active damping method does not require additional sensors and control loops. Meanwhile, the multiple instable closed-loop poles of the parallel inverter system can be moved to the stable region simultaneously. Real-time simulations based on dSPACE...
Li, Yuan; Quan, Mingran; Tian, Jiajun; Yao, Yong
2015-05-01
A tunable multiwavelength erbium-doped fiber laser (MWEDFL) based on nonlinear optical loop mirror (NOLM) and tunable birefringence fiber filter (BFF) is proposed and demonstrated. By combination of intensity-dependent loss modulation induced by NOLM and pump power adjustment, the proposed laser can achieve independent control over the number of lasing lines, without affecting other important characteristics such as channel spacing and peak location. In addition, the laser allows wavelength tuning with both the peak location and the spectral range of lasing lines controllable. Specifically, the peak location of lasing lines can be controlled to scan the whole spectral range between adjacent channels of comb filter by adjusting the BFF. Moreover, the spectral range of lasing lines can be controlled by adjusting NOLM. This tunable MWEDFL may be useful for fiber-optic communication and fiber-optic sensing.
Modeling of racetrack-resonator add-drop filters with arbitrary nonlinear directional couplers.
Gómez-Alcalá, Rafael; Fraile-Peláez, F Javier; Chamorro-Posada, Pedro; Díaz-Otero, Francisco J
2012-06-01
In this Letter we employ the general coupled-mode equations of the nonlinear directional coupler and demonstrate that the switching characteristics of prototypical nonlinear racetrack-resonator structures may differ considerably from those obtained when the standard, generally incorrect, coupled-mode equations are used.
Ma, Lifeng; Wang, Zidong; Lam, Hak-Keung; Kyriakoulis, Nikos
2016-07-07
In this paper, the distributed set-membership filtering problem is investigated for a class of discrete time-varying system with an event-based communication mechanism over sensor networks. The system under consideration is subject to sector-bounded nonlinearity, unknown but bounded noises and sensor saturations. Each intelligent sensing node transmits the data to its neighbors only when certain triggering condition is violated. By means of a set of recursive matrix inequalities, sufficient conditions are derived for the existence of the desired distributed event-based filter which is capable of confining the system state in certain ellipsoidal regions centered at the estimates. Within the established theoretical framework, two additional optimization problems are formulated: one is to seek the minimal ellipsoids (in the sense of matrix trace) for the best filtering performance, and the other is to maximize the triggering threshold so as to reduce the triggering frequency with satisfactory filtering performance. A numerically attractive chaos algorithm is employed to solve the optimization problems. Finally, an illustrative example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.
Directory of Open Access Journals (Sweden)
Junichi Susaki
2012-06-01
Full Text Available A filtering algorithm is proposed that accurately extracts ground data from airborne light detection and ranging (LiDAR measurements and generates an estimated digital terrain model (DTM. The proposed algorithm utilizes planar surface features and connectivity with locally lowest points to improve the extraction of ground points (GPs. A slope parameter used in the proposed algorithm is updated after an initial estimation of the DTM, and thus local terrain information can be included. As a result, the proposed algorithm can extract GPs from areas where different degrees of slope variation are interspersed. Specifically, along roads and streets, GPs were extracted from urban areas, from hilly areas such as forests, and from flat area such as riverbanks. Validation using reference data showed that, compared with commercial filtering software, the proposed algorithm extracts GPs with higher accuracy. Therefore, the proposed filtering algorithm effectively generates DTMs, even for dense urban areas, from airborne LiDAR data.
Tractable Latent State Filtering for Non-Linear DSGE Models Using a Second-Order Approximation
Kollmann, Robert
2013-01-01
This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the ‘pruning’ scheme of Kim, Kim, Schaumburg and Sims (2008). By contrast to particle filters, no stochastic simulations are needed for the filter here--the present method is thus much faster. In Monte Carlo e...
The Design of Digital Filter Based on MATLAB%基于MATLAB的数字滤波器的设计
Institute of Scientific and Technical Information of China (English)
刘艳
2013-01-01
This paper elaborates the digital filter by using the MATLAB, and realizes the filter design and simulation by using MAT-LAB language and tools. MATLAB language and MATLAB tools can design the digital filters symstem conveniently and quickly, so it can save many programming time, enhaces the programming efficiency, and the parameter revision is also convenient. It is favor-able to optimizing the filter design. It provides detailed steps for designing programs and interfaces by using the MATLAB.%该文阐述了利用MATLAB设计数字滤波器，并利用MATLAB语言和MATLAB工具包实现了滤波器的设计与仿真。MATLAB语言及MATLAB工具包均能方便、快速地设计出数字滤波器，可节省大量的编程时间，提高编程效率，且参数的修改也十分方便。该文给出了使用MATLAB语言进行程序设计和工具包设计的详细步骤。
The influence of the group delay of digital filters on acoustic decay measurements
DEFF Research Database (Denmark)
Sobreira-Seoane, Manuel A.; Cabo, David Pérez; Jacobsen, Finn
2012-01-01
to their phase response. In this investigation the two components are separated and the phase error analyzed in terms of the group delay of the filters. Linear phase FIR filters and minimum phase IIR filters fulfilling the class 1 requirements of the IEC 61260 standard have been designed, and their errors...
Nonlinear color-image decomposition for image processing of a digital color camera
Saito, Takahiro; Aizawa, Haruya; Yamada, Daisuke; Komatsu, Takashi
2009-01-01
This paper extends the BV (Bounded Variation) - G and/or the BV-L1 variational nonlinear image-decomposition approaches, which are considered to be useful for image processing of a digital color camera, to genuine color-image decomposition approaches. For utilizing inter-channel color cross-correlations, this paper first introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G and/or BV-L1 energy functionals, and then derives denoising-type decomposition-algorithms with an over-complete wavelet transform, through applying the Besov-norm approximation to the variational problems. Our methods decompose a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and they achieve desirable high-quality color-image decomposition, which is very robust against colored random noise.
Analysis of bus width and delay on a fully digital signum nonlinearity chaotic oscillator
Mansingka, Abhinav S.
2012-07-29
This paper introduces the first fully digital implementation of a 3rd order ODE-based chaotic oscillator with signum nonlinearity. A threshold bus width of 12-bits for reliable chaotic behavior is observed, below which the system output becomes periodic. Beyond this threshold, the maximum Lyapunov exponent (MLE) is shown to improve up to a peak value at 16-bits and subsequently decrease with increasing bus width. The MLE is also shown to gradually increase with number of introduced internal delay cycles until a peak value at 14 cycles, after which the system loses chaotic properties. Introduced external delay cycles are shown to rotate the attractors in 3-D phase space. Bus width and delay elements can be independently modulated to optimize the system to suit specifications. The experimental results of the system show low area and high performance on a Xilinx Virtex 4 FPGA with throughput of 13.35 Gbits/s for a 32-bit implementation.
A limited memory BFGS method for a nonlinear inverse problem in digital breast tomosynthesis
Landi, G.; Loli Piccolomini, E.; Nagy, J. G.
2017-09-01
Digital breast tomosynthesis (DBT) is an imaging technique that allows the reconstruction of a pseudo three-dimensional image of the breast from a finite number of low-dose two-dimensional projections obtained by different x-ray tube angles. An issue that is often ignored in DBT is the fact that an x-ray beam is polyenergetic, i.e. it is composed of photons with different levels of energy. The polyenergetic model requires solving a large-scale, nonlinear inverse problem, which is more expensive than the typically used simplified, linear monoenergetic model. However, the polyenergetic model is much less susceptible to beam hardening artifacts, which show up as dark streaks and cupping (i.e. background nonuniformities) in the reconstructed image. In addition, it has been shown that the polyenergetic model can be exploited to obtain additional quantitative information about the material of the object being imaged. In this paper we consider the multimaterial polyenergetic DBT model, and solve the nonlinear inverse problem with a limited memory BFGS quasi-Newton method. Regularization is enforced at each iteration using a diagonally modified approximation of the Hessian matrix, and by truncating the iterations.
Akhbari, Mahsa; Shamsollahi, Mohammad B; Jutten, Christian; Armoundas, Antonis A; Sayadi, Omid
2016-02-01
In this paper we propose an efficient method for denoising and extracting fiducial point (FP) of ECG signals. The method is based on a nonlinear dynamic model which uses Gaussian functions to model ECG waveforms. For estimating the model parameters, we use an extended Kalman filter (EKF). In this framework called EKF25, all the parameters of Gaussian functions as well as the ECG waveforms (P-wave, QRS complex and T-wave) in the ECG dynamical model, are considered as state variables. In this paper, the dynamic time warping method is used to estimate the nonlinear ECG phase observation. We compare this new approach with linear phase observation models. Using linear and nonlinear EKF25 for ECG denoising and nonlinear EKF25 for fiducial point extraction and ECG interval analysis are the main contributions of this paper. Performance comparison with other EKF-based techniques shows that the proposed method results in higher output SNR with an average SNR improvement of 12 dB for an input SNR of -8 dB. To evaluate the FP extraction performance, we compare the proposed method with a method based on partially collapsed Gibbs sampler and an established EKF-based method. The mean absolute error and the root mean square error of all FPs, across all databases are 14 ms and 22 ms, respectively, for our proposed method, with an advantage when using a nonlinear phase observation. These errors are significantly smaller than errors obtained with other methods. For ECG interval analysis, with an absolute mean error and a root mean square error of about 22 ms and 29 ms, the proposed method achieves better accuracy and smaller variability with respect to other methods.
Cannistraci, Carlo Vittorio
2015-01-26
Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet\\'s performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.
McDonald, Alison C; Sanei, Kia; Keir, Peter J
2013-06-01
Muscle force estimates are important for full understanding of the musculoskeletal system and EMG is a modeling method used to estimate muscle force. The purpose of this investigation was to examine the effect of high pass filtering and non-linear normalization on the EMG-force relationship of sub-maximal finger exertions. Sub-maximal isometric ramp exertions were performed under three conditions (i) extension with restraint at the mid-proximal phalanx, (ii) flexion at the proximal phalanx and (iii) flexion at the distal phalanx. Thirty high pass filter designs were compared to a standardized processing procedure and an exponential fit equation was used for non-linear normalization. High pass filtering significantly reduced the %RMS error and increased the peak cross correlation between EMG and force in the distal flexion condition and in the other two conditions there was a trend towards improving force predictions with high pass filtering. The degree of linearity differed between the three contraction conditions and high pass filtering improved the linearity in all conditions. Non-linear normalization had greater impact on the EMG-force relationship than high pass filtering. The difference in optimal processing parameters suggests that high pass filtering and linearity are dependent on contraction mode as well as the muscle analyzed.
Directory of Open Access Journals (Sweden)
Yin Hua
2015-04-01
Full Text Available Estimation of state of charge (SOC is of great importance for lithium-ion (Li-ion batteries used in electric vehicles. This paper presents a state of charge estimation method using nonlinear predictive filter (NPF and evaluates the proposed method on the lithium-ion batteries with different chemistries. Contrary to most conventional filters which usually assume a zero mean white Gaussian process noise, the advantage of NPF is that the process noise in NPF is treated as an unknown model error and determined as a part of the solution without any prior assumption, and it can take any statistical distribution form, which improves the estimation accuracy. In consideration of the model accuracy and computational complexity, a first-order equivalent circuit model is applied to characterize the battery behavior. The experimental test is conducted on the LiCoO2 and LiFePO4 battery cells to validate the proposed method. The results show that the NPF method is able to accurately estimate the battery SOC and has good robust performance to the different initial states for both cells. Furthermore, the comparison study between NPF and well-established extended Kalman filter for battery SOC estimation indicates that the proposed NPF method has better estimation accuracy and converges faster.
Bds/gps Integrated Positioning Method Research Based on Nonlinear Kalman Filtering
Ma, Y.; Yuan, W.; Sun, H.
2017-09-01
In order to realize fast and accurate BDS/GPS integrated positioning, it is necessary to overcome the adverse effects of signal attenuation, multipath effect and echo interference to ensure the result of continuous and accurate navigation and positioning. In this paper, pseudo-range positioning is used as the mathematical model. In the stage of data preprocessing, using precise and smooth carrier phase measurement value to promote the rough pseudo-range measurement value without ambiguity. At last, the Extended Kalman Filter(EKF), the Unscented Kalman Filter(UKF) and the Particle Filter(PF) algorithm are applied in the integrated positioning method for higher positioning accuracy. The experimental results show that the positioning accuracy of PF is the highest, and UKF is better than EKF.
Particle filter initialization in non-linear non-Gaussian radar target tracking
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
When particle filter is applied in radar target tracking,the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles,a new method called"competition strategy algorithm"is presented.In this method,initial measurements give birth to several particle groups around them,regularly.Each of the groups is tested several times,separately,in the beginning periods,and the group that has the most number of efficient particles is selected as the initial particles.For this method,sample initial particles selected are on the basis of several measurements instead of only one first measurement,which surely improves the accuracy of initial particles.The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greely improves the accuracy of initial particles,which makes the effect of filtering much better.
Directory of Open Access Journals (Sweden)
Umar Iqbal
2010-01-01
Full Text Available Present land vehicle navigation relies mostly on the Global Positioning System (GPS that may be interrupted or deteriorated in urban areas. In order to obtain continuous positioning services in all environments, GPS can be integrated with inertial sensors and vehicle odometer using Kalman filtering (KF. For car navigation, low-cost positioning solutions based on MEMS-based inertial sensors are utilized. To further reduce the cost, a reduced inertial sensor system (RISS consisting of only one gyroscope and speed measurement (obtained from the car odometer is integrated with GPS. The MEMS-based gyroscope measurement deteriorates over time due to different errors like the bias drift. These errors may lead to large azimuth errors and mitigating the azimuth errors requires robust modeling of both linear and nonlinear effects. Therefore, this paper presents a solution based on Parallel Cascade Identification (PCI module that models the azimuth errors and is augmented to KF. The proposed augmented KF-PCI method can handle both linear and nonlinear system errors as the linear parts of the errors are modeled inside the KF and the nonlinear and residual parts of the azimuth errors are modeled by PCI. The performance of this method is examined using road test experiments in a land vehicle.
Zeng, Nianyin; Wang, Zidong; Li, Yurong; Du, Min; Liu, Xiaohui
2011-07-01
In this paper, a mathematical model for sandwich-type lateral flow immunoassay is developed via short available time series. A nonlinear dynamic stochastic model is considered that consists of the biochemical reaction system equations and the observation equation. After specifying the model structure, we apply the extended Kalman filter (EKF) algorithm for identifying both the states and parameters of the nonlinear state-space model. It is shown that the EKF algorithm can accurately identify the parameters and also predict the system states in the nonlinear dynamic stochastic model through an iterative procedure by using a small number of observations. The identified mathematical model provides a powerful tool for testing the system hypotheses and also for inspecting the effects from various design parameters in both rapid and inexpensive way. Furthermore, by means of the established model, the dynamic changes in the concentration of antigens and antibodies can be predicted, thereby making it possible for us to analyze, optimize, and design the properties of lateral flow immunoassay devices. © 2011 IEEE
Analysis of Performance and Designing of Bi-Quad Filter using Hybrid Signed digit Number System
Directory of Open Access Journals (Sweden)
Sugandha Agarwal
2012-03-01
Full Text Available Speed of digital arithmetic processor depends mainly on the speed of adders. This paper provides a technique so that we can increase the speed of addition. Hybrid signed digit number representation perform addition in such a way that the carry propagation chain is limited to single digit position and hence are used to speed up arithmetic operation. Also hybrid signed digit reduces the critical path delay by parallelizing. Hybrid signed digit can be appropriate to use, when output is redundant representation.
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.
Kalman-median Compound Filter for Gaussian and Impulse Noise Reduction on Digital Images
山森, 一人; 山田, 義治; 相川, 勝
2013-01-01
This paper proposes an image restoration method from degraded images which include additive gaussian noise and impulse noise. This method tries to achieve image restoration by using combination of canonical state space model kalman filter and median filter. Kalman filter estimates internal state of a dynamic system based on system model. The canonical state space models are described by two equations; state equation that expresses a transition process of the region including the focusing pixe...
1986-04-01
disturbances. An optimal Kalman filtering approach was found to be impractical [2]. However, additional research showed that the .. optimal filter...Evans, R.J. - "Application of Fast Fourier Transforms to Sinusoidal Disturbance Rejection and its -. , Relationship to Kalman Filtering". University of...1206 .......... F% .9 REQUEHCY Hz Fiue9 Feunc epneo Csae oc Filtr fo ALPA=0975 nd d-0.1 I. %.0. .2
Raffensperger, Jeff P.; Baker, Anna C.; Blomquist, Joel D.; Hopple, Jessica A.
2017-06-26
Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point.Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased
基于 MATLAB GUI的 IIR 数字滤波器平台设计%The Platform Design of IIR Digital Filter Based on MATLAB GUI
Institute of Scientific and Technical Information of China (English)
2015-01-01
Combining with the research of digital filter in the digital signal processing′s theory,it analyzed the typical design methods of IIR digital filter ,built digital filter design model ,and used MATLAB to sim-ulate the design methods of IIR digital filter in this paper .It designed the interactive platform of IIR digit-al filter in MATLAB GUI graphical program environment ,which can design filter′s specifications accord-ing to the actual tasks required , compare and analyze the frequency characteristics of analog and digital filters.Through the reading datas ,analyzing the amplitudes and the choice of filter the filting that can real-ize of the actual sample signals .%结合数字信号处理理论中对数字滤波器的研究，分析IIR数字滤波器的典型设计方法，建立数字滤波器设计模型，并利用MATLAB软件对IIR数字滤波器设计方法进行仿真。同时，在MATLAB GUI图形界面编程环境下设计IIR数字滤波器交互式平台，该平台可根据实际任务需要来设计滤波器的技术指标，对比分析模拟滤波器和数字滤波器的频率特性，同时通过数据读取、幅值分析以及滤波器的选择实现对实际样本信号的滤波功能。
Nonlinear Control of Back-to-Back VSC-HVDC System via Command-Filter Backstepping
Directory of Open Access Journals (Sweden)
Jie Huang
2017-01-01
Full Text Available This paper proposed a command-filtered backstepping controller to improve the dynamic performance of back-to-back voltage-source-converter high voltage direct current (BTB VSC-HVDC. First, the principle and model of BTB VSC-HVDC in abc and d-q frame are described. Then, backstepping method is applied to design a controller to maintain the voltage balance and realize coordinated control of active and reactive power. Meanwhile, command filter is introduced to deal with the problem of input saturation and explosion of complexity in conventional backstepping, and a filter compensation signal is designed to diminish the adverse effects caused by the command filter. Next, the stability and convergence of the whole system are proved via the Lyapunov theorem of asymptotic stability. Finally, simulation results are given to demonstrate that proposed controller has a better dynamic performance and stronger robustness compared to the traditional PID algorithm, which also proves the effectiveness and possibility of the designed controller.
On Power Factor Improvement by Lossless Linear Filters under Nonlinear Nonsinusoidal Conditions
Puerto-Flores, D. del; Ortega, R.; Scherpen, J.M.A.
2011-01-01
Recently, it has been established that the problem of power factor compensation for nonlinear loads with nonsinusoidal source voltage can be recast in terms of the property of cyclodissipativity. The purpose of this brief note is to review and to illustrate the application of this framework to the p
Directory of Open Access Journals (Sweden)
Carlos Pozo
Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study
Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano
2012-01-01
Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the
Azoug, Seif Eddine; Bouguezel, Saad
2016-01-01
In this paper, a novel opto-digital image encryption technique is proposed by introducing a new non-linear preprocessing and using the multiple-parameter discrete fractional Fourier transform (MPDFrFT). The non-linear preprocessing is performed digitally on the input image in the spatial domain using a piecewise linear chaotic map (PLCM) coupled with the bitwise exclusive OR (XOR). The resulting image is multiplied by a random phase mask before applying the MPDFrFT to whiten the image. Then, a chaotic permutation is performed on the output of the MPDFrFT using another PLCM different from the one used in the spatial domain. Finally, another MPDFrFT is applied to obtain the encrypted image. The parameters of the PLCMs together with the multiple fractional orders of the MPDFrFTs constitute the secret key for the proposed cryptosystem. Computer simulation results and security analysis are presented to show the robustness of the proposed opto-digital image encryption technique and the great importance of the new non-linear preprocessing introduced to enhance the security of the cryptosystem and overcome the problem of linearity encountered in the existing permutation-based opto-digital image encryption schemes.
Big Bang–Big Crunch Optimization Algorithm for Linear Phase Fir Digital Filter Design
Directory of Open Access Journals (Sweden)
Ms. Rashmi Singh Dr. H. K. Verma
2012-02-01
Full Text Available The Big Bang–Big Crunch (BB–BC optimization algorithm is a new optimization method that relies on the Big Bang and Big Crunch theory, one of the theories of the evolution of the universe. In this paper, a Big Bang–Big Crunch algorithm has been used here for the design of linear phase finite impulse response (FIR filters. Here the experimented fitness function based on the mean squared error between the actual and the ideal filter response. This paper presents the plot of magnitude response of FIR filters and error graph. The BB-BC seems to be promising tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance.
Optimisation of digital noise filtering in the deconvolution of ultrafast kinetic data
Energy Technology Data Exchange (ETDEWEB)
Banyasz, Akos [Department of Physical Chemistry, Eoetvoes University, P.O. Box. 32, H-1518 Budapest 112 (Hungary); Dancs, Gabor [Department of Physical Chemistry, Eoetvoes University, P.O. Box. 32, H-1518 Budapest 112 (Hungary); Keszei, Erno [Department of Physical Chemistry, Eoetvoes University, P.O. Box. 32, H-1518 Budapest 112 (Hungary)]. E-mail: keszei@chem.elte.hu
2005-11-01
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.
Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models
Directory of Open Access Journals (Sweden)
Xiangyun Hu
2015-08-01
Full Text Available Automatic extraction of ground points, called filtering, is an essential step in producing Digital Terrain Models from airborne LiDAR data. Scene complexity and computational performance are two major problems that should be addressed in filtering, especially when processing large point cloud data with diverse scenes. This paper proposes a fast and intelligent algorithm called Semi-Global Filtering (SGF. The SGF models the filtering as a labeling problem in which the labels correspond to possible height levels. A novel energy function balanced by adaptive ground saliency is employed to adapt to steep slopes, discontinuous terrains, and complex objects. Semi-global optimization is used to determine labels that minimize the energy. These labels form an optimal classification surface based on which the points are classified as either ground or non-ground. The experimental results show that the SGF algorithm is very efficient and able to produce high classification accuracy. Given that the major procedure of semi-global optimization using dynamic programming is conducted independently along eight directions, SGF can also be paralleled and sped up via Graphic Processing Unit computing, which runs at a speed of approximately 3 million points per second.
Ito, Yuji; Doki, Shinji; Okuma, Sigeru
1-bit signal processing based on delta-sigma modulation has been studied for hardware implementation of signal processng systems. In the 1-bit signal processing, finite word-length problems such as overflow and coefficent quantization error occur. To solve the problems, new design method with state space is proposed in this paper. Digital filters are designed to show the feasibility of the method. Firstly, L1/L2-sensitivity is shown to evaluate coefficient quantization error and L2 scaling constraints to prevent overflow. Secondly, state space equation is shown and L1/L2-sensitivity and L2-scaling constraints are extended to take filter structure and oversampling effects into account. Finally, the proposed method is shown to attain higher SNR than conventional ones.
LDI数字椭圆滤波器的设计%Design of LDI elliptical digital filter
Institute of Scientific and Technical Information of China (English)
郑亚民
2004-01-01
介绍了一种设计Lessloss Discrete Integrator(LDI)椭圆型Digital Filter(DF)的方法.即利用椭圆型Analog Filter(AF)作为原型,找出元件的双线性变换(BLT)和LDI变换之间的关系进行预补偿,再进行信号流图的等效变换.最后用LDI变换作为电路的基本模块,去实现双线性变换的椭圆传递函数.以此方法设计出一个低通LDI数字椭圆滤波器,并利用MATLAB/SIMULINK导出滤波器的传递函数,大大简化了整个设计过程.
Accurate 3D maps from depth images and motion sensors via nonlinear Kalman filtering
Hervier, Thibault; Goulette, François
2012-01-01
This paper investigates the use of depth images as localisation sensors for 3D map building. The localisation information is derived from the 3D data thanks to the ICP (Iterative Closest Point) algorithm. The covariance of the ICP, and thus of the localization error, is analysed, and described by a Fisher Information Matrix. It is advocated this error can be much reduced if the data is fused with measurements from other motion sensors, or even with prior knowledge on the motion. The data fusion is performed by a recently introduced specific extended Kalman filter, the so-called Invariant EKF, and is directly based on the estimated covariance of the ICP. The resulting filter is very natural, and is proved to possess strong properties. Experiments with a Kinect sensor and a three-axis gyroscope prove clear improvement in the accuracy of the localization, and thus in the accuracy of the built 3D map.
Spatial filtering for zero-order and twin-image elimination in digital off-axis holography.
Cuche, E; Marquet, P; Depeursinge, C
2000-08-10
Off-axis holograms recorded with a CCD camera are numerically reconstructed with a calculation of scalar diffraction in the Fresnel approximation. We show that the zero order of diffraction and the twin image can be digitally eliminated by means of filtering their associated spatial frequencies in the computed Fourier transform of the hologram. We show that this operation enhances the contrast of the reconstructed images and reduces the noise produced by parasitic reflections reaching the hologram plane with an incidence angle other than that of the object wave.
Directory of Open Access Journals (Sweden)
Chen Xiong
2016-01-01
Full Text Available Although the structured light system that uses digital fringe projection has been widely implemented in three-dimensional surface profile measurement, the measurement system is susceptible to non-linear error. In this work, we propose a convenient look-up-table-based (LUT-based method to compensate for the non-linear error in captured fringe patterns. Without extra calibration, this LUT-based method completely utilizes the captured fringe pattern by recording the full-field differences. Then, a phase compensation map is established to revise the measured phase. Experimental results demonstrate that this method works effectively.
Self-tuning control with a filter and a neural compensator for a class of nonlinear systems.
Fu, Yue; Chai, Tianyou
2013-05-01
Considering the mismatching of model-process order, in this brief, a self-tuning proportional-integral-derivative (PID)-like controller is proposed by combining a pole assignment self-tuning PID controller with a filter and a neural compensator. To design the PID controller, a reduced order model is introduced, whose linear parameters are identified by a normalized projection algorithm with a deadzone. The higher order nonlinearity is estimated by a high order neural network. The gains of the PID controller are obtained by pole assignment, which together with other parameters are tuned on-line. The bounded-input bounded-output stability condition and convergence condition of the closed-loop system are presented. Simulations are conducted on the continuous stirred tank reactors system. The results show the effectiveness of the proposed method.
Nonlinear tracking in a diffusion process with a Bayesian filter and the finite element method
DEFF Research Database (Denmark)
Pedersen, Martin Wæver; Thygesen, Uffe Høgsbro; Madsen, Henrik
2011-01-01
A new approach to nonlinear state estimation and object tracking from indirect observations of a continuous time process is examined. Stochastic differential equations (SDEs) are employed to model the dynamics of the unobservable state. Tracking problems in the plane subject to boundaries...... become complicated using SMC because Monte Carlo randomness is introduced. The finite element (FE) method solves the Kolmogorov equations of the SDE numerically on a triangular unstructured mesh for which boundary conditions to the state-space are simple to incorporate. The FE approach to nonlinear state...... estimation is suited for off-line data analysis because the computed smoothed state densities, maximum a posteriori parameter estimates and state sequence are deterministic conditional on the finite element mesh and the observations. The proposed method is conceptually similar to existing point...
Becis-Aubry, Yasmina; Boutayeb, Mohamed; Darouach, Mohamed
2006-01-01
International audience; This contribution proposes a recursive and easily implementable online algorithm for state estimation of multi-output discrete-time systems with nonlinear dynamics and linear measurements in presence of unknown but bounded disturbances corrupting both the state and measurement equations. The proposed algorithm is based on state bounding techniques and is decomposed into two steps : time update and observation update that uses a switching estimation Kalman-like gain mat...
Cusenza, Monica; Accardo, Agostino; Monti, Fabrizio; Bramanti, Placido
2010-01-01
Simultaneous EEG-fMRI is a powerful emerging tool in functional neuroimaging that exploits the relationship between neuronal electrophysiological activity and its hemodynamic response. It has found application in the study of both spontaneous and evoked brain activity. Combining the complementary advantages of the two techniques it provides a measurement with high temporal and spatial resolution, allowing a reliable localization of event generators. However, EEG data recorded inside MRI scanner are heavily corrupted by different types of artifacts due to the interactions between the patient, EEG electrodes wires and the magnetic fields inside the scanner. In particular, gradient switching and RF pulses, necessary to acquire fMRI data, generate large artifacts that can completely obscure EEG signals. Many methods have been proposed to eliminate or at least reduce gradient artifact. In this paper both a qualitative and a quantitative evaluation of two different algorithms used for gradient artifact removal are presented. Linear and non-linear characteristics of EEG, such as power spectra, fractal dimension and beta scaling exponent, are evaluated for EEGs recorded outside and inside the scanner, in MR static and dynamic conditions. The study highlights how residual artifacts after correction and artifacts induced by correction itself could still considerably affect EEG signals. The results suggest that the quality of both these gradient artifact filtering methods is not yet sufficient to preserve EEG characteristics and thus it must be further improved. The aim of this study is to make neurophysiologists aware of the filtering effects that can compromise linear and non-linear analysis of EEG recorded during functional MRI.
Krcmarík, David; Slavík, Radan; Park, Yongwoo; Azaña, José
2009-04-27
tract: We demonstrate high quality pulse compression at high repetition rates by use of spectral broadening of short parabolic-like pulses in a normally-dispersive highly nonlinear fiber (HNLF) followed by linear dispersion compensation with a conventional SMF-28 fiber. The key contribution of this work is on the use of a simple and efficient long-period fiber grating (LPFG) filter for synthesizing the desired parabolic-like pulses from sech(2)-like input optical pulses; this all-fiber low-loss filter enables reducing significantly the required input pulse power as compared with the use of previous all-fiber pulse re-shaping solutions (e.g. fiber Bragg gratings). A detailed numerical analysis has been performed in order to optimize the system's performance, including investigation of the optimal initial pulse shape to be launched into the HNLF fiber. We found that the pulse shape launched into the HNLF is critically important for suppressing the undesired wave breaking in the nonlinear spectral broadening process. The optimal shape is found to be independent on the parameters of normally dispersive HNLFs. In our experiments, 1.5-ps pulses emitted by a 10-GHz mode-locked laser are first reshaped into 3.2-ps parabolic-like pulses using our LPFG-based pulse reshaper. Flat spectrum broadening of the amplified initial parabolic-like pulses has been generated using propagation through a commercially-available HNLF. Pulses of 260 fs duration with satellite peak and pedestal suppression greater than 17 dB have been obtained after the linear dispersion compensation fiber. The generated pulses exhibit a 20-nm wide supercontinuum energy spectrum that has almost a square-like spectral profile with >85% of the pulse energy contained in its FWHM spectral bandwidth.
Error compensation on precision machine tool servo control system based on digital concave filter
Institute of Scientific and Technical Information of China (English)
王立松; 苏宝库; 张晶; 董申
2001-01-01
It is concluded from the results of testing the frequency characteristics of the sub-micron precision machine tool servo control system, that the existence of several oscillating modalities is the main factor that affects the performance of the control system. To compensate for this effect, several concave filters are utilized in the system to improve the control accuracy. The feasibility of compensating for several oscillating modalities with a single concave filter is also studied. By applying a modified Butterworth concave filter to the practical system, the maximum stable state output error remains under + 10 nm in the closed-loop positioning system.
Polyphase Filter Banks for Embedded Sample Rate Changes in Digital Radio Front-Ends
DEFF Research Database (Denmark)
Awan, Mehmood-Ur-Rehman; Le Moullec, Yannick; Koch, Peter
2011-01-01
This paper presents efficient processing engines for software-defined radio (SDR) front-ends. These engines, based on a polyphase channelizer, perform arbitrary sample-rate changes, frequency selection, and bandwidth control. This paper presents an M-path polyphase filter bank based on a modified N......-path polyphase filter. Such a system allows resampling by arbitrary ratios while performing baseband aliasing from center frequencies at Nyquist zones that are not multiples of the output sample rate. This resampling technique is based on sliding cyclic data load interacting with cyclic-shifted coefficients....... A non-maximally-decimated polyphase filter bank (where the number of data loads is not equal to the number of M subfilters) processes M subfilters in a time period that is less than or greater than the M data loads. A polyphase filter bank with five different resampling modes is used as a case study...
Detection and Cancellation of Jamming Signal Noise Using Digital Filters for Radar Applications
2013-01-01
This paper considers the problem of detecting and classifying a radar target signal from a jamming signal produced from a target jammer source. Jamming is intentional emission of radio frequency signals to interfere with the operation of a radar by saturating its receiver with noise or false information. In order to distill the features of radar echo-signal affected by strong jamming noise, the adaptive filters are used to remove the noise and recover the radar echo-signal. An Adaptive filter...
He, Tiancheng; Xue, Zhong; Alvarado, Miguel Valdivia y.; Wong, Kelvin K.; Xie, Weixin; Wong, Stephen T. C.
2013-01-01
Fluorescence microendoscopy can potentially be a powerful modality in minimally invasive percutaneous intervention for cancer diagnosis because it has an exceptional ability to provide micron-scale resolution images in tissues inaccessible to traditional microscopy. After targeting the tumor with guidance by macroscopic images such as computed tomorgraphy or magnetic resonance imaging, fluorescence microendoscopy can help select the biopsy spots or perform an on-site molecular imaging diagnosis. However, one challenge of this technique for percutaneous lung intervention is that the respiratory and hemokinesis motion often renders instability of the sequential image visualization and results in inaccurate quantitative measurement. Motion correction on such serial microscopy image sequences is, therefore, an important post-processing step. We propose a nonlinear motion compensation algorithm using a cubature Kalman filter (NMC-CKF) to correct these periodic spatial and intensity changes, and validate the algorithm using preclinical imaging experiments. The algorithm integrates a longitudinal nonlinear system model using the CKF in the serial image registration algorithm for robust estimation of the longitudinal movements. Experiments were carried out using simulated and real microendoscopy videos captured from the CellVizio 660 system in rabbit VX2 cancer intervention. The results show that the NMC-CKF algorithm yields more robust and accurate alignment results.
Energy Technology Data Exchange (ETDEWEB)
Paixao, L.; Oliveira, B. B.; Nogueira, M. do S. [Centro de Desenvolvimento da Tecnologia Nuclear, Post-graduation in Science and Technology of Radiations, Minerals and Materials, Pte. Antonio Carlos 6.627, Pampulha, 31270-901 Belo Horizonte (Brazil); Viloria, C. [UFMG, Departamento de Engenharia Nuclear, Post-graduation in Nuclear Sciences and Techniques, Pte. Antonio Carlos 6.627, Pampulha, 31270-901 Belo Horizonte (Brazil); Alves de O, M. [UFMG, Department of Anatomy and Imaging, Prof. Alfredo Balena 190, 30130-100 Belo Horizonte (Brazil); Araujo T, M. H., E-mail: lpr@cdtn.br [Dr Maria Helena Araujo Teixeira Clinic, Guajajaras 40, 30180-100 Belo Horizonte (Brazil)
2014-08-15
It is widely accepted that the mean glandular dose (D{sub G}) for the glandular tissue is the more useful magnitude for characterizing the breast cancer risk. The procedure to estimate the D{sub G}, for being difficult to measure it directly in the breast, it is to make the use of conversion factors that relate incident air kerma (K{sub i}) at this dose. Generally, the conversion factors vary with the x-ray spectrum half-value layer and the breast composition and thickness. Several authors through computer simulations have calculated such factors by the Monte Carlo (Mc) method. Many spectral models for D{sub G} computer simulations purposes are available in the diagnostic range. One of the models available generates unfiltered spectra. In this work, the Monte Carlo EGSnrc code package with the C++ class library (eg spp) was employed to derive filtered tungsten x-ray spectra used in digital mammography systems. Filtered spectra for rhodium and aluminium filters were obtained for tube potentials between 26 and 32 kV. The half-value layer of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F and Mam Detector Platinum and 8201023-C Xi Base unit Platinum Plus w m As in a Hologic Selenia Dimensions system using a Direct Radiography mode. Calculated half-value layer values showed good agreement compared to those obtained experimentally. These results show that the filtered tungsten anode x-ray spectra and the EGSnrc Mc code can be used for D{sub G} determination in mammography. (Author)
Duifhuis, H
This letter concerns the paper "An approximate transfer function for the dual-resonance nonlinear filter model of auditory frequency selectivity" [E. A. Lopez-Poveda, J. Acoust. Soc. Am. 114, 2112-2117 (2003)]. It proposes a correction of the historical framework in which the paper is presented.
Electromagnetic bandgap (EBG) structures common mode filters for high speed digital systems
Orlandi, Antonio; De Paulis, Francesco; Connor, Samuel
2017-01-01
Digital Services in the 21st Century provides a holistic approach to understanding telecommunications by addressing the emergence and dominance of new digital services, consumer and economic dynamics, and the creation of content by service providers. The authors cover the main products and services that are provided by telecommunications operators (in general information and communication technologies providers). Key topics discussed include enriched communications, fixed and mobile broadband, financial services for unbanked customers in emerging markets, Pay TV, data communications for machines, and digital home. As opposed to technical-driven textbooks, this book also addresses customer demand and the competitive nature between telecommunications operators and Internet providers that compete to provide compelling services.
Nonlinear dynamic positioning of ships with gain-scheduled wave filtering
DEFF Research Database (Denmark)
Torsetnes, Guttorm; Jouffroy, Jerome; Fossen, Thor I.
This paper presents a globally contracting controller for regulation and dynamic positioning of ships, using only position measurements. For this purpose a globally contracting observer which reconstructs the unmeasured states is constructed. The observer produces accurate estimates of position......, slowly varying environmental disturbances (bias terms) and velocity. The estimates are automatically adjusted to the present sea state by gain-scheduling the wave model parameters in the observer. Finally, the estimates are used in a nonlinear PID control law and the stability proof of the observer...
Chaos synchronization in noisy environment using nonlinear filtering and sliding mode control
Energy Technology Data Exchange (ETDEWEB)
Behzad, Mehdi [Center of Excellence in Design, Robotics, and Automation (CEDRA), Department of Mechanical Engineering, Sharif University of Technology, Postal Code 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: m_behzad@sharif.edu; Salarieh, Hassan [Center of Excellence in Design, Robotics, and Automation (CEDRA), Department of Mechanical Engineering, Sharif University of Technology, Postal Code 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics, and Automation (CEDRA), Department of Mechanical Engineering, Sharif University of Technology, Postal Code 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu
2008-06-15
This paper presents an algorithm for synchronizing two different chaotic systems, using a combination of the extended Kalman filter and the sliding mode controller. It is assumed that the drive chaotic system has a random excitation with a stochastically chaotic behavior. Two different cases are considered in this study. At first it is assumed that all state variables of the drive system are available, i.e. complete state measurement, and a sliding mode controller is designed for synchronization. For the second case, it is assumed that the output of the drive system does not contain the whole state variables of the drive system, and it is also affected by some random noise. By combination of extended Kalman filter and the sliding mode control, a synchronizing control law is proposed. As a case study, the presented algorithm is applied to the Lur'e-Genesio chaotic systems as the drive-response dynamic systems. Simulation results show the good performance of the algorithm in synchronizing the chaotic systems in presence of noisy environment.
Rigatos, Gerasimos
2014-12-01
A synchronizing control scheme for coupled neural oscillators of the FitzHugh-Nagumo type is proposed. Using differential flatness theory the dynamical model of two coupled neural oscillators is transformed into an equivalent model in the linear canonical (Brunovsky) form. A similar linearized description is succeeded using differential geometry methods and the computation of Lie derivatives. For such a model it becomes possible to design a state feedback controller that assures the synchronization of the membrane's voltage variations for the two neurons. To compensate for disturbances that affect the neurons' model as well as for parametric uncertainties and variations a disturbance observer is designed based on Kalman Filtering. This consists of implementation of the standard Kalman Filter recursion on the linearized equivalent model of the coupled neurons and computation of state and disturbance estimates using the diffeomorphism (relations about state variables transformation) provided by differential flatness theory. After estimating the disturbance terms in the neurons' model their compensation becomes possible. The performance of the synchronization control loop is tested through simulation experiments.
Bianco, Vittorio; Memmolo, Pasquale; Paturzo, Melania; Finizio, Andrea; Ferraro, Pietro
2017-06-01
In digital holography (DH), the coherent nature of the employed light sources severely degrades the holographic reconstructions due to a mixture of speckle and incoherent additive noise. These can affect both the visual quality in holographic imaging and display, and the accuracy of quantitative phase-contrast reconstructions. Typically, the noise problem is tackled by reducing the illumination coherence, thus the most intuitive way involves the recording of multiple uncorrelated holograms to be incoherently combined. This framework is known as Multi-Look DH (MLDH). However, single shot recordings are highly desirable in DH, and numerical methods are required to go beyond the improvement bound of ML techniques. Among the existing image processing methods, the 3D Block Matching filtering (BM3D) has shown the best performance. Here we present the MLDH-BM3D, a method specifically suitable to filter DH images that combines the two aforementioned strategies to overcome their respective limitations. We demonstrate the effectiveness of this framework in three different experimental situations, i.e. reconstructions of single wavelength holograms and color holograms in the visible region and the challenging case of the Infrared Radiation Digital Holography (IRDH) reconstructions, where a very severe noise degradation occurs.
基于Matlab的IIR数字滤波器的设计%Design of IIR Digital Filter Based on Matlab
Institute of Scientific and Technical Information of China (English)
刘雪; 葛良全
2014-01-01
数字滤波器可靠性与精确度高，使用简单方便，与模拟设备相比具有许多其所没有的诸多优点，已经被泛地应用于各个科学技术领域。Matlab具有强大的数据处理功能，丰富的工具箱为工程计算提供的极大的方便，也已被广泛地应用于工程计算中。该文基于Matlab提出了IIR滤波器的设计方案与相关应用。%Digital filter possesses high level of accuracy, agility, and reliability. It has lots of advantages that analog equipment doesn’t have, so it has been widely used in any branch of science and technology. Matlab has powerful data processing capability, its rich tool kit offers extreme convenience for project calculation, So it also been widely used in the project calculation field. This paper presents design plan and relevant implement of IIR digital filter which based on Matlab.
Estimation and filtering of nonlinear systems application to a waste-water treatment process
Energy Technology Data Exchange (ETDEWEB)
Ben Youssef, C.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France). Lab. d`Automatique et d`Analyse des Systemes]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France); Zeng, F.Y.; Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1994-04-01
A fundamental task in design and control of biotechnological processes is system modelling. This task is made difficult by the scarceness of on-line direct sensors for some key variables and by the fact that identifiability of models including Michaelis-Menten type of nonlinearities is not straightforward. The use of adaptive estimation approaches constitutes an interesting alternative to circumvent these kind of problems. This paper discusses an identification technique derived to solve the problem of estimating simultaneously inaccessible state variables and time-varying parameters of a nonlinear wastewater treatment process. An extended linearization technique using Kronecker`s calculation provides the error model of the joint observer-estimator procedure which convergence is proved via Lyapunov`s method. Sufficient conditions for stability of this joint identification scheme are given and discussed according to the persistence excitation conditions of the signals. A simulation study with measurement noises and abrupt jumps of the process parameters shows the feasibility and significant robustness of the proposed adaptive estimation methodologies. (author). (author). 10 refs., 3 figs.
A novel low-complexity digital filter design for wearable ECG devices.
Asgari, Shadnaz; Mehrnia, Alireza
2017-01-01
Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.
Directory of Open Access Journals (Sweden)
I. Sharma
2016-09-01
Full Text Available In this paper, a linear phase FIR filter is designed through recently proposed nature inspired optimization algorithm known as Cuckoo search (CS. A comparative study of Cuckoo search (CS, particle swarm optimization (PSO and artificial bee colony (ABC nature inspired optimization methods in the field of linear phase FIR filter design is also presented. For this purpose, an improved L1 weighted error function is formulated in frequency domain, and minimized through CS, PSO and ABC respectively. The error or objective function has a controlling parameter wt which controls the amount of ripple in the desired band of frequency. The performance of FIR filter is examined through three key parameters; Maximum Pass Band Ripple (MPR, Maximum Stopband Ripple (MSR and Stopband Attenuation (As. Comparative study and the simulation results reveal that the designed filter with CS gives better performance in terms of Maximum Stopband Ripple (MSR, and Stopband Attenuation (As for low order filter design, and for higher order it also gives better performance in term of Maximum Passband Ripple (MPR. Superiority of the proposed technique is also shown through comparison with other recently proposed methods.
Urban and Indoor Weak Signal Tracking Using an Array Tracker with MVA and Nonlinear Filtering
Directory of Open Access Journals (Sweden)
Jicheng Ding
2014-01-01
Full Text Available We focus on the need for weak GPS signal tracking technique at a receiver powered on in urban or indoor environment; the tracking loop is unlocked and data bit edge position is unknown. A modified Viterbi algorithm (MVA based on dynamic programming is developed and it is applied to GPS bit synchronization to improve bit edge position detection probability. Meanwhile, two combination carrier tracking schemes based on central difference Kalman filter (CDKF and MVA module are designed for tracking very weak GPS signal. The testing results indicate that the methods can successfully detect bit edge position with high detection probability whether or not the tracking loop is locked. The tested combination tracking scheme is still able to work well when the signal quality deteriorates to 20 dB-Hz without additional large store space.
A Novel Front-End ASIC With Post Digital Filtering and Calibration for CZT-Based PET Detector
Energy Technology Data Exchange (ETDEWEB)
Gao, W.; Yin, J.; Li, C.; Zeng, H.; Gao, D. [Institute of Microelectronics, School of Computer Science and Techonology, Northwestern Polytechnical University, Xi' an (China); Hu, Y. [Institut Pluridiscipline Hubert Curien, CNRS/UDS/IN2P3, Strasbourg (France)
2015-07-01
This paper presents a novel front-end electronics based on a front-end ASIC with post digital filtering and calibration dedicated to CZT detectors for PET imaging. A cascade amplifier based on split-leg topology is selected to realize the charge-sensitive amplifier (CSA) for the sake of low noise performances and the simple scheme of the power supplies. The output of the CSA is connected to a variable-gain amplifier to generate the compatible signals for the A/D conversion. A multi-channel single-slope ADC is designed to sample multiple points for the digital filtering and shaping. The digital signal processing algorithms are implemented by a FPGA. To verify the proposed scheme, a front-end readout prototype ASIC is designed and implemented in 0.35 μm CMOS process. In a single readout channel, a CSA, a VGA, a 10-bit ADC and registers are integrated. Two dummy channels, bias circuits, and time controller are also integrated. The die size is 2.0 mm x 2.1 mm. The input range of the ASIC is from 2000 e{sup -} to 100000 e{sup -}, which is suitable for the detection of the X-and gamma ray from 11.2 keV to 550 keV. The linearity of the output voltage is less than 1 %. The gain of the readout channel is 40.2 V/pC. The static power dissipation is about 10 mW/channel. The above tested results show that the electrical performances of the ASIC can well satisfy PET imaging applications. (authors)
Multidimensional Systolic Arrays of LMS AlgorithmAdaptive (FIR Digital Filters
Directory of Open Access Journals (Sweden)
Bakir A. R. Al-Hashemy
2009-01-01
Full Text Available A multidimensional systolic arrays realization of LMS algorithm by a method of mapping regular algorithm onto processor array, are designed. They are based on appropriately selected 1-D systolic array filter that depends on the inner product sum systolic implementation. Various arrays may be derived that exhibit a regular arrangement of the cells (processors and local interconnection pattern, which are important for VLSI implementation. It reduces latency time and increases the throughput rate in comparison to classical 1-D systolic arrays. The 3-D multilayered array consists of 2-D layers, which are connected with each other only by edges. Such arrays for LMS-based adaptive (FIR filter may be opposed the fundamental requirements of fast convergence rate in most adaptive filter applications.
Gamadia, Mark Noel
In order to gain valuable market share in the growing consumer digital still camera and camera phone market, camera manufacturers have to continually add and improve existing features to their latest product offerings. Auto-focus (AF) is one such feature, whose aim is to enable consumers to quickly take sharply focused pictures with little or no manual intervention in adjusting the camera's focus lens. While AF has been a standard feature in digital still and cell-phone cameras, consumers often complain about their cameras' slow AF performance, which may lead to missed photographic opportunities, rendering valuable moments and events with undesired out-of-focus pictures. This dissertation addresses this critical issue to advance the state-of-the-art in the digital band-pass filter, passive AF method. This method is widely used to realize AF in the camera industry, where a focus actuator is adjusted via a search algorithm to locate the in-focus position by maximizing a sharpness measure extracted from a particular frequency band of the incoming image of the scene. There are no known systematic methods for automatically deriving the parameters such as the digital pass-bands or the search step-size increments used in existing passive AF schemes. Conventional methods require time consuming experimentation and tuning in order to arrive at a set of parameters which balance AF performance in terms of speed and accuracy ultimately causing a delay in product time-to-market. This dissertation presents a new framework for determining an optimal set of passive AF parameters, named Filter- Switching AF, providing an automatic approach to achieve superior AF performance, both in good and low lighting conditions based on the following performance measures (metrics): speed (total number of iterations), accuracy (offset from truth), power consumption (total distance moved), and user experience (in-focus position overrun). Performance results using three different prototype cameras
A digital algorithm for spectral deconvolution with noise filtering and peak picking: NOFIPP-DECON
Edwards, T. R.; Settle, G. L.; Knight, R. D.
1975-01-01
Noise-filtering, peak-picking deconvolution software incorporates multiple convoluted convolute integers and multiparameter optimization pattern search. The two theories are described and three aspects of the software package are discussed in detail. Noise-filtering deconvolution was applied to a number of experimental cases ranging from noisy, nondispersive X-ray analyzer data to very noisy photoelectric polarimeter data. Comparisons were made with published infrared data, and a man-machine interactive language has evolved for assisting in very difficult cases. A modified version of the program is being used for routine preprocessing of mass spectral and gas chromatographic data.
Nonlinear compensation research and simulation of bandlimited QPSK digital satellite channels
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Presents a phase compensation against the signal distortion mainly caused by TWTA to solve the problem of compensation and modelling of a nonlinear QPSK satellite channel assumed to be bandlimited and exhibit both ampli tude and phase nonlinearities, and to lower the bit error probability of nonlinear channel, and concludes with simula tion results that the compensation against phase distortion of TWTA can significantly improve the nonlinear performance of the channel.
基于System Generator的数字音频滤波器设计%Design of Digital Audio Filter Based on System Generator
Institute of Scientific and Technical Information of China (English)
2013-01-01
为了解决传统固定系数滤波器不能处理无法预知信号和噪声特性，提出一种基于 System Generator 的音频数字滤波器的设计方案。介绍了自适应滤波器基本原理及算法，采用LMS算法并利用System Generator构建了滤波器仿真模型。仿真结果证明：经过自适应滤波器的处理后，可较好地滤除信号中的噪声；该方法设计的滤波器有效地实现了对音频信号的自适应滤波，滤波效果良好。%In order to solve the problems of traditional digital filter with fixed coefficient that can’t process unknown noise of audio signal, this paper put forwards a design scheme of digital audio filter based on System Generator. The principle and algorithm of adaptive filter are introduced, and simulation model of filter is constructed using LMS algorithm by System Generator. The simulation result shows that noise signal can be filtered after processing of adaptive filter, the filter based on design scheme can realize adaptive filter for audio signal and achieve great effect.
Processor for high-density digital tape-recorded signals
Ashlock, J. C.
1973-01-01
Linear filter and detection theory can bear on problem of reconstructing recorded bit stream. Problem can be taken from realm of nonlinear problems even though basic record process is still recognized as highly nonlinear. Digital tape recorder can be modeled as particular type of linear communication channel with intersymbol interference.
Institute of Scientific and Technical Information of China (English)
龚轲; 张东彦; 黄明
2011-01-01
In the realm of software radio,the module often used is digital filter.Digital filters are made by digital multipliers,adders and delay units composed of an algorithm or device.Digital filter function is the discrete signal input digital signal processing operations in order to achieve the purpose of changing the signal spectrum.This article uses the Matlab System Generator under the sine wave signal generation, and adding Gaussian white noise,the signal is filtered through a variety of digital filters,then download System Generator to generate the FPGA,the signal output through the DA,the last observed in the output waveform on the oscilloscope.%数字滤波器的功能是对输入离散的数字信号进行运算处理，以达到改变信号频谱的目的。System Generator是基于定点的仿真系统。的本设计内容全部基于System Generator。首先由DDS（Direct Digital Synthesizer数字信号发生器）生成正弦波信号，之后加入高斯白噪声，将信号通过两种结构的数字滤波器进行滤波，随后将程序下载至FPGA中，通过DA将信号输出，最后在比较两种滤波器的在硬件平台上的实际性能以及消耗资源情况。
Wijayaratna, Sewwandi; Madanayake, Arjuna; Beall, Brandon D.; Bruton, Len T.
2014-05-01
Real-time digital implementation of three-dimensional (3-D) infinite impulse response (IIR) beam filters are discussed. The 3-D IIR filter building blocks have filter coefficients, which are defined using algebraic closed-form expressions that are functions of desired beam personalities, such as the look-direction of the aperture, the bandwidth and sampling frequency of interest, inter antenna spacing, and 3dB beam size. Real-time steering of such 3-D beam filters are obtained by proposed calculation of filter coefficients. Application specific computing units for rapidly calculating the 3-D IIR filter coefficients at nanosecond speed potentially allows fast real-time tracking of low radar cross section (RCS) objects at close range. Proposed design consists of 3-D IIR beam filter with 4 4 antenna grid and the filter coefficient generation block in separate FPGAs. The hardware is designed and co-simulated using a Xilinx Virtex-6 XC6VLX240T FPGA. The 3-D filter operates over 90 MHz and filter coefficient computing structure can operate at up to 145 MHz.
Removing the twin image in digital holography by segmented filtering of in-focus twin image
2008-01-01
We propose and investigate a new digital method for the reduction of twin-image noise from digital Fresnel holograms. For the case of in-line Fresnel holography the unwanted twin is present as a highly corruptive noise when the object image is numerically reconstructed. We propose to firstly reconstruct the unwanted twin-image when it is in-focus and in this plane we calculate a segmentation mask that borders this in focus image. The twin-image is then segmented and removed by sim...
Usefulness of Nonlinear Interpolation and Particle Filter in Zigbee Indoor Positioning
Zhang, Xiang; Wu, Helei; Uradziński, Marcin
2014-12-01
The key to fingerprint positioning algorithm is establishing effective fingerprint information database based on different reference nodes of received signal strength indicator (RSSI). Traditional method is to set the location area calibration multiple information sampling points, and collection of a large number sample data what is very time consuming. With Zigbee sensor networks as platform, considering the influence of positioning signal interference, we proposed an improved algorithm of getting virtual database based on polynomial interpolation, while the pre-estimated result was disposed by particle filter. Experimental result shows that this method can generate a quick, simple fine-grained localization information database, and improve the positioning accuracy at the same time. Kluczem do algorytmu pozycjonowania wykorzystującego metodę fi ngerprinting jest ustanowienie skutecznej bazy danych na podstawie informacji z radiowych nadajników referencyjnych przy wykorzystaniu wskaźnika mocy odbieranego sygnału (RSSI). Tradycyjna metoda oparta jest na przeprowadzeniu kalibracji obszaru lokalizacji na podstawie wielu punktów pomiarowych i otrzymaniu dużej liczby próbek, co jest bardzo czasochłonne.
Directory of Open Access Journals (Sweden)
S. Murugeswari
2015-01-01
Full Text Available In Digital Signal Processing, Finite Impulse Response (FIR filter is mostly used for communications and radar applications. The Performance of FIR filter depends on Multiplier and adder circuits used in filter. To reduce the dynamic power consumption and chip size, different multiplier and adder combinations are used in order to improve the overall performance of FIR filter. The Low Power Modified Square Root Carry Select Adder (M-SQRT CSLA is presented in this study by introducing half adders instead of full adders. The proposed M-SQRT CSLA has been designed to reduce dynamic power consumption. Hence the modified SQRT CSLA is applied into Wallace multiplier for addition process after the partial product generation stage. MAC unit of the Digital FIR filter is designed by using modified Wallace multipliers and M-SQRT CSLA. Further the Group 2, Group 3; Group 4 and Group5 structures of SQRT CSLA were constructed using half adders only. Comparison between proposed SQRT CSLA and Modified Carry Save Adder (MCSA has been done with reference to the Area, Power and Delay. It is proved that the proposed SQRT CSLA consumes less area and power than all other methods. Simulation is performed by Modelsim6.3c and Synthesis process is done by Xilinx 10.1. The simulation result shows that digital filter with proposed SQRT CSLA occupies less area and consumes low power.
Indian Academy of Sciences (India)
R BALASUBRAMANIAN; R SANKARAN; S PALANI
2017-09-01
This paper deals with design and simulation of a three-phase shunt hybrid power filter consisting of a pair of 5th and 7th selective harmonic elimination passive power filters connected in series with a conventional active power filter with reduced kVA rating. The objective is to enhance the power quality in a distributionnetwork feeding variety of non-linear, time-varying and unbalanced loads. The theory and modelling of the entire power circuit in terms of synchronously rotating reference frame and leading to a non-linear control scheme is presented. This work involves introduction of individual fuzzy logic controllers for d and q axiscurrent control and for voltage regulation of the DC link capacitor. The simulation schematic covering the power and control circuits have been developed taking into account severe harmonic distortion caused by non-linear and unbalanced loads. The effectiveness of the fuzzy logic controller for the compensation of harmonics and reactive power has been verified by successive simulation runs and analysis of the results. The proposed controller is also able to compensate the distortion generated by the voltage- and current-fed non-linear loads, unbalanced and dynamically varying loads. Further, excellent regulation of the DC link voltage is accomplished, which significantly contributes to improvement of power quality.
An EMI Filter Selection Method Based on Spectrum of Digital Periodic Signal
Directory of Open Access Journals (Sweden)
Matjaz Segula
2006-03-01
Full Text Available This paper describes a new method for the selection of an appropriate signal lineElectromagnetic Interference (EMI filter. To date, EMI filter selection has been based onthe measurement of the radiation of the entire device. The new selection method based onthe signalÃ¢Â€Â™s Fast Fourier Transform (FFT measurement has proved to be efficient. The EMIfilter is optimized separately for each line. The method described in this paper involving aCentral Processor Unit (CPU module demonstrates that the proposed FFT-based selectionmethod is better than the radiation-based one. The radiation level in the frequency range 30MHz to 1 GHz is lower for approximate 2 Ã¢Â€Â“ 6 dBÃŽÂ¼V/m.
Comparative Study on Some Nonlinear Filtering Algorithms%几种非线性滤波算法的比较研究
Institute of Scientific and Technical Information of China (English)
王庆欣; 史连艳
2011-01-01
针对组合导航等非线性系统,扩展卡尔曼滤波算法(EKF)在初值不准确时存在滤波发散的现象,故提出U-卡尔曼滤波(UKF);粒子滤波算法(PF)适合于强非线性、非高斯噪声系统,但同时存在退化现象,故提出2种改进算法.前人的工作多集中在单一算法的研究,而在此是将上述各种算法应用到同一典型非线性系统,通过应用Matlab进行仿真实验得出具体滤渡效果数据,综合对比分析了各算法的优缺点,得出一些有用的结论,为组合导航系统中非线性滤波算法的选择提供了参考.%For the nonlinear systems such as integrated navigation systems, since the extended Kalman filtering ( EKF) has a dispersing phenomenon when the initial state value is inaccurate, the unscented Kalman filiering ( UKF) is proposed,and although particle filtering (PF) is suitable for any nonlinear non-Gaussian systems, it has a degeneracy phenomenon, then two kinds of improved filtering algorithms are put forward. Scientific researchers focused on single filtering before. The filtering algorithms mentioned above are adopted in a same typical model of nonlinear system in this paper. The detailed data of the filtering algorithms were obtained by emulational experiments with Matlab. Some useful conclusios were acquired after the contrast and analysis of their advantages and disadvantages. A reference is offered in choosing a suitable nonlinearfiltering algorithm for integrated navigation systems.
Polyphase Filter Banks for Embedded Sample Rate Changes in Digital Radio Front-Ends
DEFF Research Database (Denmark)
Awan, Mehmood-Ur-Rehman; Le Moullec, Yannick; Koch, Peter
2011-01-01
This paper presents efficient processing engines for software-defined radio (SDR) front-ends. These engines, based on a polyphase channelizer, perform arbitrary sample-rate changes, frequency selection, and bandwidth control. This paper presents an M-path polyphase filter bank based on a modified N...... in an SDR front-end based on a polyphase channelizer. They can also be used for translation to and from arbitrary center frequencies that are unrelated to the output sample rates....
1-D Systolic Arrays Design of LMS Adaptive (FIR Digital Filtering
Directory of Open Access Journals (Sweden)
Ali H. Mahdi
2010-01-01
Full Text Available This paper extends the 1-D systolic array approach with a method of systematic linear design of systolic algorithms. Past methods for mapping the Least-Mean-Square (LMS Adaptive Finite-Impulse-Response (FIR filter onto parallel and pipelined architectures either introduce delays in the coefficients updates or have excessive hardware requirements. In this article, we describe an efficient 1-D systolic array for the LMS adaptive FIR filter that produces the same output and error signals as produced by the standard LMS adaptive filter architecture with single assignment form of processor functions.The proposed systolic architectures that are designed operate on a block-by-block basis and makes use of the flexibility in the design, which takes the inner product step (convolution sum of the tap weight vector and the tap input vector in the design consideration. It enables us to extract more than one algorithm for the same problem. The input and output data flow sequentially and continuously into and out of the systolic arrays at the system clock rates, during each clock period, processing element of the same type operates in parallel. The most computationally demanding among them performs only two consecutive multiplications and two additions/subtractions per clock period, thereby allowing a very high throughput and very fast block signal processing to be achieved at the expense of a delay of L samples between the input and output and 100% utilization, L being the block size.