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About 10,000 papers for “Nonlinear filter”

NFIR nonlinear filter

Xingjian Wang · IEEE Transactions on Signal Processing · 1991

A nonlinear filter is introduced whose output is nearest in distance to the output of a FIR (finite impulse response) linear phase filter; hence it is called the NFIR filter. After choosing the impulse response of the FIR filter properly, the NFIR filter can clean impulsive noise and preserve edges of signals. As a special case of the NFIR filter, a nearest mean (NEME) filter is derived. Theoretical analysis shows that the NEME filter is better than the median filter in smoothing additive Gaussian noise. In addition, based on the definition of the NEME filter, a new interpretation of the low-pass property of the median filter with window width 3 is described. Also, the performance of the nearest mean filter on a noisy edge is quantitatively compared with that of the median and mean filters.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 7

Nonlinear Christiansen filter

S. Vartak, N. M. Lawandy · Optics Letters · 1996

We demonstrate a nonlinear Christiansen filter in both the steady state and the transient regimes and in both the self- and the cross-modulation modes. Experiments in which a thermal nonlinearity was used agree well with predictions based on a modified scattering theory model.

Cited by 1

Study of nonlinear filter methods: Particle filter

Weiming Zhang, Gang Du, Shan Zhong et al. · Journal of Systems Engineering and Electronics · 2006

Extended Kaiman filter (EKF) is one of the most widely used methods for nonlinear system estimation. A new filtering algorithm, called particle filtering (PF) is introduced. PF can yield better performance than that of EKF, because PF does not involve the linearization approximating to nonlinear systems, that is required by the EKF. PF has been shown to be a superior alternative to the EKF in a variety of applications. The base idea of PF is the approximation of relevant probability distributions using the concepts of sequential importance sampling and approximation of probability distributions using a set of discrete random samples with associated weights. PF methods still need to be improved in the aspects of accuracy and calculating speed.

Cited by 5

The Nonlinear Projection Filter

Randal Beard, Jacob Gunther, Jonathan Lawton et al. · 1998

The conditional probability density function of the state of a stochastic dynamic system represents the complete solution to the nonlinear filtering problem because, with the conditional density in hand, all estimates of the state, optimal or otherwise, can be computed. It is well known that, for systems with continuous dynamics, the conditional density evolves, between measurements, according to Kolmogorov&amp;apos;s forward equation. At a measurement, it is updated according to Bayes formula. Therefore, these two equations can be viewed as the dynamic equations of the conditional density and, hence, the exact nonlinear filter. In this paper, Galerkin&amp;apos;s method is used to approximate the nonlinear filter by solving for the entire conditional density. Using an FFT to approximate Corresponding Author, email: beard@ee.byu.edu. the projections required in Galerkin&amp;apos;s method leads to a computationally efficient nonlinear filter. The implementation details are given and performance is assessed thr...

Cited by 0

Configurable nonlinear filter generator

Chi-Kwong Chan, L.M. Cheng · Electronics Letters · 1998

A configurable nonlinear filter generator is proposed. The nonlinear function employed is key controllable. By changing the key, a different sequence will be obtained. Simulated results show that an optimal linear complexity profile of the sequence can be generated.

Cited by 4

Nonlinear FIR filter clones

R. K. Pearson, M. Gabbouj, J. Astola · 2003

This paper considers the problem of designing nonlinear FIR filters from a bottom-up approach, in which simple components with known characteristics are combined into more complex filter structures. The specific approach considered here is based on the concept of a clone from universal algebra, generalizing the FIR-median hybrid (FMH) filter construction. Results presented here illustrate the flexibility of this procedure, the vast array of interesting special cases that emerge, including some new ones, and some of the types of qualitative behavior that are preserved under the clone interconnection strategy. 1

Cited by 0

function and Nonlinear Filter

R. Pushpavalli, G. Sivarajde · 2013

Abstract- In this paper, fuzzy based median filtering technique is proposed for enhancing highly corrupted digital images. This filter is obtained in two steps; in first step fuzzy decision rule is applied to detect the impulse noise on input image (noisy image). In second step, noisy pixels are removed using decision based filters. The performance of proposed filter is compared with other existing filters and shown to be more effective in terms of eliminating impulse noise and preserving edges and fine details of digital images.

Cited by 0

Solving SIMO Nonlinear Systems With Euler Nonlinear Filter

Kaili Yin, Yi-Fei Pu, Lu Lu · IEEE Transactions on Circuits & Systems II Express Briefs · 2021

This brief proposes a novel perspective for solving single input and multiple output (SIMO) nonlinear systems with multi-cost function adaptive algorithm. Based on Euler polynomials, the Euler filter with finite memory is proposed to construct a filter bank, which realizes the accurate identification of high-dimensional nonlinear systems. To improve the algorithm performance, a multi-cost function is proposed. Moreover, the mean-square stability and steady-state performance of the proposed method are rigorously analyzed. The typical FitzHugh-Nagumo (FHN) system, which fiercely exhibits chaotic dynamics, is considered for justifying the performance of this new algorithm. Numerical results highlight the solution accuracy via comparison with existing approaches.

Cited by 4

An analoque nonlinear dynamic filter

MF Marcel Heertjes · TU/e Research Portal (Eindhoven University of Technology) · 2005

An analogue non-linear dynamic filter having a substantially semisoidal input-output transfer characteristic with a trough at a first constant level and a peak at a second constant level, and a continuously variable transfer function between the first and second levels. The first level, which is substantially zero, is defined by a small area of the input signal in the vicinity of the zero crossings thereof, and is obtained by subtracting the output of a first clipper circuit (12) from the input signal. The second constant level is obtained by applying the signal to a second clipper circuit (14) and the signal is then applied to a rectifier (16) before being multiplied by the input signal to attain a variable gain function

Cited by 0

A nonlinear adaptive digital filter

S.A. White, V.A. Vitols · IEEE Transactions on Circuits and Systems · 1988

An adjustable, memoryless, single-valued, monotonic nonlinearity is introduced between the output point of a linear adaptive FIR (finite-impulse response) filter and the output point of the system. A control strategy is derived that permits the simultaneous shaping of both the power spectrum and the amplitude-density function of the system output by jointly adjusting the shape of the nonlinearity and the tap weights of the linear filter. A mechanization diagram and some mechanization considerations are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 11

q:p Algorithm ... +-p Nonlinear Filter

Leslie C. Stewart, Robert M. Gray, Y. Linde · 1982

New algorithms for the design of trellis encoding data compression systems are described. The main algorithm uses a training sequence of actual data from a source to improve an initial trellis decoder. An additional algorithm extends the constraint length of a given decode? Combined, these algorithms allow the automatic. design of a trellis encoding system for a particular source. The algorithms' effectiveness for random sources is demonstrated through performance comparisons with other source coding systems and with theoretical bounds. The algorithms are applied to the practical problem of the design of trellis and hybrid codes for medium-to-low- rate speech compression.

Cited by 0

Nonlinear Filter for Orbit Determination

Jangho Yoon · Journal of Aerospace System Engineering · 2016

Orbit determination problems have been interest of many researchers for long time. Due to the high nonlinearity of the equation of motion and the measurement model, it is necessary to linearize the both equations. To avoid linearization, the filter based on Fokker-Planck equation is designed. with the extended Kalman filter update mechanism, in which the associated Fokker-Planck equation was solved efficiently and accurately via discrete quadrature and the measurement update was done through the extended Kalman filter update mechanism. This filter based on the DQMOM and the EKF update is applied to the orbit determination problem with appropriate modification to mitigate the filter smugness. Unlike the extended Kalman filter, the hybrid filter based on the DQMOM and the EKF update does not require the burdensome evaluation of the Jacobian matrix and Gaussian assumption for the system, and can still provide more accurate estimations of the state than those of the extended Kalman filter especially when measurements are sparse. Simulation results indicate that the advantages of the hybrid filter based on the DQMOM and the EKF update make it a promising alternative to the extended Kalman filter for orbit estimation problems.

Cited by 0Open access

Nonlinear Filter Design for Markovian Jump Nonlinear Stochastic Systems

Wen-Hao Chen, Juh-Shinun Lin · 2009

[[abstract]]This paper discusses the nonlinear filter design for state estimation of Markovian jump nonlinear stochastic systems. Our results extend the filter theory for Markovian jump linear systems to the nonlinear stochastic systems with Markovian jumping parameters. By using the Lyapunov approach to design the nonlinear filter for Markovian jump nonlinear stochastic systems, the state estimation error for the proposed filter can approach to zero asymptotically in probability. Finally, a simulated example is given to justify the performance of the proposed nonlinear filter.

Cited by 0

Oscillator tracking filter with nonlinear feedback

A.D. Menyalo, В. В. Рапин · Radiotekhnika · 2018

An oscillator tracking filter based on a single circuit LC oscillator with the nonlinear feedback synchronized by a periodic nonharmonic signal is proposed. The theoretical investigation of the first-harmonic injection locked LC oscillator operation is considered. The model of the oscillator is presented and the stationary state operation is analyzed by the harmonic balance method. The obtained simple analytical expressions describing first and second harmonic components allow making quality analysis and can be directly applied to the practical design. This filter is intended for a selection of the first harmonic component of the external periodic polyharmonic signal in a wide working range with the purpose of measuring its frequency. It is found that such filters were very effective at large amplitudes of higher harmonic components of the external signal with unstable amplitude-phase correlations. Practical application has confirmed its high reliability.

Cited by 0Open access