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Kernel adaptive filter

About: Kernel adaptive filter is a research topic. Over the lifetime, 8771 publications have been published within this topic receiving 142711 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, it is shown that modulo arithmetic may be used in the inverse filter to eliminate completely the possibility of instability, and a very simple automatic or adaptive equalisation system is presented.
Abstract: The limitations of present automatic and adaptive equalisers stem from the use of feedforward transversal filters. These drawbacks may be obviated by using a feedback transversal filter, the inverse filter, but this is only suitable for limited use since it can be an unstable circuit. It is shown that modulo arithmetic may be used in the inverse filter to eliminate completely the possibility of instability, and a very simple automatic or adaptive equalisation system is presented. Some interesting properties of the modulo inverse filter are included.

1,035 citations

Journal ArticleDOI
TL;DR: A least-mean-square adaptive filter with a variable step size, allowing the adaptive filter to track changes in the system as well as produce a small steady state error, is introduced.
Abstract: A least-mean-square (LMS) adaptive filter with a variable step size is introduced. The step size increases or decreases as the mean-square error increases or decreases, allowing the adaptive filter to track changes in the system as well as produce a small steady state error. The convergence and steady-state behavior of the algorithm are analyzed. The results reduce to well-known results when specialized to the constant-step-size case. Simulation results are presented to support the analysis and to compare the performance of the algorithm with the usual LMS algorithm and another variable-step-size algorithm. They show that its performance compares favorably with these existing algorithms. >

966 citations

Journal ArticleDOI
TL;DR: The detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given, based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors.
Abstract: After reviewing the two main approaches of adaptive Kalman filtering, namely, innovation-based adaptive estimation (IAE) and multiple-model-based adaptive estimation (MMAE), the detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given. The developed adaptive Kalman filter is based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors. Results from two kinematic field tests in which the INS/GPS was compared to highly precise reference data are presented. Results show that the adaptive Kalman filter outperforms the conventional Kalman filter by tuning either the system noise variance–covariance (V–C) matrix `Q' or the update measurement noise V–C matrix `R' or both of them.

949 citations

Proceedings ArticleDOI
C.W. Farrow1
07 Jun 1988
TL;DR: An FIR (finite-impulse-response) filter which synthesizes a controllable delay which has the ability to interpolate between samples in the data stream of a band-limited signal is described.
Abstract: The author describes an FIR (finite-impulse-response) filter which synthesizes a controllable delay. By changing the delay the filter has the ability to interpolate between samples in the data stream of a band-limited signal. Because high sampling rates are not required, the filter is especially suited for implementation in a digital signal processor (DSP), and has been implemented in a real-time DSP. The interpolator can be used as a practical way to reconstruct an original band limited signal from samples taken at the Nyquist rate. The variable delay filter can also be used as a more general computational element. Performance results are presented. >

853 citations

Journal ArticleDOI
TL;DR: In this article, a simple filter for controlling high-frequency computational and physical modes arising in time integrations is proposed, and a linear analysis of the filter with leapfrog, implicit, and semi-implicit, differences is made.
Abstract: A simple filter for controlling high-frequency computational and physical modes arising in time integrations is proposed. A linear analysis of the filter with leapfrog, implicit, and semi-implicit, differences is made. The filter very quickly removes the computational mode and is also very useful in damping high-frequency physical waves. The stability of the leapfrog scheme is adversely affected when a large filter parameter is used, but the analysis shows that the use of centered differences with frequency filter is still more advantageous than the use of the Euler-backward method. An example of the use of the filter in an actual forecast with the meteorological equations is shown.

799 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202322
202251
202113
202020
201931
201844