Topic
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 published on a yearly basis
Papers
More filters
TL;DR: In this article , a linear prefilter was introduced to whiten the correlated noise (i.e., colored noise) for obtaining the unbiased estimate of the filter weight, and a new gradient approach was developed for the adaptive filter design based on the fractional-order derivative and a linear filter.
Abstract: The previous work for the filter design considers uncorrelated white measurement noise disturbance. For more complex correlated noise disturbance, the conventional adaptive filter results in biased estimates. To overcome this problem, we introduce a linear prefilter to whiten the correlated noise (i.e., colored noise) for obtaining the unbiased estimate of the filter weight. Moreover, the design of some adaptive filters mainly focuses on the integer-order optimization methods. However, compared with the integer-order-based adaptive algorithms, the fractional-order-based algorithms show better performance. Thus, this letter develops a new gradient approach for the adaptive filter design based on the fractional-order derivative and a linear filter. Finally, the simulation results are provided from the system identification perspective for demonstrating the performance analysis of the proposed algorithms.
93 citations
Patent•
24 Jun 2005TL;DR: In this article, a comparison of frame power estimate with an adaptive frame noise power estimate, automatic gain control with fast adaptation and minimal speech distortion, echo cancellation updated in the frequency domain with stepsize optimization and smoothed spectral whitening, and echo suppression with adaptive talking-state transitions is made.
Abstract: Hands-free phones with voice activity detection using a comparison of frame power estimate with an adaptive frame noise power estimate, automatic gain control with fast adaptation and minimal speech distortion, echo cancellation updated in the frequency domain with stepsize optimization and smoothed spectral whitening, and echo suppression with adaptive talking-state transitions.
92 citations
05 Jun 2000
TL;DR: With this new filter and using multiple tacho references, waveforms, as well as amplitude and phase may be extracted without the beating interactions that are associated with conventional methods.
Abstract: The filter characteristics of the Vold-Kalman (1993, 1960, 1961) order tracking filter are presented. Both the frequency response as well as the time response and their time-frequency relationship have been investigated for different filter types and guidelines for optimum choice of filter parameters are presented. The Vold-Kalman filter allows for the high performance simultaneous tracking of orders in systems with multiple independent shafts. With this new filter and using multiple tacho references, waveforms, as well as amplitude and phase may be extracted without the beating interactions that are associated with conventional methods. Orders extracted as waveforms have no phase bias, and may hence be used for playback, synthesis and tailoring.
92 citations
TL;DR: A sequential optimization strategy is proposed, and a new algorithm is developed, in which the filter weights and the kernel size are both sequentially updated by stochastic gradient algorithms that minimize the mean square error (MSE).
92 citations
TL;DR: Several parallel-form adaptive IIR (infinite impulse response) filters are presented, including a frequency-domain implementation based on the discrete Fourier transform and a recursive frequency-sampling structure.
Abstract: Several parallel-form adaptive IIR (infinite impulse response) filters are presented, including a frequency-domain implementation based on the discrete Fourier transform and a recursive frequency-sampling structure. The performance of the frequency-domain adaptive IIR filter is investigated in a system identification application, which includes an analysis of its modeling capabilities and a discussion of the mean-square-error performance surface. Computer simulation results are presented to illustrate the robust convergence properties of the adaptive algorithm and to demonstrate the stability of the filter. >
92 citations