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.
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TL;DR: In this article, a cascade of two filters along with a short bulk delay is used to adjust the filter response to make the most effective use of the limited number of filter coefficients.
Abstract: Feedback cancellation apparatus uses a cascade of two filters along with a short bulk delay. The first filter is adapted when the hearing aid is turned on in the ear. This filter adapts quickly using a white noise probe signal, and then the filter coefficients are frozen. The first filter models parts of the hearing-aid feedback path that are essentially constant over the course of the day. The second filter adapts while the hearing aid is in use and does not use a separate probe signal. This filter provides a rapid correction to the feedback path model when the hearing aid goes unstable, and more slowly tracks perturbations in the feedback path that occur in daily use. The delay shifts the filter response to make the most effective use of the limited number of filter coefficients.
189 citations
TL;DR: In this article, simple algebraic methods may be used to design three-dimensional (3D) recursive digital filters for two important applications: first, the selective enhancement of a two-dimensional signal that is moving with time along a linear trajectory at known velocity.
Abstract: It is shown that simple algebraic methods may be used to design three-dimensional (3-D) recursive digital filters for two important applications: first, the selective enhancement of a two-dimensional (2-D) signal that is moving with time along a linear trajectory at known velocity and, second, the selective enhancement of 3-D spatially planar waves. The design techniques involve first-order 3-D networks in the continuous domain and proceed by analogy with an extension of the simple circuit theoretic concepts of resonance and Q factor. A 3-D spatial straight-line filter is designed in the frequency domain as a 3-D planar filter and, conversely, a 3-D spatially planar filter is designed in the frequency domain as a 3-D straight-line filter.
187 citations
TL;DR: The adaptive process is considerably simplified by designing the notch filters by pole-zero placement on the unit circle using some suggested rules, and a constrained least mean-squared algorithm is used for the adaptive process.
Abstract: Investigates adaptive digital notch filters for the elimination of powerline noise from biomedical signals. Since the distribution of the frequency variation of the powerline noise may or may not be centered at 60 Hz. Three different adaptive digital notch filters are considered. For the first case, an adaptive FIR second-order digital notch filter is designed to track the center frequency variation. For the second case, the zeroes of an adaptive IIR second-order digital notch filter are fixed on the unit circle and the poles are adapted to find an optimum bandwidth to eliminate the noise to a pre-defined attenuation level. In the third case, both the poles and zeroes of the adaptive IIR second-order filter are adapted to track the center frequency variation within an optimum bandwidth. The adaptive process is considerably simplified by designing the notch filters by pole-zero placement on the unit circle using some suggested rules. A constrained least mean-squared algorithm is used for the adaptive process. To evaluate their performance, the three adaptive notch filters are applied to a powerline noise sample and to a noisy EEG as an illustration of a biomedical signal. >
187 citations
TL;DR: A two-stage algorithm, called switching-based adaptive weighted mean filter, is proposed to remove salt-and-pepper noise from the corrupted images by replacing each noisy pixel with the weighted mean of its noise-free neighbors in the filtering window.
Abstract: A two-stage algorithm, called switching-based adaptive weighted mean filter, is proposed to remove salt-and-pepper noise from the corrupted images. First, the directional difference based noise detector is used to identify the noisy pixels by comparing the minimum absolute value of four mean differences between the current pixel and its neighbors in four directional windows with a predefined threshold. Then, the adaptive weighted mean filter is adopted to remove the detected impulses by replacing each noisy pixel with the weighted mean of its noise-free neighbors in the filtering window. Numerous simulations demonstrate that the proposed filter outperforms many other existing algorithms in terms of effectiveness in noise detection, image restoration and computational efficiency.
183 citations
TL;DR: In this paper, a new nonlinear filter for continuous-time processes with discrete-time measurements is proposed, which is exact and can be implemented in real time with a computational complexity comparable to the Kalman filter.
Abstract: A new nonlinear filter is derived for continuous-time processes with discrete-time measurements. The filter is exact, and it can be implemented in real time with a computational complexity that is comparable to the Kalman filter. This new filter includes both the Kalman filter and the discrete-time version of the Benes filter as special cases. Moreover, the new theory can handle a large class of nonlinear estimation problems that cannot be solved using the Kalman or discrete-time Benes filters. A simple approximation technique is suggested for practical applications in which the dynamics do not satisfy the required conditions exactly. This approximation is analogous to the so-called "extended Kalman filter" [10], and it represents a generalization of the standard linearization method.
181 citations