Results 281 to 290 of about 182,122 (313)

Adaptive optics with adaptive filtering and control

Proceedings of the 2004 American Control Conference, 2004
This paper presents a quasi adaptive control method for adaptive optics. Adaptive compensation is needed in many adaptive optics applications because wind velocities and the strength of atmospheric turbulence can change rapidly, rendering any fixed-gain reconstruction algorithm far from optimal.
Yu-Tai Liu, Steve Gibson 0001
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Adaptive multichannel filtering

ICASSP '80. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A linearly constrained adaptive multichannel filtering algorithm is described which is designed to adjust the filter coefficients, sample by sample, within the prescribed constraints for adaptive noise cancelling purposes. This technique is applicable to many array processing problems where in the signal is corrupted by coherent as well as random noise.
openaire   +1 more source

Adaptive Filtering for Color Filter Array Demosaicking

IEEE Transactions on Image Processing, 2007
Most digital still cameras acquire imagery with a color filter array (CFA), sampling only one color value for each pixel and interpolating the other two color values afterwards. The interpolation process is commonly known as demosaicking. In general, a good demosaicking method should preserve the high-frequency information of imagery as much as ...
Naixiang Lian, Lanlan Chang, Yap-Peng Tan, Vitali Zagorodnov   +3 more
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Adaptive Filtering For Image Enhancement

Optical Engineering, 1982
In this paper, we develop an image enhancement algorithm that modifies the local luminance mean of an image and controls the local constrast as a function of the local luminance mean of the image. The algorithm first separates an image into its lows (low-pass filtered form) and highs (high-pass filtered form) components.
Tamar Peli, Jae S. Lim
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Multikernel Adaptive Filtering

IEEE Transactions on Signal Processing, 2012
This paper exemplifies that the use of multiple kernels leads to efficient adaptive filtering for nonlinear systems. Two types of multikernel adaptive filtering algorithms are proposed. One is a simple generalization of the kernel normalized least mean square (KNLMS) algorithm [2], adopting a coherence criterion for dictionary designing.
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A theory of adaptive filtering

IEEE Transactions on Information Theory, 1966
This paper considers the adaptive signal extraction problem for time-discrete data when only very general a priori assumptions regarding the distributions of signal and noise are possible. Specifically, it is assumed that the noise is white, additive, and signal independent with mean zero and unknown variance and that the signal is band-limited.
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Adaptive polynomial filters

IEEE Signal Processing Magazine, 1991
Adaptive nonlinear filters equipped with polynomial models of nonlinearity are explained. The polynomial systems considered are those nonlinear systems whose output signals can be related to the input signals through a truncated Volterra series expansion or a recursive nonlinear difference equation. The Volterra series expansion can model a large class
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Introduction to Adaptive Filtering

1997
In this section, we define the kind of signal processing systems that will be treated in this text.
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Adaptive Filters

2014
Vítor H. Nascimento, Magno T.M. Silva
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Application of an EMG interference filtering method to dynamic ECGs based on an adaptive wavelet-Wiener filter and adaptive moving average filter

Biomedical Signal Processing and Control, 2022
Yurong Li
exaly