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A theory of adaptive filtering
IEEE Transactions on Information Theory, 1966This 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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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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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
1997In this section, we define the kind of signal processing systems that will be treated in this text.
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Hypercomplex adaptive filtering.
2018The degree of diffusion of hypercomplex algebras in adaptive and non-adaptive filtering research topics is growing faster and faster. The performance of hypercomplex adaptive filters has been widely experimented during the last decade. Quaternion filters, in particular, have been utilized in systems where the signals to be processed have some form of ...
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Constrained maximum correntropy adaptive filtering
Signal Processing, 2017Siyuan Peng, Badong Chen, Zhiping Lin
exaly

