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Cited by 228

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Nonlinear adaptive prediction of nonstationary signals

Haykin, S., Liang Li·1995·IEEE Transactions on Signal Processing

Abstract

We describe a computationally efficient scheme for the nonlinear adaptive prediction of nonstationary signals whose generation is governed by a nonlinear dynamical mechanism. The complete predictor consists of two subsections. One performs a nonlinear mapping from the input space to an intermediate space with the aim of linearizing the input signal, and the other performs a linear mapping from the new space to the output space. The nonlinear subsection consists of a pipelined recurrent neural network (PRNN), and the linear section consists of a conventional tapped-delay-line (TDL) filter. The nonlinear adaptive predictor described is of general application. The dynamic behavior of the predictor is demonstrated for the case of a speech signal; for this application, it is shown that the nonlinear adaptive predictor outperforms the traditional linear adaptive scheme in a significant way.>

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Metadata

Authors
Haykin, S., & Li, L.
Venue
IEEE Transactions on Signal Processing
Published
1995
Volume
43
Issue
2
Pages
526-535
ISSN
1053-587X (ISSN-L)
OpenAlex
W2168858784
Cited by
228
References
1
FWCI
6.22
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nonlinear adaptive prediction of nonstationary signals. https://app.cochat.ai/papers/10.1109/78.348134
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Haykin, S., & Li, L. (1995). Nonlinear adaptive prediction of nonstationary signals. IEEE Transactions on Signal Processing. https://doi.org/10.1109/78.348134

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