Learning algorithms for adaptive processing and control

Author

Widrow, Bernard ; Lehr, Michael ; Beaufays, Françoise ; Wan, Eric ; Bileillo, M.

Author_Institution

Dept. of Electr. Eng., Stanford Univ., CA, USA

fYear

1993

fDate

1993

Firstpage

1

Abstract

Linear and nonlinear adaptive filtering algorithms are described, along with applications to signal processing and control problems. Specific topics addressed include adaptive least mean square (LMS) filtering, adaptive filtering with discrete cosine transform LMS (DCT/LMS), adaptive noise cancelling, fetal electrocardiography, adaptive echo cancelling, inverse plant modeling, adaptive inverse control, adaptive equalization, adaptive linear prediction, and nonlinear filtering and prediction

Keywords

adaptive control; discrete cosine transforms; filtering and prediction theory; learning systems; least squares approximations; signal processing; adaptive control; adaptive filtering algorithms; adaptive least mean square; adaptive processing; discrete cosine transform LMS; echo cancelling; equalization; fetal electrocardiography; inverse control; inverse plant modeling; linear prediction; noise cancelling; nonlinear filtering; signal processing; Adaptive control; Adaptive filters; Adaptive signal processing; Discrete cosine transforms; Filtering algorithms; Least squares approximation; Nonlinear filters; Process control; Programmable control; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993., IEEE International Conference on

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-0999-5

Type

conf

DOI

10.1109/ICNN.1993.298540

Filename

298540