DocumentCode :
2287076
Title :
Transform domain adaptive processing with neural network controlled resonator banks
Author :
Patra, Jagdish C ; Pal, Ranendra N.
Author_Institution :
Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol., Kharagpur, India
fYear :
1994
fDate :
13-16 Apr 1994
Firstpage :
666
Abstract :
Most of the adaptive processing systems are typically designed with a predefined structure. In case of abruptly changing and unstable environments this type of fixed structures pose serious limitations in processing of signals. This paper describes a hybrid adaptive processing system which can dynamically change its transfer characteristics under changeable environment. The proposed architecture basically consists of two parts, a resonator-bank digital filter (RBDF) and a neural network (NN). The RBDF provides effective implementation of orthogonal transforms recursively. The NN is utilized to perform a nonlinear mapping between its input vector U(n) and the H(n), the complex coefficients determining the transfer characteristics of the RBDF. The authors present a performance comparison of the NN controlled RBDF under different orthogonal transforms
Keywords :
digital filters; feedforward neural nets; filtering and prediction theory; resonators; signal processing; transforms; changeable environment; complex coefficients; hybrid adaptive processing system; input vector; multilayer neural network; neural network controlled resonator banks; nonlinear mapping; orthogonal transforms; performance comparison; resonator-bank digital filter; signal processing; transfer characteristics; transform domain adaptive processing; unstable environments; Adaptive control; Adaptive signal processing; Communication system control; Digital filters; Discrete transforms; Multi-layer neural network; Neural networks; Programmable control; Signal processing; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
Print_ISBN :
0-7803-1865-X
Type :
conf
DOI :
10.1109/SIPNN.1994.344823
Filename :
344823
Link To Document :
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