Title :
A perceptron-based adaptive equalizer for PAM signals
Author :
Giridhar, K. ; Shynk, John J.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
Abstract :
An adaptive equalizer based on a multilayer perceptron and the backpropagation training algorithm is presented for M-ary PAM (pulse amplitude modulation) digital communication systems. The configuration is an extension of the conventional adaptive FIR (finite impulse response) equalizer whereby the linear filter is replaced by a nonlinear feedforward network with nodes that saturate at ±1. The training signal is derived by encoding the PAM signals via a bit-mapping strategy such that the output layer of the perceptron requires log2 (M) nodes. A corresponding number of error signals is generated, and these are used to drive the backpropagation algorithm. Computer simulations are presented to illustrate the performance of the equalizer for two different bit mappings
Keywords :
backpropagation; digital signals; equalisers; feedforward neural nets; pulse amplitude modulation; M-ary PAM; PAM signals; backpropagation training algorithm; bit-mapping strategy; digital communication systems; error signals; multilayer perceptron; nonlinear feedforward network; perceptron-based adaptive equalizer; training signal; Adaptive equalizers; Adaptive filters; Amplitude modulation; Backpropagation algorithms; Digital communication; Encoding; Finite impulse response filter; Multilayer perceptrons; Nonlinear filters; Pulse modulation;
Conference_Titel :
Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0593-0
DOI :
10.1109/ISCAS.1992.230195
