Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks

Among the useful blind equalization algorithms, stochastic-gradient iterative equalization schemes are based on minimizing a nonconvex and nonlinear cost function. However, as they use a linear FIR filter with a convex decision region, their residual estimation error is high. In the paper, four nonl...

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Bibliographic Details
Published in:	IEEE transactions on neural networks Vol. 9; no. 6; pp. 1442 - 1455
Main Authors:	YOU, C, HONG, D
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.11.1998 Institute of Electrical and Electronics Engineers
Subjects:	Applied sciences Blind equalizers Constellation diagram Cost function Electric, optical and optoelectronic circuits Electronics Estimation error Exact sciences and technology Finite impulse response filter Iterative algorithms Multilayer perceptrons Neural networks Nonlinear filters Quadrature amplitude modulation Random variables Theoretical study. Circuits analysis and design Blind Backpropagation algorithm Perceptron Algorithm complexity Multiple layer Activation Quadrature modulation Neural network Feedforward Equalization Experimental study
ISSN:	1045-9227
Online Access:	Get full text
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