Title :
The identification of nonlinear discrete-time fading-memory systems using neural network models
Author :
Matthews, Michael B. ; Moschytz, George S.
Author_Institution :
MBARI, Pacific Grove, CA, USA
fDate :
11/1/1994 12:00:00 AM
Abstract :
A fading-memory system is a system that tends to forget its input asymptotically over time. It has been shown that discrete-time fading-memory systems can be uniformly approximated arbitrarily closely over a set of bounded input sequences simply by uniformly approximating sufficiently closely either the external or internal representation of the system. In other words, the problem of uniformly approximating a fading-memory system reduces to the problem of uniformly approximating continuous real-valued functions on compact sets. The perceptron is a parametric model that realizes a set of continuous real-valued functions that is uniformly dense in the set of all continuous real-valued functions. Using the perceptron to uniformly approximate the external and internal representations of a discrete-time fading-memory system results, respectively, in simple finite-memory and infinite-memory parametric system models. Algorithms for estimating the model parameters that yield a best approximation to a given fading-memory system are discussed. An application to nonlinear noise cancellation in telephone systems is presented
Keywords :
approximation theory; discrete time systems; echo suppression; nonlinear systems; parameter estimation; perceptrons; state estimation; approximation; continuous real-valued functions; identification; model parameters estimation; neural network models; nonlinear discrete-time fading-memory systems; nonlinear noise cancellation; parametric model; perceptron; telephone systems; Approximation algorithms; Echo cancellers; Mathematical model; Neural networks; Noise cancellation; Parameter estimation; Parametric statistics; Predictive models; Telephony; Yield estimation;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on