Analysis of an adaptive technique for modeling sparse systems

Abstract

An effective technique for modeling sparse systems has been developed, and the error surface of the system is analyzed with respect to estimation noise. The technique requires a type of adaptive filter which is called an adaptive delay filter. An implementation of the adaptive delay filter is discussed that includes adaptive gains in addition to variable delay taps. The filter is especially applicable to modeling systems with a sparse impulse response. Less computation is required for a sparse system than with the conventional approach. The technique is tested with a variety of unknown systems using both white noise input and autoregressive input. It is shown that it works properly for both sparse and nonsparse systems in noise-free and noisy conditions. The performance of the technique is verified by a careful analysis of the error surface and the techniques for delay determination and corresponding gain adaption. >