Design and Development of Adaptive Prediction Filter for Cancellation of Narrowband Noise Interference in Wideband Signal
Abstract
In practice, one often encounters systems that have a sparse impulse response, with the degree of sparseness varying over time. This paper presents a new approach to identify such systems which adapts dynamically to the sparseness level of the system and thus works well both in sparse and non-sparse environments. The proposed scheme uses an adaptive convex combination of the LMS algorithm and the recently proposed, sparsity-aware zero-attractor LMS (ZA-LMS) algorithm.
Keywords
Convex combination; excess mean square error; sparse systems; ZA-LMS algorithm.
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PDFCopyright (c) 2015 Pujitha Duvvuri, K. Jeevan Reddy, spv venumadhav rao
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