Abstract
A new improved memorised improved proportionate affine projection algorithm (IMIPAPA) is proposed to improve the convergence performance of sparse system identification, which incorporates l 0-norm as a measure of sparseness into a recently proposed MIPAPA algorithm. In addition, a simplified implementation of the IMIPAPA (SIMIPAPA) with low-computational burden is presented while maintaining the consistent convergence performance. The simulation results demonstrate that the IMIPAPA and SIMIPAPA algorithms outperform the MIPAPA algorithm for sparse system identification.
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