G. Alipoor
Hamedan University of Technology, Hamedan, Iran
[ 1 ] - Utilizing Kernel Adaptive Filters for Speech Enhancement within the ALE Framework
Performance of the linear models, widely used within the framework of adaptive line enhancement (ALE), deteriorates dramatically in the presence of non-Gaussian noises. On the other hand, adaptive implementation of nonlinear models, e.g. the Volterra filters, suffers from the severe problems of large number of parameters and slow convergence. Nonetheless, kernel methods are emerging solutions t...
[ 2 ] - An Analytical Model for Predicting the Convergence Behavior of the Least Mean Mixed-Norm (LMMN) Algorithm
The Least Mean Mixed-Norm (LMMN) algorithm is a stochastic gradient-based algorithm whose objective is to minimum a combination of the cost functions of the Least Mean Square (LMS) and Least Mean Fourth (LMF) algorithms. This algorithm has inherited many properties and advantages of the LMS and LMF algorithms and mitigated their weaknesses in some ways. The main issue of the LMMN algorithm is t...
نویسندگان همکار