… adaptive algorithms for blind and semi-blind signal processing with a particular focus on
robust algorithms … Moreover, novel adaptive systems and associated learning algorithms are …

… topics and applications. I highly recommend the book to any reader interested in blind
signal and image processing. Qualitative Analysis and Synthesis of Recurrent Neural Net- …

… INTRODUCTION There are many potential applications of neural networks to signal
processing. This paper treats learning algorithms for blind signal separation and deconvolution of …

… least-squares type neural or adaptive learning algorithm 1201 which is more accurate …
applications. A drawback is that the fixed-point algorithms are not strictly neural and data-adaptive…

… learning algorithms for a multi{layer arti cial neural network (ANN). The rst algorithm is based
on a recently developed adaptive … consider two di erent learning algorithms where each of …

In this information age, digital signal processing technology is playing an increasingly important
role in various fields of science and technology. Blind signal processing (BSP) has been …

… The MOD-BSF learning algorithm can be summarized as follows: … a novel Blind Source
Separation technique based on the experience of our research group in the polynomial adaptive …

… [12] HH Yang and SI Amari, “Adaptive on-line learning algorithms for blind separation-maximum
entropy and minimum mutual information,” Neural Comput., vol. 9, pp. 1457–1482, 1997…

… performance of online adaptation algorithms, is introduced. Finally, variants of the LMS
algorithm, some multichannel algorithms applications, and delayed learning algorithms, such as …

… This problem, which is known as blind source separation (BSS), can be presented by the
following … In addition, considering faster dictionary learning algorithms rather than K-SVD can …