Blind deconvolution by simple adaptive activation function neuron

Author:

Fiori Simone

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference46 articles.

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3. S. Amari, S. Douglas, A. Cichocki, H.H. Yang, Novel on-line algorithms for blind deconvolution using natural gradient approach, in: Proceedings of the 11th IFAC Symposium on System Identification, SYSID-97, Kitakyushu, Japan, 8–11 July 1997, pp. 1057–1062.

4. An information maximisation approach to blind separation and blind deconvolution;Bell;Neural Comput.,1995

5. S. Bellini, Blind Equalization, Alta Frequenza, AEI (Italian Electrotechnical Association), Vol. 57, 1988, pp. 445–450.

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1. Blind equalization with recurrent neural networks using natural gradient;2008 3rd International Symposium on Communications, Control and Signal Processing;2008-03

2. Hybrid HOS-SOS approach for blind equalisation of communication channels;Electronics Letters;2005

3. Analysis of Modified “Bussgang” Algorithms (MBAs) for Channel Equalization;IEEE Transactions on Circuits and Systems I: Regular Papers;2004-08

4. Fast Fixed-Point Neural Blind-Deconvolution Algorithm;IEEE Transactions on Neural Networks;2004-03

5. Neural independent component analysis by ‘maximum-mismatch’ learning principle;Neural Networks;2003-10

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