Title :
Implementation of Infomax ICA Algorithm for Blind Source Separation
Author :
Moreno, L. Noe Oliva ; Arce, Miguel A Alemán ; Lamont, Jair García
Author_Institution :
Escuela Super. de Comput., Inst. Politec. Nac., Mexico City
fDate :
Sept. 30 2008-Oct. 3 2008
Abstract :
In this paper, is use a field programmable gate array (FPGA) to implement an information-maximization (Infomax) algorithm to blind source separation (BSS). In this work, we show the neural network architecture for several inputs and the performance of its hardware implementation. We achieve simulations results similar as estimated in MATLAB. Some simulations results using VHDL are presented using music and voice recorded. The study of performance is made in a net of 2 times 2.
Keywords :
blind source separation; field programmable gate arrays; hardware description languages; independent component analysis; mathematics computing; neural net architecture; Infomax ICA algorithm; MATLAB; VHDL; blind source separation; field programmable gate array; information-maximization algorithm; music recording; neural network architecture; voice recording; Biosensors; Blind source separation; Entropy; Field programmable gate arrays; Independent component analysis; MATLAB; Mutual information; Neural networks; Signal processing algorithms; Source separation; BSS; FPGA; ICA; Neural Networks;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08
Conference_Location :
Morelos
Print_ISBN :
978-0-7695-3320-9
DOI :
10.1109/CERMA.2008.37