FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling

Authors:
Chang-Min Kim;Hyung-Min Park;Taesu Kim;Yoon-Kyung Choi;Soo-Young Lee
Affiliations:
Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea;-;-;-;-
Venue:
IEEE Transactions on Neural Networks
Year:
2003

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Digital Signal Processing

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Abstract

An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.