FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling
Chang‐Min Kim, Hyung‐Min Park, Taesu Kim, Yoon-Kyung Choi, Soo Young Lee · IEEE Transactions on Neural Networks · 2003
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.