System-level design of low-cost FPGA hardware for real-time ICA-based blind source separation

Blind source separation (BSS) of independent sources from their convolutive mixtures is a common problem in many real world multi-sensor applications. We present a low-cost real-time FPGA (field programmable gate array) implementation of an improved BSS algorithm for audio signals based on ICA (independent component analysis) technique. The separation is performed by implementing noncausal filters instead of causal filters within the feedback network. This reduces the required length of the unmixing filters as well as provides better separation and faster convergence. The result of testing the designed FPGA in real-time is reported.