tailieunhanh - Báo cáo hóa học: " Design of Low-Cost FPGA Hardware for Real-time ICA-Based Blind Source Separation Algorithm"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Design of Low-Cost FPGA Hardware for Real-time ICA-Based Blind Source Separation Algorithm | EURASIP Journal on Applied Signal Processing 2005 18 3076-3086 2005 C. Charoensak and F. Sattar Design of Low-Cost FPGA Hardware for Real-time ICA-Based Blind Source Separation Algorithm Charayaphan Charoensak School of Electrical and Electronic Engineering Nanyang Technological University Nanyang Avenue Singapore 639798 Email ecchara@ Farook Sattar School of Electrical and Electronic Engineering Nanyang Technological University Nanyang Avenue Singapore 639798 Email efsattar@ Received 29 April 2004 Revised 7 January 2005 Blind source separation BSS of independent sources from their convolutive mixtures is a problem in many real-world multisensor applications. In this paper we propose and implement an efficient FPGA hardware architecture for the realization of a real-time BSS. The architecture can be implemented using a low-cost FPGA field programmable gate array . The architecture offers a good balance between hardware requirement gate count and minimal clock speed and separation performance. The FPGA design implements the modified Torkkola s BSS algorithm for audio signals based on ICA independent component analysis technique. Here the separation is performed by implementing noncausal filters instead of the typical causal filters within the feedback network. This reduces the required length of the unmixing filters as well as provides better separation and faster convergence. Description of the hardware as well as discussion of some issues regarding the practical hardware realization are presented. Results of various FPGA simulations as well as real-time testing of the final hardware design in real environment are given. Keywords and phrases ICA BSS codesign FPGA. 1. INTRODUCTION Blind signal separation or BSS refers to performing inverse channel estimation despite having no knowledge about the true channel or mixing filter 1 2 3 4 5 . BSS technique has been found to be very useful in many real-world multisensor applications such as blind .