Independent signal separation using genetic algorithm

✍ Scribed by Michifumi Yoshioka; Sigeru Omatu

• Book ID: 101293892
• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 248 KB
• Volume: 131
• Category: Article
• ISSN: 0424-7760
• DOI: 10.1002/(sici)1520-6416(200006)131:4<52::aid-eej7>3.0.co;2-t

✦ Synopsis

Growing multimedia systems require more efficient signal separation methods to preserve quality of voice or music recording in a noisy environment. Some signal separation methods are based on minimizing the dependence measure among input signals to separate the noise component since the noise component is usually independent of the other signals. Under such circumstances, we have developed a new method to separate independent signal components which directly minimizes the KullbackLeibler divergence by a genetic algorithm. In this paper, we have improved the method in its separation performance and processing speed. The simulation results show that the proposed method is effective in separating the independent signals.