- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
Eigenvector Algorithms with Reference Signals for Frequency Domain BSS
Description
This paper describes blind source separation (BSS) problems in the frequency domain using an eigenvector algorithm (EVA) with reference signals. The proposed EVA has such an attractive feature that all source signals are separated simultaneously from their mixtures. This is an advantage against the methods using deflation process (e.g., super-exponential method), because those methods sometimes do not work so as to converge to desired solutions, due to deflation failure. Computer simulation demonstrates the validity of the proposed EVA.