A Distortion Free Learning Algorithm for Feedforward BSS and ITS Comparative Study with Feedback BSS
A Distortion Free Learning Algorithm for Feedforward BSS and ITS Comparative Study with Feedback BSS
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DOI：
10.1109/ijcnn.2006.246889
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发表时间：
2006-10
期刊：
影响因子：
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通讯作者：
Akihide Horita;K. Nakayama;A. Hirano;Y. Dejima
中科院分区：
文献类型：
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作者：
Akihide Horita;K. Nakayama;A. Hirano;Y. Dejima
从理论上分析了在时域和频域实现的FF-BSS系统和FB-BSS系统的源分离和信号失真。FF-BSS系统具有一定的自由度，并且会引起一定的信号失真。FB-BSS具有完全分离和无失真的独特解决方案。接下来，推导了FF-BSS系统完全分离和无失真的条件。该条件适用于学习算法。利用语音信号和平稳有色信号对传统的方法和采用所提出的无失真约束的新学习算法进行了计算机仿真。所提出的方法可以大大抑制信号失真，同时保持高的分离性能。FB-BSS系统也表现出良好的性能。基于混频过程中的传输时间差，对FF-BSS系统和FB-BSS系统进行了比较。在FB-BSS系统中，信号源和传感器的位置相当有限。
Source separation and signal distortion are theoretically analyzed for the FF-BSS systems implemented in both the time and frequency domains and the FB-BSS system. The FF-BSS systems have some degree of freedom, and cause some signal distortion. The FB-BSS has a unique solution for complete separation and distortion free. Next, the condition for complete separation and distortion free is derived for the FF-BSS systems. This condition is applied to the learning algorithms. Computer simulations by using speech signals and stationary colored signals are carried out for the conventional methods and the new learning algorithms employing the proposed distortion free constraint. The proposed method can drastically suppress signal distortion, while maintaining high separation performance. The FB-BSS system also demonstrates good performances. The FF-BSS systems and the FB-BSS system are compared based on the transmission time difference in the mixing process. Location of the signal sources and the sensors are rather limited in the FB-BSS system.