Blind source separation technique is an important branch in blind signal processing field.
盲源分离技术是盲信号处理领域的一个重要的分支。
Blind signal processing is a fundamental signal processing technology aimed at retrieving a system's unknown information from its output only.
盲信号处理是信号处理的一种基础技术，它要解决仅仅依靠输出信号去重现整个传输系统的问题。
Blind identification and equalization has been received considerable attention recently in communication and signal processing, the main work of this dissertation is on this topic.
近年来，盲信道辨识与均衡在通信和信号处理领域已经受到普遍关注。
We apply sparse signal processing to QAM blind equalization.
我们将稀疏信号处理应用于QAM盲均衡。
Blind source separation is an efficient method to recover source signals from observed signals, and it has become an attractive research in the field of signal processing.
盲源分离是从观测信号中恢复源信号的一种有效方法，目前已成为信号处理领域的研究热点。
Blind source separation is a promising technique for signal processing, which has such features as blind information processing and waveform restoral.
盲源分离是一种很有希望的信号处理技术，具有独特的盲信息处理和波形保持能力。
Through some further simplification and improvement, a real time processing system embedded on a DSP board for blind signal separation is presented.
通过对该盲分离算法进一步简化与改进，设计了一种适合于语音盲分离的实时处理系统，并且使其在DSP系统上得以实现。
Method for Blind Separation of sources is the Modem Processing Method for Signal.
盲源分离方法是近年来出现的一种先进的信号处理方法。
To obtain clearer desired signal under multi-speaker environment, the time-frequency masking effect is used in post-processing of speech enhancement using blind source separation.
本文将时频掩蔽效应引入盲源分离语音增强系统中，给出一种基于时频掩蔽效应和盲源分离的语音增强方法，并将其与期望最大化方法进行了性能比较。
To obtain clearer desired signal under multi-speaker environment, the time-frequency masking effect is used in post-processing of speech enhancement using blind source separation.
本文将时频掩蔽效应引入盲源分离语音增强系统中，给出一种基于时频掩蔽效应和盲源分离的语音增强方法，并将其与期望最大化方法进行了性能比较。
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