Frequency domain blind source separation algorithm based on improved sequencing algorithm

A sorting algorithm and blind source separation technology, applied in the field of signal processing, can solve problems such as low robustness, and achieve the effects of strong versatility, low complexity, and strong stability

Active Publication Date: 2013-09-04
HEFEI UNIV OF TECH
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Problems solved by technology

Obviously, the setting of the threshold directly determines whether the algorithm is successful, and the robustness is low

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  • Frequency domain blind source separation algorithm based on improved sequencing algorithm
  • Frequency domain blind source separation algorithm based on improved sequencing algorithm
  • Frequency domain blind source separation algorithm based on improved sequencing algorithm

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with drawings and embodiments. It should be pointed out that the described embodiments are only considered for the purpose of illustration and not limitation of the present invention.

[0034] combine figure 1 The present invention is further described, and a detailed explanation of each detail problem involved in the technical solution of the present invention is given.

[0035] Taking blind source separation of linear mixed signals as an example, a specific implementation routine is given.

[0036] 1) To obtain a mixed signal, the source signal selects two audio signals , , whose waveforms are as Figure 2(a) , 2(b) shown (waveform as Figure 2(a) , 2(b) The two audio signals shown , Specifically, it can be downloaded from the website http: / / bssnesta.webatu.com / software.html). For this two-way sound signal, linear mixing is adopted, and the mixing model is as follows:

[0037] , ...

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Abstract

The invention discloses a frequency domain blind source separation algorithm based on an improved sequencing algorithm. The frequency domain blind source separation algorithm comprises the following steps of acquiring a mixed signal; performing time-frequency transformation on the mixed signal to obtain a frequency domain mixed signal; performing whitening preprocessing on the frequency domain mixed signal; performing complex independent component analysis (ICA) on the preprocessed frequency domain mixed signal at different frequency points to obtain independent components at the frequency points; sequencing the independent components at the frequency points by the improved sequencing algorithm; and performing time-frequency inverse transformation on the sequenced frequency domain signal to obtain a time domain signal. The frequency domain blind source separation algorithm has the advantages of high stability and low complexity; and compared with a frequency domain blind source separation algorithm adopting signal features such as signal arrival angle features and intra-pulse features, the frequency domain blind source separation algorithm disclosed by the invention has the advantage of high generality. An experiment shows that the frequency domain blind source separation algorithm has a better effect of mixing linear mixed signals, convoluted mixed signals and actual mixed signals.

Description

technical field [0001] The invention belongs to the field of signal processing and relates to a frequency domain blind source separation algorithm based on an improved sorting algorithm. Background technique [0002] Blind source separation is a research topic that has developed rapidly in the field of signal processing for two decades. According to the signal classification, there are mainly sound signal blind source separation, chaotic signal blind source separation, electromagnetic signal blind source separation and so on. Since Herault J and Jutten C proposed the independent component analysis problem in the 1980s, a large number of excellent algorithms have emerged. These algorithms can be divided into three categories according to the mixture model: linear mixture, nonlinear mixture and convolutional mixture. Among them, the convolutional mixture model is the closest to the actual problem. At present, there are mainly two algorithms in time domain and frequency doma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/03
Inventor 何怡刚薄祥雷方葛丰樊晓腾
Owner HEFEI UNIV OF TECH
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