Description: Blind sound source from the independence of the starting signal! Proposed a new mixed-signal blind sound source separation method: This method is based on joint probability distribution of signal statistics! Use of signal joint probability of directional derivative entropy minimum get the best rotation angle ! finally realize blind signal separation: with the fast independent component analysis and neural network methods! This method does not require iterative calculation: the introduction of a new blind signal separation method of sound source on the bearing test bed of mixed sound signals to identify! to motor and rolling bearings separated voice! which can accurately identify the mechanical failure
- [labview_EMD] - PC EMD prepared by the decomposition pro
- [weightcenter] - The focus of pressure sensor measurement
- [InfomaxAlgorithm] - Infomax Algorithm for Blind Signal Separ
- [prdemo] - It contains matlab source code, includin
- [ICALABSPv2_2] - ICALAB for Signal Processing Toolbox for
- [bbs1] - Blind Signal Analysis
- [ICA2] - Fourth-order cumulant-based signal chara
- [1002] - Equipment condition monitoring and fault
- [s1] - Use of natural gradient algorithm, simul
- [CFBTest] - Expert System Clips and VC mixture of pr
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一种新的盲声源信号分离方法及其应用.pdf
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