摘要
Cluster analysis is a method often used in pattern recognition. With the aid of the signal processing and the learning of the computer, disfferent samples can be classifeid and recognized in a dimension reduction space of the characteristics because of the differences of their character -istics. To realize dimension reduction transformation, a nonlinear mapping method was discussed in this paper. To prove that the cluster analysis is suitable for quite different fields of samples, in this paper some ship noises and some EEG as the samples belong to two different fields are classified and shown. And it is worthy to point out that an adaptive step size expression of adaptive iteration deduced here will also be effective if it is applied to speed adaptive algorithm convergence of general signal processing.
Cluster analysis is a method often used in pattern recognition. With the aid of the signal processing and the learning of the computer, disfferent samples can be classifeid and recognized in a dimension reduction space of the characteristics because of the differences of their character -istics. To realize dimension reduction transformation, a nonlinear mapping method was discussed in this paper. To prove that the cluster analysis is suitable for quite different fields of samples, in this paper some ship noises and some EEG as the samples belong to two different fields are classified and shown. And it is worthy to point out that an adaptive step size expression of adaptive iteration deduced here will also be effective if it is applied to speed adaptive algorithm convergence of general signal processing.
基金
The project supported by National Natural Science Foundation of China
