Abstract:
In this paper we propose a pattern recognition method, the improved consecutive Hamming method (ICHAM). It ameliorates the Hamming Method using consecutive data in two aspects: (1) considering the more general case, we compute the Hamming kernel using samples which belong to the class of small variance; (2) The algorithm computing the Hamming Kernel is improved so that it locates in the center of the class that the variance is small.An example, deciding the earthquake-prone regions of Beijing and its vicinity by the ICHAM method is shown in this paper. The results show that the effect of our ICHAM method is better than that of both the binary Hamming method and the original consecutive Hamming method. Tests show that the results are more stable.