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Application of novel chaotic neural network on Mandarin digital speech recognition


Modeling olfactory neural systems, the KIII model proposed by Freeman exhibits chaotic dynamic characteristics and has potential for pattern recognition. Fuzzy c-means clustering can classify an object to several classes at the same time but with different degrees based on fuzzy sets theory. Based on the KIII model, mandarin digital speech is recognized utilizing the features extracted by the fuzzy c-means clustering. Experimental results show that the KIII model can perform digital speech recognition efficiently and the fuzzy c-means clustering has better performance than the hard k-means clustering.

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