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This paper presents an efficient and reconfigurable co-processor to calculate Mahalanobis distance, which is the most computation-intensive part in the GMM (Gaussian Mixture Models)-based classifier. The Mahalanobis distance's calculation is divided into three parts (vector-vector subtraction, matrix-vector multiplication, and vector-vector multiplication) and these three parts can operate in a parallel...
Model-based clustering is one of the most important ways for time series data mining. However, the process of clustering may encounter several problems. In this paper, a novel clustering algorithm of time-series which incorporates recursive hidden Markov model(HMM) training is proposed. Our contributions are as follows: 1) We recursively train models and use these model information in the process...
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