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A novel method called PSO optimized hidden-layer visible deep stacking network (PHVDSN) is proposed for feature extraction and recognition of motor imagery electroencephalogram (EEG) signals. A prior knowledge is introduced into the intermediate layer of deep stacking network (DSN) and the hidden nodes are expanded by the unsupervised training of restricted Boltzmann machine (RBM) for the parameter...
To study the effect of different number of diffusion gradient directions (NDGD) of diffusion tensor imaging (DTI) on dispersion degree of fractional anisotropy (FA) values and its signal noise ratio (SNR) for adult brain tissues. Eight health volunteers were imaged by a 1.5T magnetic resonance scanner with different NDGD (6, 9, 12, 15, 20, 25, and 30 noncollinear) respectively, and seven FA maps associated...
In this paper we propose a digital watermarking algorithm based on balanced multi-wavelet. According to the characteristics of the balanced multi-wavelet, a visual masking model based on single wavelet transformation and the JND (just noticeable difference) formula are analyzed and modified, then the improved visual model and the modified JND formula for balanced multi-wavelet transformation are obtained...
A method of multi-text fusion computation is discussed in this paper which extracts the common features automatically by using text fusion. When search the information in a special domain, the keywords are picked out by using relative sample muster fusion, keywords' flexible control is realized by regulating the sample muster, in final search- space's conditioning control and result tropism are achieved...
Time series clustering is an important task in time series data mining. Compared to traditional clustering problems, time series clustering poses additional difficulties. The unique structure of time series makes many traditional clustering methods unable to apply directly. This paper presents a novel feature-based approach to time series clustering, which first converts the raw time series data into...
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