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A new face recognition algorithm based on fusion of 2DPCA and Gabor features with DCV method is presented. The method first extracts features by employed 2DPCA and Gabor wavelets respectively. And the `z-score' method is applied to normalize the 2DPCA feature and Gabor feature. Then the 2DPCA feature is combined with the Gabor feature by the append rule. In order to overcome the small sample size...
A promising trend of image processing is to incorporate some knowledge on human visual system. In this paper, we propose an improved pulse coupled neural network (PCNN) for image enhancement. We apply the passive membrane equation, which is known as a model for describing the ON-OFF opponent property of the receptive fields of the retinal ganglion cells, as the linking field to modulate feeding field...
The study of early intelligent obstacle diagnosis for large-sized mechanical equipment is of momentous social significance and far-reaching economic importance. The equipment directly influences production safety for enterprises, and concern economic efficiencies. So it is very important for the induction motor to guarantee non-failure work time and the whole cutting process without fault. The early-term...
Extreme learning machine (ELM) is an easy-to use and effective learning algorithm of single-hidden layer feed-forward neural networks (SLFNs). The classical learning algorithm in neural network, e. g. backpropagation, requires setting several user-defined parameters and may get into local minimum. However, ELM only requires setting the number of hidden neurons and the activation function. It does...
Soft defined radio is again the research issue because of cognitive radio, Modulation type recognition (MTR) is the key issue of the soft defined radio, in this paper, a new MTR method based on the wavelet support vector machine (WSVM) has been proposed, we derive the WSVM kernel function and utilize it to classify the modulation type, the results show when the SNR threshold for the modulation scheme...
In this study, we assessed the large sample population of patients with chronic gastritis based on three methods with supervised learning function, i.e., the regression analysis, BP neural network and support vector machine. On basis of the results, we constructed the diagnostic models to predict the types of traditional Chinese medicine (TCM) syndromes of chronic gastritis, and compared the correct...
It makes diagnosis of induce motor very complex that itpsilas fault omens and feature is non-linear. It is more difficult to get earlier period fault information and realize function reflection between information and running state. As the knowledge limitation and parameter change in running of induce motor, the gray prediction combined with the nerve network is used to predict feature parameter and...
This paper investigates the stability of a class of delayed neural networks with impulses. By means of Lyapunov direct method, the new sufficient conditions for exponential stability of the systems are derived.
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