Improved Recurrent Neural Network Architecture For Svm Learning

2015 15TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA)(2015)

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摘要
In this paper, we provide an improvement of the circuit implementation of a one-layer recurrent neural network for support vector machine learning in pattern classification and regression. Our goal is to reduce the complexity of this architecture. Numerical example with graphical illustration is given to illuminate our main results.
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关键词
support vector machine,pattern recognition,quadratic programming problem,recurrent neural network,MATLAB Simulink modeling
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