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Titlebook: Intelligent Computing Theories and Application; 13th International C De-Shuang Huang,Vitoantonio Bevilacqua,Phalguni Gu Conference proceedi

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Enhance a Deep Neural Network Model for Twitter Sentiment Analysis by Incorporating User Behavioral r social media detect the sentiment polarity primarily based on the textual content and neglect of other information. Therefore, in this paper, we propose a neural network model that incorporates user behavioral information with a given document (tweet). The neural network used in this paper is Conv
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Topological Structure Analysis of Developmental Spiking Neural Networksreflect the ability of the network to deal with information processing. In this paper, we propose a developmental method for creating recurrent spiking neural networks based on genetic regulatory network model. This research investigates the developmental process of spiking neural networks, and anal
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Exploring the New Application of Morphological Neural Networkson of “one-trial learning”. In this paper we took advantage of morphological associative memory networks to realize the simulation of “one-trial learning” for the first time. Theoretical analysis and simulation experiments show that the method of morphological associative memory networks is a higher
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A Method to Detecting Ventricular Tachycardia and Ventricular Fibrillation Based on Symbol Entropy a proposed a novel method for detection of VF and VT, based on the Wavelet Analysis and Symbol Entropy. The classification accuracy of symbol entropy was 80.03% with SVM, and the classification accuracy of the symbol entropy with wavelet analysis arithmetic was 99.5% with SVM. Fusion algorithm is gre
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