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

Sad570

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

離開(kāi)可分裂

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

daredevil

網(wǎng)絡(luò)添麻煩

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

虛假

foppish

煞費(fèi)苦心

TOXIC

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

condescend

豐滿中國(guó)