{"title":"用Labview和Matlab编写的正弦函数对称表加法前馈神经网络","authors":"Fadhil A. Ali","doi":"10.5121/IJCSA.2014.4201","DOIUrl":null,"url":null,"abstract":"This work is proposed thefeed forward neural network with symmetric table addition methodto design the neuron synapses algorithm of the sine function approximations, and according to theTaylor series expansion. Matlab code and LabVIEW are used to build and create the neural network , which has been designed and traineddatabase set to improve its performance, and gets the besta global convergence with small value of MSE errors and 97.22% accuracy.","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"75 1","pages":"1-12"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Feed Forward Neural Network For Sine Function With Symmetric Table Addition Method Using Labview And Matlab Code\",\"authors\":\"Fadhil A. Ali\",\"doi\":\"10.5121/IJCSA.2014.4201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work is proposed thefeed forward neural network with symmetric table addition methodto design the neuron synapses algorithm of the sine function approximations, and according to theTaylor series expansion. Matlab code and LabVIEW are used to build and create the neural network , which has been designed and traineddatabase set to improve its performance, and gets the besta global convergence with small value of MSE errors and 97.22% accuracy.\",\"PeriodicalId\":39465,\"journal\":{\"name\":\"International Journal of Computer Science and Applications\",\"volume\":\"75 1\",\"pages\":\"1-12\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Science and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/IJCSA.2014.4201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJCSA.2014.4201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Feed Forward Neural Network For Sine Function With Symmetric Table Addition Method Using Labview And Matlab Code
This work is proposed thefeed forward neural network with symmetric table addition methodto design the neuron synapses algorithm of the sine function approximations, and according to theTaylor series expansion. Matlab code and LabVIEW are used to build and create the neural network , which has been designed and traineddatabase set to improve its performance, and gets the besta global convergence with small value of MSE errors and 97.22% accuracy.
期刊介绍:
IJCSA is an international forum for scientists and engineers involved in computer science and its applications to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the IJCSA are selected through rigorous peer review to ensure originality, timeliness, relevance, and readability.