{"title":"具有直接和交叉前向连接的多层神经网络分析","authors":"S. Placzek, B. Adhikari","doi":"10.3233/FI-2014-1073","DOIUrl":null,"url":null,"abstract":"Artificial Neural Networks are of much interest for many practical reasons. As of today, they are widely implemented. Of many possible ANNs, the most widely used one is the back-propagation model with direct connection. In this model the input layer is fed with input data and each subsequent layers are fed with the output of preceding layer. This model can be extended by feeding the input data to each layer. This article argues that this new model, named Cross Forward Connection, is optimal than the widely used Direct Connection.","PeriodicalId":286395,"journal":{"name":"International Workshop on Concurrency, Specification and Programming","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Analysis of Multilayer Neural Networks with Direct and Cross-Forward Connection\",\"authors\":\"S. Placzek, B. Adhikari\",\"doi\":\"10.3233/FI-2014-1073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial Neural Networks are of much interest for many practical reasons. As of today, they are widely implemented. Of many possible ANNs, the most widely used one is the back-propagation model with direct connection. In this model the input layer is fed with input data and each subsequent layers are fed with the output of preceding layer. This model can be extended by feeding the input data to each layer. This article argues that this new model, named Cross Forward Connection, is optimal than the widely used Direct Connection.\",\"PeriodicalId\":286395,\"journal\":{\"name\":\"International Workshop on Concurrency, Specification and Programming\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Concurrency, Specification and Programming\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/FI-2014-1073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Concurrency, Specification and Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/FI-2014-1073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Multilayer Neural Networks with Direct and Cross-Forward Connection
Artificial Neural Networks are of much interest for many practical reasons. As of today, they are widely implemented. Of many possible ANNs, the most widely used one is the back-propagation model with direct connection. In this model the input layer is fed with input data and each subsequent layers are fed with the output of preceding layer. This model can be extended by feeding the input data to each layer. This article argues that this new model, named Cross Forward Connection, is optimal than the widely used Direct Connection.