{"title":"具有状态依赖外部输入的递归神经网络的吸引性分析","authors":"Gang Baol, Kang Li, Zhenyan Song","doi":"10.1109/ICIST55546.2022.9926830","DOIUrl":null,"url":null,"abstract":"This paper introduces a novel kind of discontinu-ous neural networks which are with state-dependent switching external input. The switched external input is defined as a step function with respect to state value. Firstly, we derive a sufficient condition for network state attractivity by dividing the state space according to the swithed external input function and the activation function. At last, one numerical example verifies our results.","PeriodicalId":211213,"journal":{"name":"2022 12th International Conference on Information Science and Technology (ICIST)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Attractivity Analysis for Recurrent Neural Networks with State-dependent External Input\",\"authors\":\"Gang Baol, Kang Li, Zhenyan Song\",\"doi\":\"10.1109/ICIST55546.2022.9926830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a novel kind of discontinu-ous neural networks which are with state-dependent switching external input. The switched external input is defined as a step function with respect to state value. Firstly, we derive a sufficient condition for network state attractivity by dividing the state space according to the swithed external input function and the activation function. At last, one numerical example verifies our results.\",\"PeriodicalId\":211213,\"journal\":{\"name\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIST55546.2022.9926830\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 12th International Conference on Information Science and Technology (ICIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST55546.2022.9926830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Attractivity Analysis for Recurrent Neural Networks with State-dependent External Input
This paper introduces a novel kind of discontinu-ous neural networks which are with state-dependent switching external input. The switched external input is defined as a step function with respect to state value. Firstly, we derive a sufficient condition for network state attractivity by dividing the state space according to the swithed external input function and the activation function. At last, one numerical example verifies our results.