{"title":"量子启发二进制神经网络算法","authors":"O. Patel, Aruna Tiwari","doi":"10.1109/ICIT.2014.29","DOIUrl":null,"url":null,"abstract":"In this paper a novel quantum based binary neural network learning algorithm is proposed. It forms three layer network structure. The proposed method make use of quantum concept for updating and finalizing weights of the neurons and it works for two class problem. The use of quantum concept form an optimized network structure. Also performance in terms of number of neurons and classification accuracy is improved. Same is compared with a quantum-based algorithm for optimizing artificial neural networks algorithm (QANN). It is found that there is improvement in the form of number of neurons at hidden layer, number of iterations, training accuracy and generalization accuracy.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"52 1","pages":"270-274"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Quantum Inspired Binary Neural Network Algorithm\",\"authors\":\"O. Patel, Aruna Tiwari\",\"doi\":\"10.1109/ICIT.2014.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a novel quantum based binary neural network learning algorithm is proposed. It forms three layer network structure. The proposed method make use of quantum concept for updating and finalizing weights of the neurons and it works for two class problem. The use of quantum concept form an optimized network structure. Also performance in terms of number of neurons and classification accuracy is improved. Same is compared with a quantum-based algorithm for optimizing artificial neural networks algorithm (QANN). It is found that there is improvement in the form of number of neurons at hidden layer, number of iterations, training accuracy and generalization accuracy.\",\"PeriodicalId\":6486,\"journal\":{\"name\":\"2014 17th International Conference on Computer and Information Technology (ICCIT)\",\"volume\":\"52 1\",\"pages\":\"270-274\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 17th International Conference on Computer and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2014.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 17th International Conference on Computer and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2014.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper a novel quantum based binary neural network learning algorithm is proposed. It forms three layer network structure. The proposed method make use of quantum concept for updating and finalizing weights of the neurons and it works for two class problem. The use of quantum concept form an optimized network structure. Also performance in terms of number of neurons and classification accuracy is improved. Same is compared with a quantum-based algorithm for optimizing artificial neural networks algorithm (QANN). It is found that there is improvement in the form of number of neurons at hidden layer, number of iterations, training accuracy and generalization accuracy.