{"title":"一种电流模式CMOS多层感知器芯片","authors":"G. M. Bo, D. Caviglia, M. Valle","doi":"10.1109/MNNFS.1996.493778","DOIUrl":null,"url":null,"abstract":"An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi layer perceptron (MLP) network with 64 inputs, 64 hidden neurons and 10 outputs. The computational cells have been designed by using the current mode approach and weak inversion biased MOS transistors to reduce the occupied area and power consumption. The processing delay is less than 2 /spl mu/s and the total average power consumption is around 200 mW. This is equivalent to a computational power of about 2.5/spl times/10/sup 9/ connections per second. The chip can be employed in a chip-in-the-loop neural architecture.","PeriodicalId":151891,"journal":{"name":"Proceedings of Fifth International Conference on Microelectronics for Neural Networks","volume":"43 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A current mode CMOS multi-layer perceptron chip\",\"authors\":\"G. M. Bo, D. Caviglia, M. Valle\",\"doi\":\"10.1109/MNNFS.1996.493778\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi layer perceptron (MLP) network with 64 inputs, 64 hidden neurons and 10 outputs. The computational cells have been designed by using the current mode approach and weak inversion biased MOS transistors to reduce the occupied area and power consumption. The processing delay is less than 2 /spl mu/s and the total average power consumption is around 200 mW. This is equivalent to a computational power of about 2.5/spl times/10/sup 9/ connections per second. The chip can be employed in a chip-in-the-loop neural architecture.\",\"PeriodicalId\":151891,\"journal\":{\"name\":\"Proceedings of Fifth International Conference on Microelectronics for Neural Networks\",\"volume\":\"43 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Fifth International Conference on Microelectronics for Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MNNFS.1996.493778\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Fifth International Conference on Microelectronics for Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MNNFS.1996.493778","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi layer perceptron (MLP) network with 64 inputs, 64 hidden neurons and 10 outputs. The computational cells have been designed by using the current mode approach and weak inversion biased MOS transistors to reduce the occupied area and power consumption. The processing delay is less than 2 /spl mu/s and the total average power consumption is around 200 mW. This is equivalent to a computational power of about 2.5/spl times/10/sup 9/ connections per second. The chip can be employed in a chip-in-the-loop neural architecture.