{"title":"One-neuron circuitry for carry generation in a 4-bit adder","authors":"C. Yao, A. Willson","doi":"10.1109/IJCNN.1992.227173","DOIUrl":null,"url":null,"abstract":"It is shown how a parallel carry generator circuit using the sigmoidal (input/output) characteristic of a neuron can be employed in a carry select adder architecture. The circuit performs the carry generation function in parallel with the generation of the summation bits. By examining the input-output pairs of a digital adder it is found that the generation of its output carry is a most basic mapping of a neural network, the mapping of a single neuron. The realization of this mapping by a transistor circuit is described. Performance results derived from SPICE simulations of the proposed circuit, using 1.2- mu m CMOS technology, are also given.<<ETX>>","PeriodicalId":286849,"journal":{"name":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1992.227173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is shown how a parallel carry generator circuit using the sigmoidal (input/output) characteristic of a neuron can be employed in a carry select adder architecture. The circuit performs the carry generation function in parallel with the generation of the summation bits. By examining the input-output pairs of a digital adder it is found that the generation of its output carry is a most basic mapping of a neural network, the mapping of a single neuron. The realization of this mapping by a transistor circuit is described. Performance results derived from SPICE simulations of the proposed circuit, using 1.2- mu m CMOS technology, are also given.<>
它展示了如何利用神经元的s型(输入/输出)特性的并行进位发生器电路可以用于进位选择加法器结构。该电路与求和位的生成并行地执行进位生成功能。通过研究数字加法器的输入输出对,发现其输出进位的生成是神经网络最基本的映射,即单个神经元的映射。文中描述了用晶体管电路实现这种映射的方法。本文还给出了采用1.2 μ m CMOS技术的电路的SPICE仿真结果。