{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T18:46:13Z","timestamp":1648925173190},"reference-count":11,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2000,1,1]],"date-time":"2000-01-01T00:00:00Z","timestamp":946684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2000,1]]},"DOI":"10.1016\/s0893-6080(99)00101-x","type":"journal-article","created":{"date-parts":[[2002,7,25]],"date-time":"2002-07-25T22:54:47Z","timestamp":1027637687000},"page":"125-132","source":"Crossref","is-referenced-by-count":11,"title":["Training neural networks to be insensitive to weight random variations"],"prefix":"10.1016","volume":"13","author":[{"given":"M.","family":"Conti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Orcioni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C.","family":"Turchetti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/S0893-6080(99)00101-X_BIB10","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1162\/neco.1992.4.4.494","article-title":"Exact calculation of the Hessian matrix for the multilayer perceptron","volume":"4","author":"Bishop","year":"1992","journal-title":"Neural Computation"},{"issue":"1","key":"10.1016\/S0893-6080(99)00101-X_BIB5","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1109\/72.105422","article-title":"Sensitivity analysis of multilayer perceptron with differentiable activation functions","volume":"3","author":"Choi","year":"1992","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"6","key":"10.1016\/S0893-6080(99)00101-X_BIB2","first-page":"1069","article-title":"A class of Neural Networks based on approximate identity for analog IC's hardware implementation","volume":"E77-A","author":"Conti","year":"1994","journal-title":"IEICE Transactions on Fundamentals"},{"key":"10.1016\/S0893-6080(99)00101-X_BIB8","unstructured":"Conti, M., Orcioni, S., & Turchetti, C. (1995). An efficient algorithm for learning artificial neural networks subject to weight tolerances. In: Proceedings of the 1995 International Symposium on Artificial Neural Networks, ISANN95, December 18\u201320, 1995, Hsinchu, Taiwan (pp. BB25\u2013BB30)."},{"key":"10.1016\/S0893-6080(99)00101-X_BIB1","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/BF02551274","article-title":"Approximation by superimposition of a sigmoidal function","volume":"2","author":"Cybenko","year":"1989","journal-title":"Mathematical Control Systems Signals"},{"issue":"4","key":"10.1016\/S0893-6080(99)00101-X_BIB7","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1142\/S0129065795000263","article-title":"Can deterministic penalty terms model the effect of synaptic weight noise on network fault-tolerance?","volume":"6","author":"Edwards","year":"1995","journal-title":"International Journal of Neural Systems"},{"issue":"1","key":"10.1016\/S0893-6080(99)00101-X_BIB4","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1109\/72.80296","article-title":"Back-propagation learning and nonidealities in analog neural network hardware","volume":"2","author":"Frye","year":"1991","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"3","key":"10.1016\/S0893-6080(99)00101-X_BIB3","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/4.209997","article-title":"Design and characterization of analog VLSI neural network modules","volume":"28","author":"Godwa","year":"1993","journal-title":"IEEE Journal of Solid State Circuits"},{"issue":"5","key":"10.1016\/S0893-6080(99)00101-X_BIB6","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1109\/72.317730","article-title":"Enhanced MLP performance and fault tolerance resulting from synaptic weight noise during training","volume":"5","author":"Murray","year":"1994","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"5","key":"10.1016\/S0893-6080(99)00101-X_BIB9","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/81.232577","article-title":"Learning neural networks with respect to tolerances to weight errors","volume":"40","author":"Ruzicka","year":"1995","journal-title":"IEEE Transactions on CAS-I"},{"issue":"12","key":"10.1016\/S0893-6080(99)00101-X_BIB11","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1109\/81.340846","article-title":"Approximate identity neural networks for analog synthesis of nonlinear dynamical systems","volume":"41","author":"Turchetti","year":"1994","journal-title":"IEEE Transactions on Circuits and Systems-I"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S089360809900101X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S089360809900101X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T17:29:14Z","timestamp":1555608554000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S089360809900101X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2000,1]]},"references-count":11,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2000,1]]}},"alternative-id":["S089360809900101X"],"URL":"https:\/\/doi.org\/10.1016\/s0893-6080(99)00101-x","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2000,1]]}}}