{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T07:44:30Z","timestamp":1648799070504},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"supp01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[1992,1]]},"abstract":"<jats:p> The information coming into a module, which is part of a global system, will in general require pre-processing that consists in building a representation \u2014 expressing it in a new code \u2014 convenient to the task to be performed by this particular module. This information, coming either from the environment or from another module in the system, will undergo this operation in what we can call an encoder. In this work we describe our results for a perceptron architecture viewed as an encoder, using encoding principles based on Information Theory. In particular we show how to evaluate the information capacity and the typical mutual information, quantities which are relevant to analize the different criteria used to code the information. Techniques taken from statistical mechanics of disordered systems will be shown to be useful for these calculations. <\/jats:p>","DOI":"10.1142\/s012906579200036x","type":"journal-article","created":{"date-parts":[[2004,11,24]],"date-time":"2004-11-24T03:29:42Z","timestamp":1101266982000},"page":"41-50","source":"Crossref","is-referenced-by-count":1,"title":["INFORMATION PROCESSING BY A PERCEPTRON"],"prefix":"10.1142","volume":"03","author":[{"given":"J.-P.","family":"Nadal","sequence":"first","affiliation":[{"name":"Laboratoire de Physique Statistique, Ecole Normale Sup\u00e9rieure, 24, rue Lhomond, F-75231 Paris Cedex 05, France"}]},{"given":"N.","family":"Parga","sequence":"additional","affiliation":[{"name":"Istituto Superiore di Sanita, Physics Laboratory, INFN Sezione Sanita, Viale Regina Elena 299, 00161 Roma, Italy"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S012906579200036X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T16:22:09Z","timestamp":1565194929000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S012906579200036X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1992,1]]},"references-count":0,"journal-issue":{"issue":"supp01","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1992,1]]}},"alternative-id":["10.1142\/S012906579200036X"],"URL":"https:\/\/doi.org\/10.1142\/s012906579200036x","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[1992,1]]}}}