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In contrast with previous studies, this paper starts from very basic local rules (algorithm) and the required cloning templates are calculated step\u2010by\u2010step. Mathematical techniques of combining<jats:italic>compatible<\/jats:italic>templates are proposed and optimization of the total number of cloning templates, the operating speed and sensitivity is addressed. Finally, the speed and circuit performances are compared with other studies.<\/jats:p>","DOI":"10.1002\/cta.4490220505","type":"journal-article","created":{"date-parts":[[2007,7,2]],"date-time":"2007-07-02T11:23:17Z","timestamp":1183375397000},"page":"363-375","source":"Crossref","is-referenced-by-count":2,"title":["An optimized synthesis of a discrete\u2010time cellular neural network for parallel thinning"],"prefix":"10.1002","volume":"22","author":[{"given":"Chun\u2010Ying","family":"Ho","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinsaku","family":"Mori","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2006,12,19]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"crossref","unstructured":"H.Harrer J. A.NossekandF.Zou A learning algorithm for time\u2010discrete cellular neural network Proc. 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