{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:57:01Z","timestamp":1760245021716},"reference-count":4,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2003,8]]},"abstract":"<jats:p> Recently a discrete-time cellular neural network (DT-CNN) is applied to many image processing applications such as compression and reconstruction, recognition and so on. Conventional image processing techniques such as the discrete cosine transformation (DCT) and wavelet transforms work as a simple filter and do not make good use of interpolative dynamics by the feedback A template, which is one of the significant characteristics of a cellular neural network (CNN). If CNN is applied to a filter by an only feedforward B template, one should make a model which consists of digital filters using high speed signal processing modules such as a high speed digital signal processor. This paper describes the nonlinear interpolative effect of the feedback A template, by showing the evaluation of image compression and reconstruction. <\/jats:p>","DOI":"10.1142\/s0218126603001008","type":"journal-article","created":{"date-parts":[[2003,12,5]],"date-time":"2003-12-05T09:20:48Z","timestamp":1070616048000},"page":"505-518","source":"Crossref","is-referenced-by-count":11,"title":["NONLINEAR INTERPOLATIVE EFFECT OF FEEDBACK TEMPLATE  FOR IMAGE PROCESSING BY DISCRETE-TIME CELLULAR NEURAL NETWORK"],"prefix":"10.1142","volume":"12","author":[{"given":"NOBUAKI","family":"TAKAHASHI","sequence":"first","affiliation":[{"name":"Department of Electrical  and Electronics Engineering, Sophia University, 7-1, Kioi-cho, Chiyoda-ku, Tokyo 102-8554, Japan"},{"name":"IBM Research, Tokyo Research  Laboratory, IBM Japan, Ltd., 1623-14, Shimotsuruma,  Yamato-shi, Kanagawa 242-8502, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TSUYOSHI","family":"OTAKE","sequence":"additional","affiliation":[{"name":"Department of Electrical  and Electronics Engineering, Sophia University, 7-1, Kioi-cho, Chiyoda-ku, Tokyo 102-8554, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"MAMORU","family":"TANAKA","sequence":"additional","affiliation":[{"name":"Department of Electrical  and Electronics Engineering, Sophia University, 7-1, Kioi-cho, Chiyoda-ku, Tokyo 102-8554, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1109\/31.7600"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1109\/31.7601"},{"key":"rf3","first-page":"1387","volume":"77","author":"Tanaka M.","journal-title":"IEICE Trans. Fundamentals"},{"key":"rf8","volume-title":"Neural Network and Circuit","author":"Tanaka M.","year":"1999"}],"container-title":["Journal of Circuits, Systems and Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218126603001008","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T03:45:54Z","timestamp":1565149554000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218126603001008"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,8]]},"references-count":4,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2003,8]]}},"alternative-id":["10.1142\/S0218126603001008"],"URL":"https:\/\/doi.org\/10.1142\/s0218126603001008","relation":{},"ISSN":["0218-1266","1793-6454"],"issn-type":[{"value":"0218-1266","type":"print"},{"value":"1793-6454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,8]]}}}