{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T03:47:25Z","timestamp":1649216845668},"reference-count":22,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2004,8]]},"abstract":"<jats:p> In this work, the development of an Artificial Neural Network (ANN) based soft estimator is reported for the estimation of static-nonlinearity associated with the transducers. Under the realm of ANN based transducer modeling, only two neural models have been suggested to estimate the static-nonlinearity associated with the transducers with quite successful results. The first existing model is based on the concept of a functional link artificial neural network (FLANN) trained with \u03bc-LMS (Least Mean Squares) learning algorithm. The second one is based on the architecture of a single layer linear ANN trained with \u03b1-LMS learning algorithm. However, both these models suffer from the problem of slow convergence (learning). In order to circumvent this problem, it is proposed to synthesize the direct model of transducers using the concept of a Polynomial-ANN (polynomial artificial neural network) trained with Levenberg-Marquardt (LM) learning algorithm. The proposed Polynomial-ANN oriented transducer model is implemented based on the topology of a single-layer feed-forward back-propagation-ANN. The proposed neural modeling technique provided an extremely fast convergence speed with increased accuracy for the estimation of transducer static nonlinearity. The results of convergence are very stimulating with the LM learning algorithm. <\/jats:p>","DOI":"10.1142\/s0129065704001991","type":"journal-article","created":{"date-parts":[[2004,9,13]],"date-time":"2004-09-13T10:17:21Z","timestamp":1095070641000},"page":"237-246","source":"Crossref","is-referenced-by-count":3,"title":["ARTIFICIAL NEURAL NETWORK BASED SOFT ESTIMATOR FOR ESTIMATION OF TRANSDUCER STATIC NONLINEARITY"],"prefix":"10.1142","volume":"14","author":[{"given":"AMAR PARTAP","family":"SINGH","sequence":"first","affiliation":[{"name":"Sant Harchand Singh Longowal Central  Institute of Engineering and Technology (SHSL-CIET), Longowal-148106 (District Sargrur), Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TARA SINGH","family":"KAMAL","sequence":"additional","affiliation":[{"name":"Guru Teg Bahadur Khalsa Institute of Engineering  and Technology, Chhapianwali (Malout)-152107  (District Muktsar), Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"SHAKTI","family":"KUMAR","sequence":"additional","affiliation":[{"name":"Haryana Engineering College,  Jagadhri-135003, Haryana, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1109\/19.2666"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1088\/0957-0233\/2\/2\/002"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1016\/j.sna.2003.10.060"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1109\/19.368082"},{"key":"rf7","volume-title":"Principles of Measurement Systems","author":"Bentley J. 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