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000000161 001__ 161
000000161 037__ $$aENY-ARTICLE-2008-123
000000161 041__ $$aeng
000000161 100__ $$aKostyla, P
000000161 245__ $$aArtificial Neural Network for Real-Time Estimation of Basic Parameter of Signals
000000161 260__ $$c2008-04-06
000000161 300__ $$a2p
000000161 500__ $$aProceedings of the 7th Int. Conference EEEIC 2008, Cottbus, 5-11.05.2008, pp. 3-4
000000161 520__ $$aThis paper presents for students instructions to using parallel algorithms, which can be implemented by analogue adaptive circuits employing some neural networks principles for estimation of parameters of signals in power system. Algorithms based on the standard least-squares (LS) criteria is proposed. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent optimization algorithm. The corresponding architectures of analogue neuron-like adaptive processors are also shown.
000000161 6531_ $$aEEEIC
000000161 6531_ $$aneural network
000000161 6531_ $$asignal analysis
000000161 8560_ $$fzbigniew.leonowicz@pwr.wroc.pl
000000161 8564_ $$uhttp://zet10.ipee.pwr.wroc.pl/record/161/files/$$zAccess to Fulltext
000000161 909CO $$ooai:zet10.pwr.wroc.pl:161$$pglobal
000000161 980__ $$aARTICLE