caa a22 4500 477072976 CHVBK 20180405111431.0 cr unu---uuuuu 170330e19961201xx s 000 0 eng 10.1007/BF01413821 doi (NATIONALLICENCE)springer-10.1007/BF01413821 Osowski S. Institute of the Theory of Electrical Engineering, and Electrical Measurements, Technical University, pl. Politechniki 1, 00-661, Warsaw, Poland aut Multilayer volterra filter and its applications [Elektronische Daten] [S. Osowski] The paper presents the application of the successive linearisation to the neural network implementation of the Volterra filter. Applying the signal flow graph approach, the new learning rules for adaptation of weights of the multilayer network structure obtained are given. The multilayer structure presented is applied to signal processing, including identification of the parameters of the plant, noise cancelling and signal prediction. The results of the simulation of the filter in these three basic application modes are presented and discussed. Springer-Verlag London Limited, 1996 Neural network nationallicence Signal flow graph nationallicence Simulation nationallicence Volterra filter nationallicence Neural Computing & Applications Springer-Verlag 4/4(1996-12-01), 228-236 0941-0643 4:4<228 1996 4 521 https://doi.org/10.1007/BF01413821 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01413821 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Osowski S. Institute of the Theory of Electrical Engineering, and Electrical Measurements, Technical University, pl. Politechniki 1, 00-661, Warsaw, Poland aut NATIONALLICENCE 773 0- Neural Computing & Applications Springer-Verlag 4/4(1996-12-01), 228-236 0941-0643 4:4<228 1996 4 521 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer