TY - JOUR
T1 - Discrete-time domain poles zeros identification using back propagation neural networks
AU - Chow, T. W S
AU - Yam, Y. F.
PY - 1991
Y1 - 1991
N2 - This paper describes a back propagation neural network applying to poles zeros identification in discrete time domain. Traditional Recursive Least Squares (RLS) algorithm is time consuming and sensitive to noise. Neural networks possess massive parallel processing capability and noise immunity, the time and noise constraints can be eliminated. The results are encouraging and demonstrate that neural networks offer new promising directions towards solving system identification problems radically.
AB - This paper describes a back propagation neural network applying to poles zeros identification in discrete time domain. Traditional Recursive Least Squares (RLS) algorithm is time consuming and sensitive to noise. Neural networks possess massive parallel processing capability and noise immunity, the time and noise constraints can be eliminated. The results are encouraging and demonstrate that neural networks offer new promising directions towards solving system identification problems radically.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0026381508&origin=recordpage
M3 - RGC 22 - Publication in policy or professional journal
SN - 0537-9989
SP - 215
EP - 218
JO - IEE Conference Publication
JF - IEE Conference Publication
T2 - 6th International Conference on Digital Processing of Signals in Communications
Y2 - 2 September 1991 through 6 September 1991
ER -