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Linear system identification using the TLS EXIN neuron
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DOI：10.1016/S0925-2312(98)00115-5.png)
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Abstract
En 中文
The paper presents a neural approach for the parameter estimation of adaptive IIR filters for linear system identification. It is based on a novel neuron, the TLS EXIN neuron, capable of resolving the TLS problem present in this kind of estimation, where noisy errors affect not only the observation vector but also the data matrix. After a survey of other techniques far solving such parameters estimations, the TLS EXIN neuron is compared both theoretically and numerically with the former techniques, resulting in improved performance. Moreover, it is also proved that the TLS EXIN neuron permits some powerful acceleration techniques, unlike the other approaches. These results are also shown numerically. (C) 1999 Elsevier Science B.V. All rights reserved.
Keywords:
IIR filters
TLS EXIN neuron
linear system identification
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6.5
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2.5W
Citations:
6.5W
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Neural network approach to the TLS linear prediction frequency estimation problem.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
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