Discrete-time domain poles zeros identification using back propagation neural networks
Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 215-218 |
| Journal / Publication | IEE Conference Publication |
| Publication status | Published - 1991 |
Conference
| Title | 6th International Conference on Digital Processing of Signals in Communications |
|---|---|
| Place | United Kingdom |
| City | Loughborough |
| Period | 2 - 6 September 1991 |
Link(s)
Abstract
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.
Citation Format(s)
Discrete-time domain poles zeros identification using back propagation neural networks. / Chow, T. W S; Yam, Y. F.
In: IEE Conference Publication, 1991, p. 215-218.
In: IEE Conference Publication, 1991, p. 215-218.
Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal
