On-line Successive Synthesis of Wavelet Networks
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal
Related Research Unit(s)
|Journal / Publication||Neural Processing Letters|
|Publication status||Published - 1998|
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-0032046204&origin=recordpage|
An approach for the on-line synthesis of wavelet network using recursive least square (RLS) training is proposed. It is based on the concept of successive approximation of the system function to be learned. By using the Bayesian Information Criteria (BIC), the optimal number of wavelets is determined in the training process. Simulation results show that the proposed approach can approximate the unknown system function satisfactorily. Moreover, it can adapt to the changes in system parameters that off-line training cannot.
- Network synthesis, Recursive least square training, Wavelet network