Chaotic time-series prediction and the relocating-LMS (RLMS) algorithm for radial basis function networks

SARANLI A., BAYKAL B.

8th European Signal Processing Conference, EUSIPCO 1996, Trieste, İtalya, 10 - 13 Eylül 1996 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Trieste
  • Basıldığı Ülke: İtalya
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this study, the problem of real-time chaotic time- series prediction using Radial Basis Function Networks is addressed. The performance of a number of train ing methods based either on supervised error correction or on adaptive clustering techniques are investigated. Some performance drawbacks due to their exclusive us age are pointed out and a new algorithm combining their desirable properties is presented. The proposed Relocating-LMS algorithm is compared with t he exist ing methods on a chaotic time-series produced by the Mackey-Glass Equation and is further tested on a se ries generated by the Logistic Map function, leading to encouraging results.