On a dynamic wavelet network and its modeling application

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Atıf İçin Kopyala

Becerikli Y., Oysal Y., Konar A.

ARTIFICAIL NEURAL NETWORKS AND NEURAL INFORMATION PROCESSING - ICAN/ICONIP 2003, cilt.2714, ss.710-718, 2003 (SCI-Expanded)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 2714
• Basım Tarihi: 2003
• Doi Numarası: 10.1007/3-540-44989-2_85
• Dergi Adı: ARTIFICAIL NEURAL NETWORKS AND NEURAL INFORMATION PROCESSING - ICAN/ICONIP 2003
• Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
• Sayfa Sayıları: ss.710-718
• Anadolu Üniversitesi Adresli: Hayır

Özet

This study presents a nonlinear dynamical system modeling with dynamic wavelet networks (DWNs). Wavelet is widely used in processing of signals and data. It has been also shown that wavelet can be effectively used in nonlinear system modeling. For this, dynamic wavelet networks (DWNs) structure based on Hoppfield networks has been developed. DWN has a lag dynamic, non orthogonal mother wavelets as activation function and interconnection weights. Network weights are adjusted based on supervised training. With fast training algorithms (quasi-Newton methods), wavelet networks are trained. In this paper, Mexican Hat wavelet. First, a phase-portraits based example is given. For this, it has been shown that DWN has chaos properties. The last, a dynamical system with discrete-event is modeled using DWN. There is a localization property at discrete-event instant for time-frequency in this example.