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Chaotic AR(1) model estimation

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3 Author(s)
Pantaleon, C. ; Dpto. Ing. Comunicaciones, ETSII y Telecom, Cantabria Univ., Santander, Spain ; Luengo, David ; Santamaria, I.

Chaotic signals generated by iterating nonlinear difference equations may be useful models for many natural phenomena. We propose a family of chaotic models for signal processing applications. The chaotic signals generated by this family of first-order difference equations have autocorrelations identical to stochastic first-order autoregressive (AR) processes. After considering the huge computational cost and the inconsistency of the optimal model estimator in the maximum-likelihood (ML) sense we propose low-cost, suboptimal estimation approaches. Computer simulations show the good performance of the proposed modeling approach

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Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on  (Volume:6 )

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