Title :
Complexity issues in synchronisation
Abstract :
In this paper, we look at synchronization over a finite window of data from a computational complexity point of view. The setting is purely in discrete time. It is shown that for polynomial systems the computational complexity of a readily available global Newton algorithm adapted to identify the finite trajectory of the dynamical system´s state over the observation window scales in a polynomial manner in the dimension of the system state and the degree of the polynomials required to describe the models. Moreover, this algorithm has good robustness properties with respect to measurement errors and model errors. Simulation results are included
Keywords :
Newton method; chaos; computational complexity; discrete time systems; polynomials; synchronisation; telecommunication security; chaotic dynamic systems; computational complexity; discrete time systems; finite trajectory; global Newton algorithm; measurement errors; model errors; polynomial systems; robustness; secure communication; synchronization; Australia; Chaotic communication; Computational complexity; Context; Neural networks; Newton method; Polynomials; Robustness; State-space methods; Time factors;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980189