Title :
Tensor function analysis of quantized chaotic piecewise-affine pseudo-Markov systems. II. Higher order correlations and self-similarity
Author :
Rovatti, Riccardo ; Mazzini, Gianluca
Author_Institution :
CEO-ARCES, Bologna Univ., Italy
fDate :
2/1/2002 12:00:00 AM
Abstract :
For pt. I see ibid., vol. 49, pp. 137-49 (2002).The general approach developed in the companion paper for the statistical analysis of trajectories produced by a class of chaotic systems generalizing the classical view of piecewise-affine Markov maps is here applied to the computation of higher order correlations. For any given order m, a procedure is given to write a closed form expression in the z-transformed domain for the mth dimensional tensor encoding the contribution of the system dynamics to the correlation functions of that order. After having defined and discussed a suitable generalization of the concept of second-order self-similarity, we finally use this general procedure to show that simple chaotic maps may exhibit highly nontrivial behaviors also in their higher order statistics
Keywords :
Markov processes; Z transforms; chaos; correlation theory; cryptography; discrete time systems; fractals; higher order statistics; nonlinear dynamical systems; state-space methods; tensors; Z transforms; abstract model; chaotic systems; closed form expression; discrete-time systems; higher order correlations; higher order statistics; highly nontrivial behaviors; macro-state transition; piecewise-affine Markov maps; quantized trajectories; self-similarity; simple chaotic maps; statistical analysis; tensor encoding; tensor function analysis; Chaos; Higher order statistics; Power system modeling; Signal analysis; Signal generators; Signal processing; Statistical analysis; Tensile stress; Trajectory; Writing;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on