Intelligent Engineering Systems through Artificial Neural Networks Volume 18
13 Computing Algorithmic Complexity Using Advance Sampling Technique
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In high dimensional feedback-controlled systems, the rate of information generation is too low for a given integration time-step. The low level of information generation is because of the slow system evolution with the optimum integration step size. This causes longer processing time and larger buffer capacity requirement for complexity analysis. Thus, for these systems, immediate solutions are not good candidate for sampling and mapping to binary sequences. To overcome this problem and eliminate the need for large buffer size, in this paper we introduce a method that instead of using real-time dynamic solutions, advance solutions are selected. This means, if trajectories traced and sampled with advance time, then system dynamics provides adequate information from phase space attractors.