Chaos Theory

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Chaos Theory

A theory stating that seemingly unrelated events affect each other in a predictable, mathematical way. In investing, chaos theory is used to predict future stock prices using information that does not seem to affect prices directly, such as trading volume and trader sentiment. Computing these factors using chaos theory is as complex as it is controversial.
References in periodicals archive ?
In this paper, along the chaos-based pipeline, we propose an image encryption algorithm based on the cross diffusion of two chaotic maps, namely the Logistic map and the Chebyshev map.
It has been shown by some experiments that continuous time chaotic systems give more successful results than chaotic maps.
Remaining part of the paper is organized as follows: in Section 2, brief details of different chaotic maps are incorporated.
As can be seen from the above description, the proposed permutation scheme well addresses the two problems encountered when using the discretized version of area-preserving chaotic maps. First, the proposed scheme can be applied to images of arbitrary size, whereas the area-preserving chaotic maps can be only applied to square images.
had proposed performance-enhanced image encryption schemes based on depth-conversion integral imaging and chaotic maps [11].
System parameters and initial conditions of the chaotic map determine the key space.
Let J = {y:y [member of] (0, [infinity])} and [theta]: J [right arrow] J be an unknown chaotic map:
Chaotic signal can be readily obtained from a chaotic oscillator, a chaotic map. Therefore it can be said that chaotic methods would be more efficient and convenient than other methods.
Thus, this paper presents a new approach based on the charged system search (CSS) with chaotic map for partition clustering.
The topics include efficient color image segmentation by a parallel optimized (ParaOptiMUSIG) activation function, chaotic map model-based interference employed in a quantum-inspired genetic algorithm to determine the optimum gray level image thresholding, multi-objective genetic and fuzzy approaches in rule mining problems of knowledge discovery in databases, concept generation in knowledge representation using formal concept analysis, applying a functional approach to lists for developing relational model databases and Petri net analysis, and a Shannon-like solution for the fundamental equation of information science.
In this proposal, when a random number is needed by the classical DE algorithm, it is generated by iterating one step of the chosen chaotic map that has been started from a random initial condition at the first iteration.