2013Unpublished venueRequires access

A new series-wound framework for generating 1D chaotic maps

Zhongyun Hua, Yicong Zhou, C. L. Philip Chen

Open publisher page 12 citations

Abstract

This paper introduces a series-wound framework to generate a large number of new one-dimensional (1D) chaotic maps using a combination of two different 1D chaotic maps (called seed maps). Examples and experimental analysis demonstrate that the newly generated chaotic maps have more parameters, larger chaotic ranges, and better chaotic behaviors than their corresponding seed maps.

About this research paper

What this paper is about

This paper introduces a series-wound framework to generate a large number of new one-dimensional (1D) chaotic maps using a combination of two different 1D chaotic maps (called seed maps). Examples and experimental analysis demonstrate that the newly generated chaotic maps have more parameters, larger chaotic ranges, and better chaotic behaviors than their corresponding seed maps.

Why it matters

OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

This paper introduces a series-wound framework to generate a large number of new one-dimensional (1D) chaotic maps using a combination of two different 1D chaotic maps (called seed maps). Examples and experimental analysis demonstrate that the newly generated chaotic maps have more parameters, larger chaotic ranges, and better chaotic behaviors than their corresponding seed maps.

Key concepts: Chaotic, Series (stratigraphy), Chaotic map, Computer science, Chaotic systems, Time series, Algorithm, Statistical physics

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