In this paper, a network of coupled chaotic maps for multi-scale image segmentation is proposed. Time evolutions of chaotic maps that correspond to a pixel cluster are synchronized with one another, while this synchronized evolution is desynchronized with respect to time evolution of chaotic maps corresponding to other pixel clusters in the same image. The number of pixel clusters is previously unknown and the adaptive pixel moving technique introduced in the model makes it robust enough to classify ambiguous pixels.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1142/S0129065703001522 | DOI Listing |
Chaos
January 2025
Physics Institute, University of São Paulo-USP, São Paulo, SP 05508-090, Brazil.
This study focuses on the analysis of a unique composition between two well-established models, known as the Logistic-Gauss map. The investigation cohesively transitions to an exploration of parameter space, essential for unraveling the complexity of dissipative mappings and understanding the intricate relationships between periodic structures and chaotic regions. By manipulating control parameters, our approach reveals intriguing patterns, with findings enriched by extreme orbits, trajectories that connect local maximum and minimum values of one-dimensional maps.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Science, Faculty of Computers and Information, Suez University, P.O. Box 43221, Suez, Egypt.
Developing robust and secure image encryption methods for transmitting multiple images in batches over unprotected networks has become imperative. This necessity arises from the limitations of single-image encryption techniques in managing the escalating volume of extensive data. This paper introduces a novel three-layer multiple-image encryption (MIE) technique to encrypt batch images based on three 2D-chaotic maps.
View Article and Find Full Text PDFPhys Rev E
November 2024
Ecole Nationale Supérieure de Génie Mathématique et Modélisation (ENSGMM), Université Nationale des Sciences, Technologies, Ingénierie et Mathématiques, Abomey, Republique du Bénin.
On applying a small bias force, nonequilibrium systems may respond in paradoxical ways such as with giant negative mobility (GNM)-a large net drift opposite to the applied bias, or giant positive mobility (GPM)-an anomalously large drift in the same direction as the applied bias. Such behaviors have been extensively studied in idealized models of externally driven passive inertial particles. Here, we consider a minimal model of a memory-driven active particle inspired from experiments with walking and superwalking droplets, whose equation of motion maps to the celebrated Lorenz system.
View Article and Find Full Text PDFCogn Neurodyn
October 2024
Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, Tamilnadu 600 069 India.
To illustrate the occurrences of extreme events in the neural system we consider a pair of Chialvo neuron maps. Importantly, we explore the dynamics of the proposed system by including a flux term between the neurons. Primarily, the dynamical behaviors of the coupled Chialvo neurons are examined using the Lyapunov spectrum and bifurcation analysis.
View Article and Find Full Text PDFHeliyon
December 2024
Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
Using discrete fractional calculus, a wide variety of physiological phenomena with various time scales have been productively investigated. In order to comprehend the intricate dynamics and activity of neuronal processing, we investigate the behavior of a slow-fast FitzHugh-Rinzel (FH-R) simulation neuron that is driven by physiological considerations via the Caputo fractional difference scheme. Taking into account the discrete fractional commensurate and incommensurate mechanisms, we speculate on the numerical representations of various excitabilities and persistent activation reactions brought about by the administered stimulation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!