IMAGE PROCESSING AND SELF-ORGANIZING CNN

DOI10.1142/S0218127405013794zbMath1093.94500OpenAlexW2065148753MaRDI QIDQ5474333

Makoto Itoh, Leon O. Chua

Publication date: 23 June 2006

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218127405013794

zbMATH Keywords

complexitynumerical integrationdivergenceself-organizationneural field equationCNNnumeral differentiation

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Developmental biology, pattern formation (92C15) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Applications of dynamical systems (37N99)

Related Items (6)

GENERALIZED CELLULAR NEURAL NETWORKS (GCNNs) CONSTRUCTED USING PARTICLE SWARM OPTIMIZATION FOR SPATIO-TEMPORAL EVOLUTIONARY PATTERN IDENTIFICATION ⋮ COMPLEXITY OF REACTION–DIFFUSION CNN ⋮ ADVANCED IMAGE PROCESSING CELLULAR NEURAL NETWORKS ⋮ OSCILLATIONS ON THE EDGE OF CHAOS VIA DISSIPATION AND DIFFUSION ⋮ THREE-DIMENSIONAL CELLULAR NEURAL NETWORKS AND PATTERN GENERATION PROBLEMS ⋮ THE IDENTIFICATION OF COUPLED MAP LATTICE MODELS FOR AUTONOMOUS CELLULAR NEURAL NETWORK PATTERNS

Cites Work

• SIMULATION AND VISUALIZATION OF CNN DYNAMICS
• EQUIVALENT CNN CELL MODELS AND PATTERNS
• DESIGNING CNN GENES
• STAR CELLULAR NEURAL NETWORKS FOR ASSOCIATIVE AND DYNAMIC MEMORIES
• Edge of Chaos and Local Activity Domain of FitzHugh-Nagumo Equation
• TESTING FOR LOCAL ACTIVITY AND EDGE OF CHAOS

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