The CNN paradigm

Attractors for stochastic lattice dynamical systems with a multiplicative noise

“…These systems are used to model such systems as cellular neural networks with applications to image processing, pattern recognition, and brain science [15,16,17,18]. They are also used to model the propagation of pulses in myelinated axons where the membrane is excitable only at spatially discrete sites.…”

CNN-based models for color vision and visual illusions

“…Most of these works was devoted to examine the early vision stages (retina) [7,9,12,14], and some of them for further parts of the visual pathway (LGN, cortex) [7,13]. The first CNN models of the color vision [5,8] reflected the basic neuromorphic models [11]. In this paper we apply this knowledge to prove the usefulness of these models in the understanding of color vision and in the explanation some of the visual illusions.…”

A 3-D four-wing attractor and its analysis

“…In this endeavor, there are two major thrusts: generalizing Chua's circuits with multi-scroll attractors and generalizing the Lorenz system with multi-wing attractors. In efforts to generalize Chua's circuit [4] to produce multi-scroll attractors, several effective techniques have been developed, including generalized Chua's circuits and cellular neural networks [5,6]. In [4,5,7], the piecewise-linear (PWL) function method was utilized, which can increase the number of equilibria by adding breakpoints.…”

“…In efforts to generalize Chua's circuit [4] to produce multi-scroll attractors, several effective techniques have been developed, including generalized Chua's circuits and cellular neural networks [5,6]. In [4,5,7], the piecewise-linear (PWL) function method was utilized, which can increase the number of equilibria by adding breakpoints. A sine-function approach was then proposed for creating multi-scroll chaotic attractors [8].…”