Since the outstanding and pioneering research work of Hopfield on recurrent neural
networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong …

The piecewise-linear (PWL) approximation technique developed by Julia/spl acute/n et al. in
the past few years is applied to find approximate models of dynamical systems dependent …

We use the multistable property of a Cellular Nonlinear Network (CNN) to extract the regions
of interest of an image representing the radiography of a soldering. We also propose the …

The concepts of selectable and unselectable sets are proposed to describe some interesting
dynamical properties of a class of recurrent neural networks (RNNs) with saturated …

Digital architectures for the circuit realization of multivariate piecewise‐linear (PWL)
functions are reviewed and compared. The output of the circuits is a digital word …

For almost 100 years, nonlinear science has attracted the attention of researchers to
circumvent the limitation of linear theories in the explanation of natural phenomenons …

In this paper, canonical isolated CNN cell models are proposed by using implicit differential
equations. A number of equivalent but distinct CNN cell models are derived from these …

In this work we present a programmable and reconfigurable single instruction multiple data
(SIMD) visual processor based on the S-CNN architecture, namely, the Simplicial CNN …

This Letter presents the architecture implementation and testing of an single instruction
multiple data (SIMD) processor for energy aware embedded morphological visual …

We propose a new algorithm inspired by the properties of diffusion processes for image
filtering. We show that purely nonlinear diffusion processes ruled by Fisher equation allows …