Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

Neural Information Processing and VLSI provides a unified treatment of this important
subject for use in classrooms, industry, and research laboratories, in order to develop …

In this paper, a novel method for designing templates of cellular neural network to cancel the
image noise is discussed. The discrete-time cellular neural network (DTCNN) combining …

In our previous work and in a patent we proposed an architecture for current-mode FPAA. It
is suitable for a wide class of circuits, including continuous-time filters, differential and …

In this section we give an overview of the state of the art of cellular neural network (s)(CNN).
This overview will give readers who are not familiar with CNN all elementary concepts …

A cellular neural network (CNN) is a locally connected, massively paralleled computing
system with simple synaptic operators so that it is very suitable for VLSI implementation in …

In this paper, a network called a discrete-time cellular neural network (DTCNN) with
uncertainty is introduced. A methodology for the robust stability of the DTCNN is presented …

In this paper, a novel method for designing templates of cellular neural networks to reduce
the image noise is discussed. The discrete-time cellular neural network (DTCNN) combining …

Abstract At room temperature (300K), the electromagnetic (EM) radiation emitted by humans
and other living beings peaks mostly in the long-wavelength infrared (LW-IR) regime. And …

A smart-pixel cellular neural network with hardware annealing capability, digitally
programmable synaptic weights, and multisensor parallel interface has been under …