The CNN paradigm
LO Chua, T Roska - IEEE Transactions on Circuits and Systems …, 1993 - ieeexplore.ieee.org
A concise tutorial description of the cellular neural network (CNN) paradigm is given, along
with a precise taxonomy. The CNN is defined, and the canonical equations are described …
with a precise taxonomy. The CNN is defined, and the canonical equations are described …
Cellular neural networks with non‐linear and delay‐type template elements and non‐uniform grids
T Roska, LO Chua - International Journal of Circuit Theory and …, 1992 - Wiley Online Library
The cellular neural network (CNN) paradigm is a powerful framework for analogue non‐
linear processing arrays placed on a regular grid. In this paper we extend the current …
linear processing arrays placed on a regular grid. In this paper we extend the current …
Current-mode techniques for the implementation of continuous-and discrete-time cellular neural networks
A Rodriguez-Vazquez, S Espejo… - … on Circuits and …, 1993 - ieeexplore.ieee.org
A unified, comprehensive approach to the design of continuous-time (CT) and discrete-time
(DT) cellular neural networks (CNNs) using CMOS current-mode analog techniques is …
(DT) cellular neural networks (CNNs) using CMOS current-mode analog techniques is …
An analog implementation of discrete-time cellular neural networks
H Harrer, JA Nossek, R Stelzl - IEEE Transactions on Neural …, 1992 - ieeexplore.ieee.org
An analog circuit structure for the realization of discrete-time cellular neural networks
(DTCNNs) is introduced. The computation is done by a balanced clocked circuit based on …
(DTCNNs) is introduced. The computation is done by a balanced clocked circuit based on …
Resistive grid image filtering: input/output analysis via the CNN framework
The cellular neural network framework developed by LO Chua and L. Yang (IEEE Trans.
Circuits Syst., vol. 32, Oct. 1988) is used to analyze the image filtering operation performed …
Circuits Syst., vol. 32, Oct. 1988) is used to analyze the image filtering operation performed …
Detecting simple motion using cellular neural networks
T Roska, T Boros, P Thiran… - … International Workshop on …, 1990 - ieeexplore.ieee.org
The general framework of motion detection based on the discrete-time samples of the
moving image is defined. Four types of motion detection problem are studied. The simplest …
moving image is defined. Four types of motion detection problem are studied. The simplest …
The CNN is universal as the Turing machine
LO Chua, T Roska… - IEEE Transactions on …, 1993 - ieeexplore.ieee.org
The CNN is universal as the Turing machine Page 1 IEEE TRANSACTIONS ON CIRCUITS
AND SYSTEMS-I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 40, NO. 4. APRIL …
AND SYSTEMS-I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 40, NO. 4. APRIL …
The use of CNN models in the subcortical visual pathway
T Roska, J Hamori, E Labos, K Lotz… - … on Circuits and …, 1993 - ieeexplore.ieee.org
The equivalent notions of neuroanatomy and the cellular neural network (CNN) model are
discussed with a view toward studying the visual system. Various mainly subcortical …
discussed with a view toward studying the visual system. Various mainly subcortical …
A current-mode cellular neural network implementation
JE Varrientos, E Sanchez-Sinencio… - … on Circuits and …, 1993 - ieeexplore.ieee.org
A compact and efficient current-mode circuit implementation for a cellular neural network is
presented. The implementation presented consists of current amplifiers, simple current …
presented. The implementation presented consists of current amplifiers, simple current …
Physically unclonable functions derived from cellular neural networks
We propose the design of Physically Unclonable Functions (PUFs) exploiting the nonlinear
behavior of Cellular Neural Networks (CNNs). Our work derives from some theoretical …
behavior of Cellular Neural Networks (CNNs). Our work derives from some theoretical …