Add to ORKGAbstract- A c4D tool based on SPICE macromodels to simuhte simplfled fmlfy circuit realizations of a filly programmable, two dimensional cellular neural network (Cm is presented The mociels can be easily e t e d to match the electrical parameters of real circuit implementations. Generic m a c r d d l s for both current mock and voltage mode CNNs are provided The macromdls m t only simuhte the conceptual CNN cell, but also provide the capability to maiel actual CWN architectures and their nmi&alities. Moreover, macromodeling provides the capa6ility to determine the eflect of parameter variation on the operation of the CiW elyiciently without the need for comptationally expensive, exhaustive circuit simuhtions. We have used the CAW macrom...
The paper proposes a new electronic design which closely approximates the standard implementation in...
Hardware implementation of programmable neural networks requires multiplications of input analogue v...
Cellular Neural Networks (CNN's) represent a remarkable improvement in hardware implementation of Ar...
A CAD tool based on SPICE macromodels to simulate simplified faulty, circuit realizations of a fully...
A robust testing method for detecting circuit faults within two-dimensional Cellular Neural Network ...
Due to the character of the original source materials and the nature of batch digitization, quality ...
Testing strategies to quantify parametric faults in a fully programmable, two-dimensional cellular n...
A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation ...
A novel approach to test the functional behaviour of cellular neural networks (CNNs) is proposed. Th...
SummaryA cellular neural network (CNN) is a massively parallel analog array processor capable of sol...
We report on the design of a new full-analog currend-mode CNN in a 1.2 um CMOS technology, whose cel...
A cellular neural network (CNN) is a massively parallel analog array processor capable of solving va...
This paper describes the design of a programmable Cellular Neural Network (CNN) chip, with additiona...
This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variab...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
The paper proposes a new electronic design which closely approximates the standard implementation in...
Hardware implementation of programmable neural networks requires multiplications of input analogue v...
Cellular Neural Networks (CNN's) represent a remarkable improvement in hardware implementation of Ar...
A CAD tool based on SPICE macromodels to simulate simplified faulty, circuit realizations of a fully...
A robust testing method for detecting circuit faults within two-dimensional Cellular Neural Network ...
Due to the character of the original source materials and the nature of batch digitization, quality ...
Testing strategies to quantify parametric faults in a fully programmable, two-dimensional cellular n...
A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation ...
A novel approach to test the functional behaviour of cellular neural networks (CNNs) is proposed. Th...
SummaryA cellular neural network (CNN) is a massively parallel analog array processor capable of sol...
We report on the design of a new full-analog currend-mode CNN in a 1.2 um CMOS technology, whose cel...
A cellular neural network (CNN) is a massively parallel analog array processor capable of solving va...
This paper describes the design of a programmable Cellular Neural Network (CNN) chip, with additiona...
This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variab...
Cellular Neural Networks are characterized by simplicity of operation. The network consists of a lar...
The paper proposes a new electronic design which closely approximates the standard implementation in...
Hardware implementation of programmable neural networks requires multiplications of input analogue v...
Cellular Neural Networks (CNN's) represent a remarkable improvement in hardware implementation of Ar...