A practical survey of the design rules of uncoupled and coupled linear CNN templates with binary inputs and outputs is given. The usage and the properties of the different classes of CNN templates are analyzed. CNN chip specific robustness considerations are also given
Cellular Neural Networks (CNN) [1] is classified into two types of system like space-invariant syste...
In this paper a VLSI implementation of a 3 x 3 cell digitally programmable cellular neural networks ...
A cellular neural network (CNN) is an information processing system with a large scale nonlinear ana...
Demonstrates the processing capabilities of an analog programmable array processor chipMINUS/CNNUC3-...
This paper demonstrates the processing capabilities of a recently designed analog programmable array...
We demonstrate the importance of the reconfigurability of a 64/spl times/64 cells size CNN-UM chip. ...
Abstract — In this article, detailed investigation of the template design method of cellular neural ...
Cellular neural networks proved to be a useful parallel computing system for image processing applic...
In the previous study, we have proposed a template design method of cellular neural networks with ba...
In this paper a high performance VLSI implementation of a 3×3 Digitally Programmable Cellular Neura...
Hardware implementation of programmable neural networks requires multiplications of input analogue v...
Cellular Neural Networks(CNN) were introduced by Chua and Yang in 1988. The idea of CNN was inspired...
Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) ...
Cellular neural networks (CNN) were introduced by Chua and Yang in 1998 [1]. The idea of the CNN was...
In this paper, a kind of relation between CNN (cellular neural network) and GIM (Gibbs image model) ...
Cellular Neural Networks (CNN) [1] is classified into two types of system like space-invariant syste...
In this paper a VLSI implementation of a 3 x 3 cell digitally programmable cellular neural networks ...
A cellular neural network (CNN) is an information processing system with a large scale nonlinear ana...
Demonstrates the processing capabilities of an analog programmable array processor chipMINUS/CNNUC3-...
This paper demonstrates the processing capabilities of a recently designed analog programmable array...
We demonstrate the importance of the reconfigurability of a 64/spl times/64 cells size CNN-UM chip. ...
Abstract — In this article, detailed investigation of the template design method of cellular neural ...
Cellular neural networks proved to be a useful parallel computing system for image processing applic...
In the previous study, we have proposed a template design method of cellular neural networks with ba...
In this paper a high performance VLSI implementation of a 3×3 Digitally Programmable Cellular Neura...
Hardware implementation of programmable neural networks requires multiplications of input analogue v...
Cellular Neural Networks(CNN) were introduced by Chua and Yang in 1988. The idea of CNN was inspired...
Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) ...
Cellular neural networks (CNN) were introduced by Chua and Yang in 1998 [1]. The idea of the CNN was...
In this paper, a kind of relation between CNN (cellular neural network) and GIM (Gibbs image model) ...
Cellular Neural Networks (CNN) [1] is classified into two types of system like space-invariant syste...
In this paper a VLSI implementation of a 3 x 3 cell digitally programmable cellular neural networks ...
A cellular neural network (CNN) is an information processing system with a large scale nonlinear ana...
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