摘要
The application of cellular neural networks (CNN) for solving partial differential equations (PDEs) is investigated in this paper. Two kinds of the PDEs , the heat conduction equation and Poisson's equation,are considered to be typical examples. They can be computed in real time by using the CNN ,while the CNN' s hardware is implemented by the integrated OP AMP . The experimental results show that the hardware performence is in agreement with that given by the computer simulation. Therefore,the CNN is a new powerful tool for solving PDEs.
The application of cellular neural networks (CNN) for solving partial differential equations (PDEs) is investigated in this paper. Two kinds of the PDEs , the heat conduction equation and Poisson's equation,are considered to be typical examples. They can be computed in real time by using the CNN ,while the CNN' s hardware is implemented by the integrated OP AMP . The experimental results show that the hardware performence is in agreement with that given by the computer simulation. Therefore,the CNN is a new powerful tool for solving PDEs.
