Abstract
In this paper 2-D discrete-space filters are generated from their analog counterparts and implemented by Cellular Neural Networks (CNN). To this end, first 2-D analog transfer functions are obtained from their 1-D counterparts. Then, the corresponding difference equations are obtained by discretization of 2-D analog filter differential equations, which are then implemented by CNN. Simulation results are presented.
Keywords
Cellular neural network
Discretization
Artificial neural network
Transfer function
Computer science
Filter (signal processing)
Analogue filter
Infinite impulse response
Algorithm
Digital filter
Mathematics
Mathematical analysis
Artificial intelligence
Electrical engineering
Engineering
Subject Areas
Neural Networks Stability and Synchronization
·Computer Networks and Communications ·Physical Sciences
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
Cellular Automata and Applications
·Computational Theory and Mathematics ·Physical Sciences
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