A new simulation method for Time-Derivative Cellular Neural Networks

Time-derivative Cellular Neural Networks (TDCNN) is a general class of CNN having derivative connections between cells. It has been reported that several mixed-domain 3D spatiotemporal transfer functions for linear filtering can be implemented via TDCNN such as bandpass filters and visual receptive...

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Bibliographic Details
Published in2009 17th European Signal Processing Conference pp. 288 - 292
Main Authors Nergis Tural Polat, S., Tavsanoglu, Vedat
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Abstracts
Biological system modeling
Cellular
Cellular neural networks
Computational modeling
Computer simulation
Computers
Derivatives
Filtering
Joints
Neural networks
Simulation
Software packages
Three dimensional
Visual
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Summary:Time-derivative Cellular Neural Networks (TDCNN) is a general class of CNN having derivative connections between cells. It has been reported that several mixed-domain 3D spatiotemporal transfer functions for linear filtering can be implemented via TDCNN such as bandpass filters and visual receptive field models. In this paper a new computer simulation method for TDCNN is presented. The new simulation method reduces simulation time dramatically and simplifies the simulation steps.
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SourceType-Conference Papers & Proceedings-2
ISBN:9781617388767
1617388769