SCNN: a universal simulator for cellular neural networks
Research output: Contribution to conferences › Paper › Contributed › peer-review
Contributors
Abstract
In this paper a universal simulator for Cellular Neural Network (CNN) is presented. CNN with nonlinear and delaytype templates can be simulated precisely with SCNN, practically without any limitations. Furthermore different training algorithms for networks with translation variant and invariant templates are implemented in SCNN. As an example, parameter deviations of a template have been reduced by training. Simulation and training results will be discussed in detail.
Details
Original language | English |
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Pages | 255-259 |
Number of pages | 5 |
Publication status | Published - 1996 |
Peer-reviewed | Yes |
Externally published | Yes |
Conference
Title | Proceedings of the 1996 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96 |
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Duration | 24 - 26 June 1996 |
City | Seville, Spain |
External IDs
ORCID | /0000-0001-7436-0103/work/142240252 |
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