Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/44065
|Download PDF (Published version) (Adobe Acrobat PDF, 582 KB)|
- Improving the robustness of winner-take-all cellular neural networks
- Andrew, Lachlan L. H.
- This paper describes two improvements on a recently proposed winner-take-all (WTA) architecture with linear circuit complexity based on the cellular neural network paradigm. The general design technique originally used to select parameter values is extended to allow values to be optimized for robustness against relative parameter variations as well as absolute variations. In addition, a modified architecture, called clipped total feedback winner-take-all (CTF-WTA) is proposed. This architecture is shown to share most properties of standard cellular neural networks, but is shown to be better suited to the WTA application. It is shown to be less sensitive to parameter variations and under some conditions to converge faster than the standard cellular version. In addition, the effect of asymmetry between the neurons on the reliability of the circuit is examined, and CTF-WTA is found to be superior.
- Publication type
- Journal article
- IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol. 43, no. 4 (Apr 1996), pp. 329-334
- Publication year
- Algorithms; Cellular neural networks; CNNs; Computational complexity; Convergence of numerical methods; Linear integrated circuits; Optimization; Parameter variation; Probability density function; Sensitivity analysis; Unipolar activation function; Vectors; Winner-take-all architecture; WTA) architecture
- Publisher URL
- Copyright © 1996 IEEE. Paper reproduced here in accordance with the copyright policy of the publisher.
- Additional information
- This work was supported in part by a scholarship from the Australian Telecommunications and Electronics Research Board (ATERB).
- Full text
- Peer reviewed