Abstract
The neural-network model based on the theory proposed by Wilson and Cowan has been simulated by using digitized real images. Mathematically, the model is based on coupled nonlinear differential equations that describe the functional dynamics of cortical nervous tissue, and the model can operate in different dynamical modes, depending on coupling strengths. The model is shown to store images in reduced form and to recognize edges of an object. Examples of how the network processes input images are shown.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
H.R. Wilson and J.D. Cowan, “Excitatory and inhibitory interactions in localized populations of model neurons,” Biophys. J.,vol. 12, pp. 1–24, 1972.
H.R. Wilson and J.D. Cowan, “A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue,” Kybernetik,vol. 13, pp. 55–80, 1973.
H. Sakaguchi, “Oscillatory and excitable behaviours in a population of model neurons,” Prog. Theor. Phys.,vol. 79, pp. 1061–1068, 1988.
M.M. Gupta and G.K. Knopf, “A dynamic neural network for visual memory,” in Visual Communications and Image Processing ‘80: Fifth in a Series, M. Kunt, ed., Proc. Soc., Photo-Opt. Instrum. Eng., vol. 1360, pp. 1044–1055, 1990.
J.L. Homer (ed.), Optical Signal Processing, Academic Press: San Diego, CA, 1987.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1993 Springer Science+Business Media New York
About this chapter
Cite this chapter
Mantere, K., Parkkinen, J., Jaaskelainen, T., Gupta, M.M. (1993). Wilson—Cowan Neural-Network Model in Image Processing. In: Dougherty, E.R., Astola, J. (eds) Mathematical Nonlinear Image Processing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3148-7_11
Download citation
DOI: https://doi.org/10.1007/978-1-4615-3148-7_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6378-1
Online ISBN: 978-1-4615-3148-7
eBook Packages: Springer Book Archive