Title :
A micropopulation model adaptation for neural network studies
Author :
Ackerman, Eugene ; Kilis, Danny ; Hatfield, Gregory A.
Author_Institution :
Minnesota Univ., Minneapolis, MN, USA
Abstract :
A discrete-time, micropopulation model called SUMMERS has been adapted to represent one of the neural network models proposed by K. Fukushima (see Biolog. Cybern., vol.50, p.105-13, 1984). Such specializations of SUMMERS allow for ease of model modification and extension, while sharing most of the Fortran coding with a group of micropopulation models used in epidemiological studies of chronic and infectious diseases. The neural network model. COGNET, can duplicate the features of the primarily deterministic Fukushima model and also can incorporate stochastic elements processed using Monte Carlo techniques. It is planned to use COGNET to test new features that would be based on neuroanatomic and physiological information
Keywords :
Monte Carlo methods; medical computing; neural nets; physiological models; stochastic processes; COGNET; Fortran coding; Monte Carlo techniques; SUMMERS; chronic diseases; deterministic Fukushima model; discrete time micropopulation model; epidemiological studies; infectious diseases; neural network models; neuroanatomic information; physiological information; stochastic elements; Adaptation model; Biological system modeling; Difference equations; Diseases; Libraries; Monte Carlo methods; Neural networks; Stochastic processes; Testing; Voice mail;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.96579
