Markus Diesmann, Marc-Oliver Gewaltig, Ad Aertsen, "Stable propagation of synchronous spiking in cortical neural networks", Nature, vol. 402, pp. 529–533, 1999.
Bernhard Sendhoff and Martin Kreutz, "A model for the dynamic interaction between evolution and learning", Neural Processing Letters, vol. 10, no. 3, pp. 181–193, 1999.
Edgar Körner, Marc-Oliver Gewaltig, Ursula Körner, Andreas Richter, Tobias Rodemann, "A Model of Computation in Neocortical Architecture", Neural Networks, vol. 12, pp. 989–1006, 1999.
Bernhard Sendhoff and Martin Kreutz, "Variable encoding of modular neural networks for time series prediction", Congress on Evolutionary Computation CEC, pp. 259-266, 1999.
Yaochu Jin, Werner von Seelen, Bernhard Sendhoff, "On Generating FC^3 Fuzzy Rule Systems From Data Using Evolution Strategies", IEEE Transactions on Systems, Man and Cybernetics, Part B, vol. 29, no. 4, pp. 829-845, 1999.Abstract
Sophisticated fuzzy rule systems are supposed to be ﬂexible, complete, consistent and compact (FC^3). Flexibility, completeness and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violated if a fuzzy system is generated from data collec...
Edgar Körner and Gen Matsumoto, "Cortical architecture and self-referential control for brain-like processing in artificial neural systems", Artificial life and robotics, vol. 2, no. 3, pp. 170–178, 1998.
Edgar Körner, "Synchronization of Decision Processes - But Not of Spikes: Gamma Paced Temporal Encoding in Model Cortical Columns", Bochum-Tamagawa Brain Forum, 1997.
Edgar Körner and Ursula Körner, "Concurrent Parallel-Sequential Processing in Gamma Controlled Cortical-Type Networks of Spiking Neurones", Proc. International Conference on Artificial Neural Networks, pp. 91–96, 1997.
Edgar Körner, Hiroshi Tsujino, Tomohiko Masutani, "A Cortical-type Modular Neural Network for Hypothetical Reasoning", Neural Networks, vol. 10, no. 5, pp. 791–814, 1997.
The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.