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The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net­ works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.

The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net­ works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.

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Part I: Plenary Talks and Tutorials: What Can a Neural Network Do without Scaling Activation Function? (Y. Ito); Ratio Scales Are Critical for Modeling Neural Synthesis in the Brain (T. L. Saaty); Hypermatrix of the Brain (T. L. Saaty); The Computational Capabilities of Neural Networks (J. Sima).- Part II: Neural Networks - Theory: Activation Functions (N. C. Steele, C. R. Reeves, E.I. Gaura); A Simulation of Spiking Neurons by Sigmoid Neurons (V. Kvasnicka); Tightness of Upper Bounds on Rates of Neural-Network Approximation (V. Kurkova, M. Sanguineti); Incremental Function Approximation Based on Gram-Schmidt Orthonormalisation Process (B. Beliczynski); Wavelet Based Smoothing in Time Series Prediction with Neural Networks (U. Lotric, A. Dobnikar); Fitting Densities and Hazard Functions with Neural Networks (C. Reeves, C. Johnston); Optimization of Expensive Functions by Surrogates Created from Neural Network Ensembles (J. Pospichal); Local-Global Neural Networks for Interpolation (C. E. Pedreira, L. C. Pedroza, M. Farinas); Improving the Competency of Classifiers through Data Generation (H. L. Viktor, I. Skrypnik; Graded Rescaling in Hopfield Networks (X. Zeng, T. R. Martinez); Principles of Associative Computation (A. Wichert, B. Lonsinger-Miller); An Experimental Assessment of the Performance of Several Associative Memory Models (S. P. Turvey, S. P. Hunt, N. Davey, R. J. Frank); Recall Time in Densely Encoded Hopfield Network: Results from KFS Theory and Computer Simulation(A. A. Frolov, D. Husek, P. Combe, V. Snasel); On-Line Identification and Rule Extraction of Finite State Automata with Recurrent Neural Networks (I. Gabrijel, A. Dobnikar); Using Decision Surface Mapping in the Automatic Recognition of Images (C. Reeves, G. S. Billan); Competitive Learning and Its Convergence Analysis (Y.-J. Zhang, Z.-Q. Liu); Structural Information Control for Flexible Competitive Learning (R. Kamimura, T. Kamimura, T. R. Shultz); Recursive Learning Scheme for Recurrent Neural Networks Using Simultaneous Perturbation and Its Application (Y. Maeda); Reinforcement Learning for Rule Generation (D. Vogiatzis, A. Stafylopatis); Learning Feed-Forward Multi-Nets (R. S. Venema, L. Spaanenburg); Unlearning in Feed-Forward Multi-Nets (L. Spaanenburg); Context Neural Network for Temporal Correlation and Prediction (L. F. Mingo, L. Aslanyan, J. Castellanos, V. Riazanov, M. A. Diaz); A Pruning Self-Organizing Algorithm to Select Centers of Radial Basis Function Neural Networks (L. N. de Castro, F. J. Von Zuben); Modular Clustering by Radial Basis Function Network for Complexity Reduction in System Modeling (O. Ciftcioglu, S. Sariyildiz); A Fuzzy Approach to Sociodynamical Interactions (D. W. Pearson, G. Dray); An Immunological Approach to Initialize Feedforward Neural Network Weights (L. N. de Castro, F. J. Von Zuben); How Certain Characteristics of Cortical Frequency Representation May Influence Our Perception of Sounds (L. Benuskova); Long Short-Term Memory Learns Context Free and Context Sensitive Languages (F. A. Gers, J. Schmidhuber); An Artificial Neural Network Model Based on Neuroscience: Looking Closely at the Brain (J. L. G. Rosa); STARBRAIN and EUROBRAIN, Starlab's and Europe's Artificial Brain Projects: An Overview (H. de Garis).- Part III: Neural Networks - Applications: Application of Feature Extraction in Text-to-Speech Processing (V. Sebesta, J. Tuckova); Gaussian Synapse Networks for Handwritten Character Recognition (J. L. Crespo, R. J. Duro); A Generic Pretreatment for Spiking Neuron Application on Lipreading with STANN (Spatio-Temporal Artificial Neural Networks) (R. Seguier, D. Mercier); A Comparison of a Neural Network and an Observer Approach for Detecting Faults in a Benchmark System (D. N. Shields, S. Du, E. Gaura); A Neuro-Fuzzy Image Analysis System for Biomedical Imaging Applications (L. Patino, M. Razaz); Real Time Identification and Control of a DC Motor Using Recurrent Neural Networks (I. Baruch, J. M. Flores

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