1. Global Analysis of Recurrent Neural Networks. - 1. 1 Global Analysis-Why?. - 1. 2 A Framework for Neural Dynamics. - 1. 3 Fixed Points. - 1. 4 Periodic Limit Cycles and Beyond. - 1. 5 Synchronization of Action Potentials. - 1. 6 Conclusions. - References. - 2. Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns. - 2. 1 Introduction. - 2. 2 Correlation-Based Models. - 2. 3 The Problem of Map Structure. - 2. 4 The Computational Significance of Correlatin-Based Rules. - 2. 5 Open Questions. - References. - 3. Associative Data Storage and Retrieval in Neural Networks. - 3. 1 Introduction and Overview. - 3. 1. 1 Memory and Representation. - 3. 2 Neural Associatve Memory Models. - 3. 3 Analysis of the Retrieval Process. - 3. 4 Information Theory of the Memory Process. - 3. 5 Model Performance. - 3. 6 Discussion. - Appendix 3. 1. - Appendix 3. 2. - References. - 4. Inferences Modeled with Neural Networks. - 4. 1 Introduction. - 4. 2 Model for Cognitive Systems and for Experiences. - 4. 3 Inductive Inference. - 4. 4 External Memory. - 4. 5 Limited Use of External Memory. - 4. 6 Deductive Inference. - 4. 7 Conclusion. - References. - 5. Statistical Mechanics of Generalization. - 5. 1 Introduction. - 5. 2 General Results. - 5. 3 The Perceptron. - 5. 4 Geometry in Phase Space and Asymptotic Scaling. - 5. 5 Applications to Perceptrons. - 5. 6 Summary and Outlook. - Appendix 5. 1: Proof of Sauer's Lemma. - Appendix 5. 2: Order Parameters for ADALINE. - References. - 6. Bayesian Methods for Backpropagation Networks. - 6. 1 Probability Theory and Occam's Razor. - 6. 2 Neural Networks as Probabilistic Models. - 6. 3 Setting Regularization Constants ? and ?. - 6. 4 Model Comparison. - 6. 5 Error Bars and Predictions. - 6. 6 Pruning. - 6. 7 Automatic Relevance Determination. - 6. 8 Implicit Priors. - 6. 9 Cheap and CheerfulImplementations. - 6. 10 Discussion. - References. - 7. Penacée: A Neural Net System for Recognizing On-Line Handwriting. - 7. 1 Introduction. - 7. 2 Description of the Building Blocks. - 7. 3 Applications. - 7. 4 Conclusion. - References. - 8. Topology Representing Network in Robotics. - 8. 1 Introduction. - 8. 2 Problem Description. - 8. 3 Topology Representing Network Algorithm. - 8. 4 Experimental Results and Discussion. - References. Language: English