Neural Networks in Computer Intelligence provides basic concept, algorithms and analysis of important neural network models developed to date, with emphasis on the importance of knowledge in system design. The book bridges the gap between afrificial intelligence and neural networks.Table of Contents: Preface Acknowledgements PART I: THEORY, METHODS, APPLICATIONS Chapter 1. Introduction Chapter 2. Basic Neural Computational Models Chapter 3. Learning: Supervised and Unsupervised Chapter 4. Knowledge-Based Neural Networks Chapter 5. Incremental Learning Chapter 6. Mathematical Modeling Chapter 7. Complex Domains Chapter 8. Discovery Chapter 9. Structures and Sequences Chapter 10. Learning Spatiotemporal Patterns PART II: NEURAL NETWORKS AND EXPERT SYSTEMS Chapter 11. Expert Systems Chapter 12. Causal Learning and Modeling Chapter 13. Validation and Verification Chapter 14. Rule Generation from Neural Networks Chapter 15. Learning Grammars PART III: CASE STUDIES Chapter 16. Genetic Pattern Recognition Chapter 17. Drug Discovery Chapter 18. Flow Cytometric Analysis of Leukemia Index