Advances in Information Systems Science
Springer-Verlag New York Inc.
9781461590521 (ISBN)
1 Theory of Algorithms and Discrete Processors.- 1. Introduction.- 2. Discrete Processors.- 3. Examples of Discrete Processors.- 4. Computers and Discrete Processors.- 5. Systems of Algorithmic Algebras.- 6. Application of Algorithmic Algebras to Transformations of Microprograms.- 7. Equivalence of Discrete Processors.- 8. Equivalence of Automata with Terminal States Relative to an Automaton without Cycles.- 9. Specific Cases of Solutions to the Equivalence Problem.- 10. Conclusions.- References.- 2 Programming Languages.- 1. Introduction.- 2. The Basic Linguistic Nature of Programming Languages.- 3. Programming Languages and Semiotics.- 4. The Formal Definition of Programming Lan guages.- 5. The Definition of Programmable Automata and their Languages.- 6. Parallel Concurrent Processes.- 7. Machine Languages.- 8. Special and General-Purpose Algorithmic Languages.- 9. Special Problem-Oriented Languages.- 10. Simulation Languages.- 11. Conversational Languages.- 12. Conclusion.- References.- 3 Formula Manipulation—The User’s Point of View.- 1. Introduction.- 2. Different Types of Formula Manipulation Systems.- 3. Toward a Mathematical Utility.- 4. The Formula Manipulation Language Symbal.- 5. The Syntax of Symbal.- 6. The Basic Symbols and Syntactic Entities.- 7. Expressions.- 8. The Remaining Parts of the Language.- 9. Standard Variables.- 10. Techniques and Applications.- 11. Summary.- References.- 4 Engineering Principles of Pattern Recognition.- 1. Introduction.- 2. Basic Problems in Pattern Recognition.- 3. Feature Selection and Preprocessing.- 4. Pattern Classification by Distance Functions.- 5. Pattern Classification by Potential Functions...- 6. Pattern Classification by Likelihood Functions.- 7. Pattern Classification by Entropy Functions...- 8. Conclusions.-References.- 5 Learning Control Systems.- 1. Introduction.- 2. Trainable Controllers.- 3. Reinforcement Learning Control Systems.- 4. Bayesian Learning in Control Systems.- 5. Learning Control Systems Using Stochastic Approximation.- 6. The Method of Potential Functions and its Application to Learning Control.- 7. Stochastic Automata as Models of Learning Controllers.- 8. Conclusions.- Appendix. Stochastic Approximation—A Brief Survey.- References.- Author Index.
| Zusatzinfo | 3 Illustrations, black and white |
|---|---|
| Verlagsort | New York, NY |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Themenwelt | Schulbuch / Wörterbuch |
| Geisteswissenschaften | |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Naturwissenschaften | |
| Sozialwissenschaften | |
| ISBN-13 | 9781461590521 / 9781461590521 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich