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Neural networks fundamentals in mobile robot control systems
Оборот титула
Table of contents
1. LECTURE: INTRODUCTION TO NEURAL NETWORKS
-
1.1. Application of artificial intelligence in robotics
1.2. Structure of an intelligent control system of robot
1.3. The artificial intelligence technologies taxonomy
1.4. Morphology of a biological neuron
1.5. Mathematical model of a biological neuron
1.6. A neural model for a threshold logic
1.7. A neural threshold logic synthesis
1.8. Problems
Practical training 1
1.9. Task for practical training 1
1.10. Example of the practical training performing
1.11. Variants
1.12. Requirements to the results representation
Practical training 2
1.13. Task for practical training 2
1.14. Example of the practical training 2 performing
1.15. Variants
1.16. Requirements to the results representation
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS
+
3. LECTURE: MULTILAYERED FEEDFORWARD STATIC NEURAL NETWORKS
+
4. LECTURE: ADVANCED METHODS FOR LEARNING NEURAL NETWORKS
+
BIBLIOGRAPHY
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1. LECTURE: INTRODUCTION TO NEURAL NETWORKS
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1.1. Application of artificial intelligence in robotics
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Neural networks fundamentals in mobile robot control systems
Table of contents
1. LECTURE: INTRODUCTION TO NEURAL NETWORKS
-
1.1. Application of artificial intelligence in robotics
1.2. Structure of an intelligent control system of robot
1.3. The artificial intelligence technologies taxonomy
1.4. Morphology of a biological neuron
1.5. Mathematical model of a biological neuron
1.6. A neural model for a threshold logic
1.7. A neural threshold logic synthesis
1.8. Problems
Practical training 1
1.9. Task for practical training 1
1.10. Example of the practical training performing
1.11. Variants
1.12. Requirements to the results representation
Practical training 2
1.13. Task for practical training 2
1.14. Example of the practical training 2 performing
1.15. Variants
1.16. Requirements to the results representation
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS
+
3. LECTURE: MULTILAYERED FEEDFORWARD STATIC NEURAL NETWORKS
+
4. LECTURE: ADVANCED METHODS FOR LEARNING NEURAL NETWORKS
+
BIBLIOGRAPHY