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Neural networks fundamentals in mobile robot control systems
Оборот титула
Table of contents
1. LECTURE: INTRODUCTION TO NEURAL NETWORKS
+
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS
-
2.1. Parametric adaptation of the neural threshold element
2.2. The perceptron rule of adaptation
2.3. Mays adaptation rule
2.4. Adaptive linear element
2.5. α - Least Mean Square Algorithm
2.6. Mean Square Error Method
2.7. μ - Least Mean Square Algorithm
2.8. Adaline with sigmoidal functions
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS
Справка
STUDENT'S CONSULTANT
Электронная библиотека технического вуза
Все издания
Login/Registration
Во весь экран / Свернуть
ru
Accessibility
General Catalogue
Все издания
Menu
Искать в книге
К результату поиска
Advanced search
Bookmarks
Homepage
Login/Registration
Во весь экран / Свернуть
ru
Управление
My reports
General Catalogue
Издательства
УГС
Мои списки
Download app
Neural networks fundamentals in mobile robot control systems
Оборот титула
Table of contents
1. LECTURE: INTRODUCTION TO NEURAL NETWORKS
+
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS
-
2.1. Parametric adaptation of the neural threshold element
2.2. The perceptron rule of adaptation
2.3. Mays adaptation rule
2.4. Adaptive linear element
2.5. α - Least Mean Square Algorithm
2.6. Mean Square Error Method
2.7. μ - Least Mean Square Algorithm
2.8. Adaline with sigmoidal functions
2. LECTURE: BASES OF LEARNING OF NEURAL NETWORKS