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Training Models Theory
Neural Network introduction
ART Neural Network
Backpropagation
Kohonen Neural Network
Hopfield
Neocognitron
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Perceptron & Adaline
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SharkTime Neural network software
Neuroph - Java Neural Network
Setting the GUI enviroment
XML based neural network processing language
Simple Hopfield simulator
The Neocognitron neural network
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Artificial Intelligence
Introduction to Artificial Intelligence
Defining Artificial Intelligence
General Problem Solving Approaches in AI
The Disciplines of Artificial Intelligence
The Subject of Artificial Intelligence
Applications of Artificial Intelligence Techniques
Digital Signal Processing (DSP)
Introduction
Applications of DSP
Telecomunications
Audio Processing
Echo Location
Image Processing
DSP Fundamentals
Signals and Systems
Requirements for Linearity
Convolution
Correlation ...Soon
DFT Discrete fouirer transfomation...Soon
FFT Fast fourier Transformation...Soon
Genetic Algorithms
Introduction
Deterministic Explanation of Holland's Observation
Stochastic Explanation of Genetic Algorithms
The Fundamental Theorem of Genetic Algorithms
The Markov Model for Convergence Analysis
Intelligent Search
Introduction
General Problem Solving Approaches
Breadth First Search
Depth First Search
Iterative Deepening Search
Hill Climbing
Simulated Annealing
Heuristic Search
Heuristic Search for OR Graphs
Machine Learning
Introduction
Supervised Learning
Inductive Learning
Analogical Learning
Neural Networks Training Models
Neural Network introduction
Introduction
Biological Model
Matematical Model
Activation Functions
A framework for distributed representation
Neural Network Topologies
Training of artifcial neural networks
ART Neural Network
An introduction to the adaptative resonance theory, training model
Introduction
The Adaptative Resonance Theory: ART
ART1: The simplified neural network model
ART1: The original model
THE ART1 C Source code..soon
Backpropagation
The backpropagation training model explanations and algorithms
Multi-layer feed-forward networks
Delta rule
Understanding Backpropagation
Working with backpropagation
Kohonen Neural Network
Introduciton to Kohonen neural network
Introduction
The SOM Learning Algorithm
Hopfield
The hopfield neural network model and algorithm.
Neocognitron
Introduction
Neocognitron Architecture
Neocognitron data processing
Training Weights on the S-Layers
Perceptron & Adaline
An explanation about the perceptron model and the adaline training model
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Applications of Neural Networks
Robot Control
Introduction
End-efector positioning
Camera-robot coordination
Approach 1: Feed-forward networks
Approach 2: Topology conserving maps
Speech Recognition
Introduction
Fundamentals of Speech Recognition
Dynamic Time Warping Algorithm
Neural Network Approaches
Phoneme Classification
Static Approaches
Dynamic Approaches
Stock Market Prediciton
Introduction
Stock Markets and Prediction
Prediction Using Neural Networks
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