Artificial neural networks

Neuro AI - Intelligent systems and Neural Networks

Preface Skip this and go to Introduction to neural networks... Read more

Fuzzy Logic

A fuzzy logic system is unique, because is able to simultaneously handle numerical data and linguistic knowledge. It is a non linear mapping of an input data vector into a scalar output i.e. it maps' numbers into numbers.... Read more

Robot Control

Introduction End-efector positioning Camera-robot coordination Approach 1: Feed-forward networks Approach 2: Topology conserving maps ... Read more

Stock market prediction

Introduction Stock Markets and Prediction Prediction Using Neural Networks ... Read more

Speech Recognition

Introduction Fundamentals of Speech Recognition Dynamic Time Warping Algorithm Neural Network Approaches Phoneme Classification Static Approaches Dynamic Approaches ... Read more

Machine Learning

Introduction Supervised Learning Inductive Learning Analogical Learning ... Read more

Logic Programming

Introduction to PROLOG Programming Logic Programs - A Formal Definition A Scene Interpretation Program Illustrating Backtracking by Flow of Satisfaction Diagramsmore soon... ... Read more

Intelligent Search

Introduction General Problem Solving Approaches Breadth First Search Depth First Search Iterative Deepening Search Hill Climbing Simulated Annealing ... Read more

Genetic Algorithms

Introduction Deterministic Explanation of Holland's Observation Stochastic Explanation of Genetic Algorithms The Fundamental Theorem of Genetic Algorithms ... Read more

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 ... Read more

Digital Signal Processing(DSP)

What is Digital Signal Processing? Digital signal processing is the newest technology in the tech world. It is not as new as the iPod but enough for being a young discipline in different areas such as electronics and computing. Digital Signal Processing a.k.a. (DSP) is widely used in the world as many technologies depend of their algorithms.... Read more

Perceptron and Adaline

This part describes single layer neural networks, including some of the classical approaches to the neural computing and learning problem. In the first part of this chapter we discuss the representational power of the single layer networks and their learning algorithms and will give some examples of using the networks. In the second part we will discuss the representational limitations of single layer networks. Two 'classical' models will be described in the first part of the chapter: the Perceptron, proposed by Rosenblatt (Rosenblatt, 1959) in the late 50's and the Adaline, presented in the early 60's by by Widrow and Hoff (Widrow & Hoff, 1960). ... Read more

Neocognitron

Introduction Neocognitron Architecture Neocognitron data processing Training Weights on the S-Layers ... Read more

Kohonen

Introduction The SOM Learning Algorithm ... Read more

Hopfield neural network

One of the earliest recurrent neural networks reported in literature was the auto-associator independently described by Anderson (Anderson, 1977) and Kohonen (Kohonen, 1977) in 1977. It consists of a pool of neurons with connections between each unit i and j, i 6= j.... Read more

Backpropagation Neural Network

Multi-layer feed-forward networks Delta rule Understanding Backpropagation Working with backpropagation ... Read more

Adaptive Resonance Theory

Introduction The Adaptative Resonance Theory: ART ART1: The simplified neural network model ART1: The original model ... Read more

Neural network introduction

Introduction Biological Model Mathematical Model Activation Functions ... Read more

History of Artificial Intelligence

Professor Peter Jackson of the University of Edinburgh classified the artificial intelligence history into three periods namely ... Read more