What are artificial neural networks?
An artificial neural network (ANN) is the piece of a computing device designed to simulate the way the human mind analyzes and procedures information. It is the inspiration of artificial intelligence (AI) and solves issues that might show not possible or tough through human or statistical standards. ANNs have self-gaining knowledge of skills that allow them to provide higher effects as extra records will become available.
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Download Artificial Neural Networks PDF notes free from here. This notes is very useful any help full for those who interested in it and wants to learn more about neural networks, machine learning and artificial intelligence. In this notes you will learn the process of neural networks, its brief introduction and performance of parameters. This notes turned into written with the number one subject of answering readers with exclusive profiles, from those interested by acquiring understanding approximately architectures of artificial neural network to the ones inspired through its multiple applications for solving real-world problems.
This notes divided into two parts:
- Architectures of Artificial Neural Networks and Their Theoretical Aspects
- Application of Artificial Neural Networks in Engineering and Applied Science Problems
You Can Learn These Topics
Part 1:
Introduction
Fundamental Theory
Key Features
Biological Neuron
Artificial Neural Networks Architecture and Training Process
The Perceptron Network
Operating Principle of the Perceptron
The ADALINE Network and Delta Rule
Multiplayer Perceptron Network
Radial Basis Function Networks
Recurrent Hopfield Network
Self-Organizing Kohonen Network
LVQ and Counter Propagation Network
Adaptive Resonance Principle
Practical Work
Part 2:
Coffee Comprehensive Quality Estimate using Multiplayer Perceptron
Computer Networks Traffic Analysis Using SNNP Protocol and LVQ Networks
Forecast of Stock Market Trend Using Recurrent Networks
Computational Results
Recurrent Network Characteristics
Pattern Identification of Adulterants in Coffee Powders Using Kohonen Self-Organizing Map
Recognition of Disturbance Related to Electrical Power Quality Using MLP Networks
Characteristic of the MLP Networks
introduction
Characteristic of the Neural Network
Performance Analysis of RBF and MLP Networks in Pattern Classification
Solution of Constraint Optimization Problems Using Hopfield Networks