2019’s Best Artificial Neural Network PDF Books, Notes, Course Data and Tutorials

Here you will get access to free Artificial Neural Network PDF Books, Notes and courses that will help you to boost your ANN skills.

Introduction to Artificial Neural Network (ANN)

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems ‘learn’ to perform tasks by considering examples, generally without being programmed with any task-specific rules. For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as cat or no cat and using the results to identify cats in other images. They do this without any prior knowledge about cats, e.g., that they have fur, tails, whiskers and cat-like faces. Instead, they automatically generate identifying characteristics from the learning material that they process.

An ANN is based on a collection of connected units or nodes called artificial neurons which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it.

This Outline Will be similar with your University 2019 Course Outline for Artificial Neural Network Subject.

Introduction to cybernetics, Brain and Neural System as Cybernetics, Type of Neural Networks, Static and Dynamic Neural Networks, Neuron Models. Network Architecture and Toplogy, Training and Validation Procedure,  Perceptron, Hamming Network, Feed forward Layer, Recurrent Layer, Perceptron Learning Rule, Proof of Convergence, Signals and Weight Vector Space, Linear Transformation, Performance Surface and Optimization, Hebbian and Widrow-Hoff Learning, Back-propagation and Variations. Associative Learning, Competitive Networks using SOM, Biological Motivation for Vision using Grossberg Network, Adaptive Resonance Theory, Hopfield Network, Cellular Neural Network. Evolutionary Neural Network, Spike Neural Networks, Application of Neural Networks in Signal and Image Processing, Bioinformatics, Telecommunication and High Energy Physics. Quantum Neural Networks.ata warehouse maintenance.

Best Recommended Artificial Neural Network PDF Books, Tutorials and Notes for Universities:

Here is detailed list of best Artificial Neural Networks books for Universities:

  • Neural Network Design, Martin T. Hagan, Howard B. Demuth, Mark H. Beale
  • An Introduction to Neural Networks by James A a Anderson
  • Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition by Sandhya Samarasinghe PDF Book

Free Artificial Neural Network PDF Notes and Books and Helping Material to Download

Neural Network Design, Martin T. Hagan, Howard B. Demuth, Mark H. Beale PDF Book

Neural Network Design, Martin T. Hagan, Howard B. Demuth, Mark H. Beale PDF Book free download

An Introduction to Neural Networks by James A a Anderson PDF Book

Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition by Sandhya Samarasinghe PDF Book

Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition by Sandhya Samarasinghe PDF Book free download

Artificial Neural Networks (ANN) Video Tutorials

Artificial Neural Networks by Astral1911

Beginner Introduction to Neural Networks by giant_neural_network

Artificial neural networks by tuwa kuksy

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