Artificial Neural Networks

Artificial Neural Networks are the simulations which performs specific tasks like pattern recognition, clustering etc. on computer.

Artificial neural networks are mathematical models inspired by the organization and functioning of biological neurons.  They are similar to the human brains, acquire knowledge through learning and their knowledge is stored within inter neuron connections strengths known as synaptic weights.

Architecture of ANN

A large number of artificial neurons called units arranged in a series of layers are contained by neural networks. Different layers are Input layer, Output layer and Hidden layer.

  • Input layer contains those units which receives input from outside world on which network will learn and recognise about the process.
  • Output layer contains units that respond to the information about how it’s learned any task.
  • Hidden layer are in between input and output layers. It transforms the input in to something that output unit can use in some ways.

  • Advances in Artificial Neural Systems
  • ANN Controller for automatic ship berthing
  • ANN in Estimating Participation in Electrons
  • Adaptive Neuro Fuzzy Interface System
  • Parallel growing and training of neural networks using ouput parallelism

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