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Artificial Neural Network (Units (Nodes, Links, Activation Function,…
Artificial Neural Network
Introduction
A information processing paradigm that is inspired by the way biological nervous systems like brain
composed of a large number of highly interconnected processing elements (neurons)
Learns like humans
Characteristics
Adaptive Learning
Self-Organization
Real Time Operation
Fault Tolerance
Units
Nodes
Links
Activation Function
Weight
Bias
Types
Feedforward Network
Recurrent Neural Network
Time Delay Neural Network
Hoppfield Network
Perceptron
Takes several binary inputs and gives a single binary output
Sigmoid Neurons
Like P
erceptron except it outputs values between 0 and 1
Applications
Clustering
Predictions
Classifications
Pattern Recognitions