Artificial Neural Networks

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CULTURE AND SOCIETY, EDUCATION

Artificial Neural Networks

BY AAP Bridge at AAPBridge

The idea of ANNs is based on the belief that the working of the human brain by making the right connections, can be imitated using silicon and wires as living neurons and dendrites. The human brain is composed of 86 billion nerve cells called neurons. They are connected to other thousand cells by Axons. Stimuli from external environment or inputs from sensory organs are accepted by dendrites. These inputs create electric impulses, which quickly travel through the neural network. A neuron can then send the message to another neuron to handle the issue or does not send it forward.

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INSTRUCTIONS:

ANNs are composed of multiple nodes, which imitate the biological neurons of the human brain. The neurons are connected by links and they interact with each other. The nodes can take input data and perform simple operations on the data. The result of these operations is passed to other neurons. The output at each node is called its activation or node value.

Each link is associated with weight. ANNs are capable of learning, which takes place by altering weight values

Two Artificial Neural Network topologies: − FeedForward and Feedback

INSTRUCTIONS:

In this ANN, the information flow is unidirectional. A unit sends information to another unit from which it does not receive any information. There are no feedback loops. They are used in pattern generation/recognition/classification. They have fixed inputs and outputs.

feedback loops are allowed. They are used in content-addressable memories.