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Adnan Ahmed Khan edited this page Jan 19, 2021 · 2 revisions

Single Input Neuron

What is a Single Input Neuron?

A single-input neuron is shown in figure above. The scalar input p is multiplied by the scalar weight w to form wp, one of the terms that is sent to the summer. The other input, 1 , is multiplied by a bias b and then passed to the summer. The summer output n, often referred to as the net input, goes into a transfer function f , which produces the scalar neuron output a.(The term “activation function” is often used rather than transfer function and “offset” rather than bias.)

If we relate this simple model to the biological neuron shown below, the weight w corresponds to the strength of a synapse, the cell body is represented by the summation and the transfer function, and the neuron output a represents the signal on the axon.

Single Biological Neuron

The bias is much like a weight, except that it has a constant input of 1. However, if you do not want to have a bias in a particular neuron, it can be omitted. Note that w and b are both adjustable scalar parameters of the neuron. Typically the transfer function is chosen by the designer and then the parameters w and b will be adjusted by some learning rule so that the neuron input/output relationship meets some specific goal.

Sources

Neural Network Design

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