Introduction and Single-Input Neuron

A neural network is an adaptive system that can change its model by learning external and/or internal data. There are many applications from using a neural network:

• Pattern Recognition, such as image and speech.
• Function Estimation, such as quadratic function and time series prediction.
• Classification, such as pattern and sequence recognition.
• etc.
  

Single-Input Neuron

This is the simplest model of a neural network.




















f is a transfer function. This is the list of transfer functions which are used frequently:
Name: Hard Limit (hardlim)
Input/Output Relation:
a = 0 when n <.0.

a = 1 when n ≥ 0

Name: Saturating Linear (satlin)
Input/Output Relation:
a = 0 when n <.0.

a = n when 0 ≤ n ≤ 1

a = 1 when n > 1

Name: Symmetric Saturating Linear (satlins)
Input/Output Relation:
a = -1 when n < -1
a = n when -1 ≤ n ≤ 1
a = 1 when n > 1

Name: Log-Sigmoid (logsig)
Input/Output Relation:





Name: Hyperbolic Tangent Sigmoid (tansig)
Input/Output Relation: