Artificial Neural Networks (ANN)

A Neural Network is a massively parallel distributed processor that
has a natural propensity for storing experiential knowledge and
making it available for use
--Haykin

Neural networks are composed of simple elements operating in parallel. These
elements are inspired by biological nervous systems. As in nature, the
connections between elements largely determine the network function. You
can train a neural network to perform a particular function by adjusting the
values of the connections (weights) between elements.
Typically, neural networks are adjusted, or trained, so that a particular input
leads to a specific target output.

Neural networks have been trained to perform complex functions in various
fields, including pattern recognition, identification, classification, speech,
vision, and control systems.
Neural networks can also be trained to solve problems that are difficult for
conventional computers or human beings. The toolbox emphasizes the use of
neural network paradigms that build up to—or are themselves used in—
engineering, financial, and other practical applications.