C++ Neural Networks and Fuzzy Logic: Preface

Connection weight

A numerical label associated with a connection and used in a weighted sum of inputs.

Constraint

A condition expressed as an equation or inequality, which has to be satisfied by the variables.

Convergence

Termination of a process with a final result.

Crisp

The opposite of fuzzy—usually a specific numerical quantity or value for an entity.

D

Delta rule

A rule for modification of connection weights, using both the output and the error obtained. It is also

called the LMS rule.

E

Energy function

A function of outputs and weights in a neural network to determine the state of the system, e.g.,

Lyapunov function.

Excitation

Providing positive weights on connections to enable outputs that cause a neuron to fire.

Exemplar

An example of a pattern or object used in training a neural network.

Expert system

A set of formalized rules that enable a system to perform like an expert.