Neural Network Class Library

• Node.h declares a class template for a generic node object. A node is defined by weighted input and output connections to other nodes, and an output value.
• Weight.h declares a class template for a weighted connection from one node to another. The attributes of a weighted connection are a weight, a pointer to the connected node, and the last change made in the weight.
• FeedforwardNode.h declares an abstract base class to represent nodes in feedforward networks. Derived from the Node class, it adds an error attribute and a logistic activation function.
• BackpropagationNode.h declares a class which extends the FeedforwardNode class by adding the functionality necessary for the backpropagation algorithm.
• Node.cpp, Weight.cpp, FeedforwardNode.cpp, and BackpropagationNode.cpp define the relevant member functions.
• DataVector.h declares a container class template for holding network training vectors; DataVector.cpp defines the relevant class functions.

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