C++ Neural Networks and Fuzzy Logic: Preface

C++ Implementation

In our C++ implementation of a discrete bidirectional associative memory network, we create classes for

neuron and network. Other classes created are called exemplar, assocpair, potlpair, for the exemplar pair

of vectors, associated pair of vectors, and potential pairs of vectors, respectively, for finding heteroassociation

between them. We could have made one class of pairvect for a pair of vectors and derived the exemplar and

C++ Neural Networks and Fuzzy Logic:Preface

Recall of Vectors

157

---

so on from it. The network class is declared as a friend class in these other classes. Now we present the

header and source files, called bamntwrk.h and bamntwrk.cpp. Since we reused our previous code from the

Hopfield network of Chapter 4, there are a few data members of classes that we did not put to explicit use in

the program. We call the neuron class bmneuron to remind us of BAM.