C++ Neural Networks and Fuzzy Logic: Preface

Figure 7.2

  Class hierarchy used in the backpropagation simulator.

Function overloading can be seen in the definition of the calc_error() function. It is used in the input_layer

with no parameters, while it is used in the output_layer (which the input_layer inherits from) with one

parameter. Using the same function name is not a problem, and this is referred to as overloading. Besides

function overloading, you may also have operator overloading, which is using an operator that performs some

familiar function like + for addition, for another function, say, vector addition.

When you have overloading with the same parameters and the keyword virtual, then you have the potential

for dynamic binding, which means that you determine which overloaded function to execute at run time and

not at compile time. Compile time binding is referred to as static binding. If you put a bunch of C++ objects in

an array of pointers to the base class, and then go through a loop that indexes each pointer and executes an

overloaded virtual function that pointer is pointing to, then you will be using dynamic binding. This is exactly

the case in the function calc_out(), which is declared with the virtual keyword in the layer base class. Each

descendant of layer can provide a version of calc_out(), which differs in functionality from the base class, and

the correct function will be selected at run time based on the object’s identity. In this case calc_out(), which is

a function to calculate the outputs for each layer, is different for the input layer than for the other two types of

layers.

Let’s look at some details in the header file in Listing 7.1: