CHAPTER 4 – Software Tools

Publisher Summary This chapter describes software tools to model, specify, and run neural networks on PCs and explains the way by which a network specification is turned into working code. It focuses on low-level programming tools for implementing networks. Neural network software implements neural networks on a hardware platform. The terms artificial neural network and neural network simulation are often used to describe the software. The chapter describes forward and backward passes of the neural network. In a backward pass, the error signals are propagated backward through the network, starting at the output layer. The error term (or delta) at the output layer, delta2, is computed from the difference between the actual output and the desired target values for each node in the output layer, for each training pattern: delta2 = (target - out2) * out2 * (1 - out2), where out2 is the activation vector at the output layer, and target is the target vector (desired network reponse).