An interactive object-oriented neural network simulator applied to the recognition of acoustical signals

An interactive object-oriented layer-based simulator is presented. It is intended for large-scale investigations of artificial neural networks (ANNs), and consists of two parts. The first is a simulation kernel, whose underlying base model is a layer of units, processing inputs to outputs. The core model has no knowledge of the ANN, but serves as a base for specialized layers. The second is the interactive counterpart, where by means of several windows, the actual state of the simulation can be visualized with variable amounts of information, and controlled, interacting with the layer as a whole, or with every single variable. Every specialized layer inherits from its parent layer both the simulation kernel and its interactive counterpart, modifies existing functions, and adds new variables and functions. Individual layers are combined by multiple inheritance. The simulator has been successfully applied to the recognition of acoustical signals.<
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