Modeling of intelligent calculations in cubic network of workstations

Article describes model of computation with feedforward multilayer neural network implemented in the network of workstations with cubic topology. Presented computation model is based on parallel error backpropagation algorithm with regard to characteristics of simulations implementation architecture. Effectivity of parallel implementation of feedforward multilayer neural network is represented trough the cost of computation in parallel environment of workstations. Designed computation model allows formally describe components of parallel implementation of neural network. Model provides mathematical instrument for verification of performance, used in simulation of feedforward multilayer neural network on specified hardware platform.