Applications of a connection code computer for neural network calculations

A model of a connection code computer, which we proposed as a reconfigurable hardware, is developed for modelling neural networks. This hardware is able to speed up the parallel and pipelined calculations by realizing the optimal composition (hardware structure) for various problems. As an example, one of typical neural network models, the backpropagation model, is simulated. Each component is improved to reduce the chip-size. All components are designed and are implemented to check the sizes and their performance