Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Guest editorial - Special issue on neural networks hardware implementations
IEEE Transactions on Neural Networks
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In this paper we present and analyze an artificial neural network hardware engine, its architecture and implementation. The engine was designed to solve performance problems of the serial software implementations. It is based on a hierarchical parallel and parameterized architecture. Taking into account verification results, we conclude that this engine improves the computational performance, producing speedups from 52.3 to 204.5 and its architectural parameterization provides more flexibility.