Alfred Strey

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A neural network specification language is presented that can be used for the high-level description of artificial and biology-oriented neural networks. The main objective of the language design is the support of the inherent parallelism of neural networks so that efficient simulation code for parallel computers and neurocomputer architectures can be(More)
A new methodology for the generation of efficient parallel programs from high-level neural network specifications is presented. All possible mappings of the neural network onto the parallel processors are generated and evaluated by using a description of the parallel target architecture. Thus the optimal mapping can be determined at compile-time and(More)
In this article the neural network speciication language EpsiloNN is presented. From an abstract speciication that is independent of the target computer architecture, a simulation source program for a workstation or a parallel computer can be generated. Neurocomputers requiring xed-point data types and arithmetic are supported too. The language design is(More)
The correlation between two signals (cross correlation) is a standard approach to feature detection. The normalized form of cross correlation (normalized correlation coefficient) is particularly used for template matching. In this case, the two-dimensional correlation of images is considered. One of its biggest drawbacks is the need for a lot of(More)