Titlebook: Neural Computers; Rolf Eckmiller,Christoph Malsburg Conference proceedings 1989 Springer-Verlag Berlin Heidelberg 1989 artificial intellig

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The Role of Adaptive and Associative Circuits in Future Computer Designss speech and images; these functions, however, have now been abandoned. Some vistas to sixth- and later-generation computers have already been presented, too. The latter are supposed to be even more “natural”. Certainly the fifth-generation computers have applied very traditional logic programming,

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Faust, Mephistopheles and Computerlso introduces the concept of the Satan, embodying the bad and evil. The antagonisme between the good and bad principle dominates all our life. There always is a difference between pleasant and unpleasant events.

interference

Goal and Architecture of Neural Computersal includes construction of a generalized scene. Some of the necessary sub-goals have been demonstrated on the basis of neural architecture, but this architecture has to be further developed. Major issues are the reduction of learning times, the integration of subsystems and the introduction of synt

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Conventional Fault-Tolerance and Neural Computers objectives. A wide range of techniques have been used according to the particular objectives and the system architecture. Almost all of these techniques can be observed in biological neural networks and may even be in use simultaneously. This paper suggests that VLSI designers may wish to incorpora

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Fault-Tolerance in Imaging-Oriented Systolic Arraysic multi-pipeline structure..Practical implementations require large pipelines, adopting highly integrated circuits that are prone to production defects and run-time faults; efficient fault-tolerance through reconfiguration is then required..Still, the basic problem of concurrent (or semi-concurrent

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A Hierarchical Neural Network Model for Selective Attentioned on a digital computer. The model has the function of segmentation and pattern-recognition. When a composite stimulus consisting of two patterns or more is presented, the model focuses its attention selectively to one of them, segments it from the rest, and recognizes it. After that, the model swi

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Computing Motion in the Presence of Discontinuities: Algorithm and Analog Networksoblem to its solution by minimizing certain “cost” functions. These cost or energy functions can be mapped onto very simple analog and binary resistive networks. Thus, we will see how the optical flow can be computed by injecting currents into “neural” networks and recording the resulting stationary