图像压缩的自关联神经网络:大规模并行实现

Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop Pub Date : 1992-08-31 DOI:10.1109/NNSP.1992.253675

A. Basso

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引用次数: 1

摘要

提出了一种基于神经网络的图像压缩技术在关联字符串处理器(ASP)机上的大规模并行实现。尽管ASP的结构是线性的，并且使用了固定的算法来实现，但在学习速度(每秒10/sup / 9/连接)和重建图像的质量方面显示出了令人鼓舞的结果。

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Autoassociative neural networks for image compression: a massively parallel implementation

A massively parallel implementation on the associative string processor (ASP) machine of a neural-network-based technique for image compression is presented. Despite the linear structure of the ASP and the use of fixed arithmetic for the implementation, promising results are shown in terms of learning speed, on the order of 10/sup 9/ connections per second, and the quality of the reconstructed images.<>

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Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop

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