Application of Data Compression and Decompression Based on Artificial Neural Network and Collaborative Computer Network

Li Dong, Binpeng Qu, Meng Zhang, Jing Yu
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Abstract

Before data transmission, in order to improve the utilization ratio of transmission channel, there is need to compress the transmitted data. Before data storage, in order to save storage space, there is need to compress the stored data. There are many methods for data compression and decompression, but the existing methods may be not effective for some particular applications. Therefore, for the special applications, special compression and decompression methods should be applied, which means to combine neural network and collaboration cognitive model. When finite multi-dimensional data needs to transmit with long distance or store data for a long time, the method combining neural network and collaborative computer should be applied to implement compression and decompression of finite multi-dimensional data.
基于人工神经网络和协同计算机网络的数据压缩与解压缩应用
在数据传输之前,为了提高传输信道的利用率,需要对传输的数据进行压缩。在存储数据之前,为了节省存储空间,需要对存储的数据进行压缩。数据压缩和解压缩的方法有很多,但现有的方法可能对某些特定的应用不太有效。因此,对于特殊的应用,需要采用特殊的压缩和解压方法,即将神经网络与协作认知模型相结合。当有限多维数据需要远距离传输或长时间存储时,应采用神经网络与协同计算机相结合的方法对有限多维数据进行压缩与解压缩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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