The gzip compressor is based on the DEFLATE lossless data compression algorithm, which USES a combination of the LZ77 algorithm and Huffman coding.
gzip压缩器基于deflate无损数据压缩算法,它使用LZ77算法和Huffman编码的组合。
Lossless compression based on Huffman coding (lossless data compression) and decompression algorithms.
基于Huffman编码的无损压缩(lossless data compression)和解压缩算法。
First, the new scheme of a lossless data compression based on neural network is given by using non-statistical method.
本文首先采用非统计的方法给出了基于神经网络的无损数据压缩新方案。
The paper describes a real-time lossless data compression algorithm for both individual band and multi-spectral remote sensing images.
讨论了对单波段遥感图像和多波段遥感图像都适用的一种实时无失真数据压缩的方法。
A lossless data compression scheme based on neural network is obtained through the structure specific mapping, integral function and BP neural network.
通过构造特别的映射、整函数和BP神经网络,获得一套基于神经网络的无损数据压缩方案。
Finally, how the lossless data compression was integrated into the CCSDS-based on-board data systems was studied.
最后讨论了CCSDS无损数据压缩标准是如何融入CCSDS体制的星载数据系统中的。
In the computer information processing, "Huffman coding" is a consistent coding method (also known as "entropy coding method") for lossless data compression.
在计算机信息处理中,“哈夫曼编码”是一种一致性编码法(又称“熵编码法”),用于数据的无损耗压缩。
A lossless data compression algorithm takes a string of symbols and translates it reversibly into another string, one that is on the average of shorter length.
一个无损压缩算法就是将代表字符的序列通过可逆变换变化成为一个新的序列,通过这样的变换使它的平均长度变短。
Taking the remote noise data as the object of the research, the paper discussed the application of lossless data compression technology in the field of data acquisition.
本文主要以火箭发射时的遥测噪声数据为研究对象,探索研究了无损数据压缩技术在数据采集系统中的应用。
Bonus: Lossless data compression cannot guarantee compression for all data input files.
额外收获:无损耗数据压缩不能保证对所有输入的数据文件进行压缩。
Lossless data compression is one of the major services in space flight missions and remote-sensing systems.
无损数据压缩是航天应用和遥感系统的重要业务之一。
Lossless data compression is one of the major services in space flight missions and remote-sensing systems.
无损数据压缩是航天应用和遥感系统的重要业务之一。
应用推荐