An on-line universal lossy data compression algorithm via continuous codebook refinement - Part I: Basic results
An on-line universal lossy data compression algorithm via continuous codebook refinement - Part I: Basic results
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通过连续码本细化的在线通用有损数据压缩算法 - 第一部分：基本结果
DOI：
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发表时间：
1996
影响因子：
2.5
通讯作者：
V. Wei
中科院分区：
文献类型：
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作者：
Zhen Zhang;V. Wei
提出了一种新的在线通用损耗数据压缩算法。对于具有未知统计数据的有限记忆来源，其性能渐近地接近基本率失真极限。该代码簿是随机生成的，并不断地由简单的规则适应。没有单独的代码手册培训或代码簿传输。候选代码字是根据任意和可能次优的分布随机生成的。通过精心设计的“黄金洗涤”或“信息理论筛”机制，良好的代码字和只有良好的代码字可以促进具有很高可能性的永久状态。我们还确定算法接近基本限制的速率。
A new on-line universal lossy data compression algorithm is presented. For finite memoryless sources with unknown statistics, its performance asymptotically approaches the fundamental rate distortion limit. The codebook is generated on the fly, and continuously adapted by simple rules. There is no separate codebook training or codebook transmission. Candidate codewords are randomly generated according to an arbitrary and possibly suboptimal distribution. Through a carefully designed "gold washing" or "information-theoretic sieve" mechanism, good codewords and only good codewords are promoted to permanent status with high probability. We also determine the rate at which our algorithm approaches the fundamental limit.