一个通用随机编码组合用于样本智能的损耗压缩
1The Viterbi Faculty of Electrical and Computer Engineering, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel.
Entropy (Basel, Switzerland)
|August 26, 2023
概括
这项研究引入了一种用于速率扭曲代码的新型随机选择方法,在损耗压缩中实现了非对称的最佳性. 提出的基于Lempel-Ziv (LZ) 算法的方法优于现有的数据压缩方法.
科学领域:
- 信息理论 信息理论
- 数据压缩数据压缩
- 计算机科学 计算机科学
背景情况:
- 速率扭曲理论是损失数据压缩的基础.
- 佩尔-齐夫 (LZ) 算法被广泛用于无损数据压缩.
- 优化代码选择对于高效的压缩性能至关重要.
研究的目的:
- 为随机选择速率扭曲代码提出一个通用集合.
- 为了证明拟议的编码方案的非对称最佳性.
- 将新方案与现有方法进行比较.
主要方法:
- 基于与2-LZ ((x^) 相称的概率的生殖载体的随机选择.
- 使用 1978 年的 Lempel-Ziv (LZ) 算法对代码长度进行分析.
- 对于非对称的最佳性和反向定理的数学证明.
主要成果:
- 拟议的组合产生了一个异常最优的可变速率损耗压缩方案.
- 一个反向定理证实该方案的性能不能被基本改进.
- 与最短的LZ代码选择相比,新的编码方案显示出更高的性能.
结论:
- 全面组合在理论上提供了一个合理的,在实践中优越的速率扭曲编码方法.
- 这种方法通过优化代码选择推进了损失数据压缩领域的发展.
- 这些发现对设计更高效的压缩算法有影响.
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