Lossy Compression of Individual Sequences Revisited: Fundamental Limits of Finite-State Encoders

Author:

Merhav Neri1

Affiliation:

1. The Viterbi Faculty of Electrical and Computer Engineering, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel

Abstract

We extend Ziv and Lempel’s model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless finite-state encoder that compresses the reconstruction codeword with no additional distortion. We first derive two different lower bounds to the compression ratio, which depend on the number of states of the lossless encoder. Both bounds are asymptotically achievable by conceptually simple coding schemes. We then show that when the number of states of the lossless encoder is large enough in terms of the reconstruction block length, the performance can be improved, sometimes significantly so. In particular, the improved performance is achievable using a random-coding ensemble that is universal, not only in terms of the source sequence but also in terms of the distortion measure.

Publisher

MDPI AG

Reference39 articles.

1. Berger, T. (1971). Rate Distortion Theory—A Mathematical Basis for Data Compression, Prentice-Hall Inc.

2. Cover, T.M., and Thomas, J.A. (2006). Elements of Information Theory, John Wiley & Sons.

3. Gallager, R.G. (1968). Information Theory and Reliable Communication, John Wiley & Sons.

4. Gray, R.M. (1990). Source Coding Theory, Kluwer Academic Publishers.

5. Viterbi, A.J., and Omura, J.K. (1979). Principles of Digital Communication and Coding, McGraw-Hill Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3