Adaptive Data Compression

Author:   Ross N. Williams
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1991
Volume:   110
ISBN:  

9781461368106


Pages:   382
Publication Date:   13 February 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Adaptive Data Compression


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Overview

Following an exchange of correspondence, I met Ross in Adelaide in June 1988. I was approached by the University of Adelaide about being an external examiner for this dissertation and willingly agreed. Upon receiving a copy of this work, what struck me most was the scholarship with which Ross approaches and advances this relatively new field of adaptive data compression. This scholarship, coupled with the ability to express himself clearly using figures, tables, and incisive prose, demanded that Ross's dissertation be given a wider audience. And so this thesis was brought to the attention of Kluwer. The modern data compression paradigm furthered by this work is based upon the separation of adaptive context modelling, adaptive statistics, and arithmetic coding. This work offers the most complete bibliography on this subject I am aware of. It provides an excellent and lucid review of the field, and should be equally as beneficial to newcomers as to those of us already in the field.

Full Product Details

Author:   Ross N. Williams
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1991
Volume:   110
Dimensions:   Width: 16.00cm , Height: 2.10cm , Length: 24.00cm
Weight:   0.655kg
ISBN:  

9781461368106


ISBN 10:   1461368103
Pages:   382
Publication Date:   13 February 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1: Introductory Survey.- 2: The DHPC Algorithm.- 3: A Classification of Adaptivity.- 4: An Experimental Adaptive Algorithm.- 5: A Multimodal Algorithm.- 6: Applications to User Interfaces.- 7: Conclusions.- Appendix A: Estimation Formula Calculation.- Appendix B: The Word “Adapt” And Its Forms.- Appendix C: User Input Experiments.- C.1 Introduction.- C.2 Experiment 22: Redundancy of User Input.- C.3 Experiment 23: Timing Between Keystrokes.- Appendix D: Further Research.- D.1 The SAKDC Algorithm.- D.2 The MMDC Algorithm.- D.1 User Interfaces.- Appendix E: Summary of Notation.- References.

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