Time-universal data compression and prediction

09/09/2018
by   Boris Ryabko, et al.
0

Suppose there is a large file which should be transmitted (or stored) and there are several (say, m) admissible data-compressors. It seems natural to try all the compressors and then choose the best, i.e. the one that gives the shortest compressed file. Then transfer (or store) the index number of the best compressor (it requires log m bits) and the compressed file.The only problem is the time, which essentially increases due to the need to compress the file m times (in order to find the best compressor). We propose a method that encodes the file with the optimal compressor, but uses a relatively small additional time: the ratio of this extra time and the total time of calculation can be limited by an arbitrary positive constant. Generally speaking, in many situations it may be necessary find the best data compressor out of a given set, which is often done by comparing them empirically. One of the goals of this work is to turn such a selection process into a part of the data compression method, automating and optimizing it.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/08/2023

Compression Performance Analysis of Different File Formats

In data storage and transmission, file compression is a common technique...
research
01/01/2022

X3: Lossless Data Compressor

X3 is a lossless optimizing dictionary-based data compressor. The algori...
research
02/18/2020

How incomputable is Kolmogorov complexity?

Kolmogorov complexity is the length of the ultimately compressed version...
research
05/17/2019

Parallel decompression of gzip-compressed files and random access to DNA sequences

Decompressing a file made by the gzip program at an arbitrary location i...
research
04/24/2019

Reconstruct the Directories for In-Memory File Systems

Existing path lookup routines in file systems need to construct an auxil...
research
12/22/2015

A Novel Approach to Compress Centralized Text Data using Indexed Dictionary

Data compression is very important feature in terms of saving the memory...
research
11/10/2017

In-Depth Exploration of Single-Snapshot Lossy Compression Techniques for N-Body Simulations

In situ lossy compression allowing user-controlled data loss can signifi...

Please sign up or login with your details

Forgot password? Click here to reset