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Research draft

data compression

vr.tr.data-compression · ACT.ACT

Let an agent explain data compression and its methods, relay theory, algorithms and applications from computer science sources, describe the techniques the registry aliases name, and distinguish compression from encryption, deduplication, archiving and probabilistic data structures.

Thing Registry Activities and processes

Research draft, second pass

A second pass drafted this model: the structure a model of this thing needs, and what is known about it in the world. The line under this one says how the second half was obtained - researched against sources, or recalled without web access, in which case nothing here was read anywhere and every claim is a lead to verify. Unreviewed either way.

written by Claude from model knowledge without web access - no source was read, every claim is a lead to verify

Researched by: Claude

Purpose and description

Let an agent explain data compression and its methods, relay theory, algorithms and applications from computer science sources, describe the techniques the registry aliases name, and distinguish compression from encryption, deduplication, archiving and probabilistic data structures.

The process of encoding information using fewer bits than the original representation, either lossless, allowing exact reconstruction through entropy coding and dictionary methods, or lossy, discarding less important information as in JPEG and MP3, including executable compression, solid compression of many files as one stream in archivers, dataset compression and model compression of neural networks by pruning and quantisation; approximate membership query filters such as Bloom filters are related space-efficient data structures rather than compression per se.

What it is for: Reducing data size for storage and transmission.

It can be explain lossless and lossy compression; relay algorithms and theory; describe named techniques; distinguish related concepts.

Distinguishing features

Fewer bits

Lossless or lossy

Entropy bounds

Ubiquitous

What it looks like

Not a visible object; smaller encoded files.

Physical character

Shannon source coding theorem: 1948 year

Huffman coding: 1952 year

LZ77: 1977 year - Lempel and Ziv

JPEG standard: 1992 year

How it is recognised

Encoding data in fewer bits

Entropy coding, executable compression, solid compression, dataset and model compression; AMQ filters as related

Encryption hides content; deduplication removes copies; archiving bundles files; Bloom filters answer membership queries

Related models

is a kind of - in registry terms

data processing

is bounded by -

entropy (information theory)

includes -

Huffman coding

is contrasted with -

encryption

In practice

Families and kinds

entropy coding such as Huffman and arithmetic coding

dictionary methods such as LZ77 and LZW

lossy media codecs

executable compression

solid archive compression

model compression for neural networks

Standards and regulation

Codec standards such as JPEG, MPEG and zlib RFC 1950

Patent and licensing regimes for codecs

Failure modes and hazards

Quality loss in lossy compression

Compression bombs

Registry aliases mixing compression and filters

Also called

Approximate Membership Query Filterexecutable compressionmodel compressiondataset compressionentropy codingsolid compressionvideo compressiontoken-based compressionsource codingspeech codingimage compressionlossless compressionlossy compressiondictionary coderminificationaudio compressionmodel quantizationFibonacci codingAsymmetric Numeral Systemsadaptive codingTunstall codingAlgebraic code-excited linear predictionContinuously variable slope delta modulationPDC-EFRfractal compressiontexture compressionLZ77 and LZ78PumpingLuminance-Alpha Texture Compression

Where this came from

wikidata · CC0 1.0

Drafted structure

Bundle to layer to finding to question, as the second pass will find it: 4 bundles · 8 layers · 8 findings · 16 questions.

Understand What data compression is.

Science.

Definition

Definition.

Definition

Definition.

  1. What is data compression, and how does it differ from encryption, deduplication, archiving and probabilistic filters? definition
  2. Is the question about theory, an algorithm, a format or a specific application? boundary

Techniques

Named techniques.

Techniques

Techniques.

  1. What are entropy coding, executable, solid, dataset and model compression, and AMQ filters? definition
  2. Which entry fits the specific technique? action
Theory Theory.

Science.

Entropy

Information theory.

Entropy

Entropy.

  1. How does Shannon entropy bound lossless compression? provenance
  2. Which references are standard? provenance

Algorithms

Algorithms.

Algorithms

Algorithms.

  1. How do Huffman, arithmetic, LZ and transform coding work? provenance
  2. Which sources are cited? provenance
Applications Applications.

Application.

Media

Media codecs.

Media

Media.

  1. How do lossy codecs for images, audio and video work? provenance
  2. Which entry fits JPEG? action

ML

Model compression.

ML

ML.

  1. How are neural networks compressed by pruning, quantisation and distillation? provenance
  2. Which entry fits quantization (machine learning)? action
Context History and security.

Context.

History

History.

History

History.

  1. How did compression develop from Morse code to modern codecs? provenance
  2. Which entry fits the history of data compression? action

Security

Security issues.

Security

Security.

  1. What risks such as compression bombs and side channels exist, at a general level? provenance
  2. Which entry fits zip bomb? action

What the second pass must settle

  • Should model compression and solid compression be separate primary entries?
  • How should computer science sources be linked?
  • The registry alias approximate membership query filter is a data structure rather than compression; should it be split off?