Convolutional code

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Map view:

Zoom: 100%

More settings

Connection length 100% Label size 100% Node size 100% Line width 100% Label width 100%

Export map as:

Convolutional code topic overview

The analysis highlights History and Applications as prominent areas in the source structure around Convolutional code.

Related topics: 55
Source areas: 12
Connected nodes: 67
Extracted relationships: 81
Concept neighborhoods: 31
Bridge connections: 67

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Decoding convolutional codes · 8 topics

History · 8 topics

Overview · 7 topics

Convolutional encoding · 6 topics

Impulse response, transfer function, and constraint length · 6 topics

Where convolutional codes are used · 6 topics

Popular convolutional codes · 5 topics

Recursive and non-recursive codes · 3 topics

Punctured convolutional codes · 2 topics

Turbo codes: replacing convolutional codes · 2 topics

Free distance and error distribution · 1 topics

Trellis diagram · 1 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Telecommunication Telecommunications
Error-correcting code Error correction code
Boolean polynomial Algebraic normal form
Trellis Trellis (graph)
Code rate
Block codes Block code
Symbol puncturing Punctured code

History

Where convolutional codes are used

Digital video
Mobile communications Mobile telephony
Satellite communications Communications satellite
Concatenation Concatenated error correction code
Reed–Solomon Reed–Solomon error correction
Shannon limit Shannon–Hartley theorem

Convolutional encoding

Memory registers Processor register
Adders Adder (electronics)
Boolean Boolean algebra
XOR gate
Generator polynomials Polynomial code
Bit shift Bitwise operation

Recursive and non-recursive codes

Systematic Systematic code
LDPC Low-density parity-check code
Serial concatenated convolutional codes

Impulse response, transfer function, and constraint length

Convolution
Linear time-invariant system LTI system
Transfer function
Z-transform
Rational function
Polynomial degrees Degree of a polynomial

Trellis diagram

Finite state machine Finite-state machine

Free distance and error distribution

Hamming distance

Decoding convolutional codes

Algorithms Algorithm
Maximum likelihood Maximum likelihood estimation
VLSI Very-large-scale integration
SIMD Single instruction, multiple data
Sequential decoding
Fano Robert Fano
Pioneer program
Maximum a posteriori Maximum a posteriori estimation

Popular convolutional codes

Punctured convolutional codes

Turbo codes: replacing convolutional codes

Shannon's theorem Noisy-channel coding theorem
Error floors Error floor

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Convolutional code connects Entity context

The extracted context around Convolutional code shows recurring relationship patterns in the source. For example, Convolutional code → Archived, Better Digital CommunicationsConvolutional, Chapter, Coding, Convolutional Decoders, David, ECC, Inference, Information Theory, Learning Algorithms, MacKay, MIT, PageMatlab, The, The Error Correcting Codes, TU Ilmenau, Wayback Machine Another extracted example is Convolutional code → CPUs, Fano, For, Jupiter, Longer, Pioneer, Reed, Saturn, Several, SIMD, Solomon, Such, Unlike Viterbi, Viterbi, Viterbi-decoded, VLSI. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

related to External links · 17

Convolutional code → Archived, Better Digital CommunicationsConvolutional, Chapter, Coding, Convolutional Decoders, David, ECC, Inference, Information Theory, Learning Algorithms, MacKay, MIT, PageMatlab, The, The Error Correcting Codes, TU Ilmenau, Wayback Machine

related to Decoding convolutional codes · 16

Convolutional code → CPUs, Fano, For, Jupiter, Longer, Pioneer, Reed, Saturn, Several, SIMD, Solomon, Such, Unlike Viterbi, Viterbi, Viterbi-decoded, VLSI

related to history · 11

Convolutional code → Andrew Viterbi, BCJR, Claude Berrou, Convolutional, In, It, Other, Peter Elias, Recursive, These, Viterbi

related to Where convolutional codes are used · 10

Convolutional code → Convolutional, EDGE, GPRS, GSM, Prior, Reed, Release, Shannon, Solomon, These

related to Punctured convolutional codes · 6

Convolutional code → Bits, Convolutional, For, It, Puncturing, The

related to Turbo codes: replacing convolutional codes · 6

Convolutional code → Concatenation, Reed, Shannon's, Simple Viterbi-decoded, Solomon, Viterbi

related to Free distance and error distribution · 5

Convolutional code → Hamming, It, Since, That, The

related to Popular convolutional codes · 5

Convolutional code → An, In, This, Viterbi-decoded, Voyager

is a · 2

Convolutional code → number of errors that can be corrected by the code, type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream

see also · 1

Convolutional code → Quantum

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

convolutional codes code encoder rate decoding length displaystyle input output data used also block constraint memory typically trellis systematic one

Convolutional code relationships Subject–Predicate–Object triples

TTTA extracted 81 structured relationships around Convolutional code. Examples in this analysis include Convolutional code → is a → type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream and Convolutional code → is a → number of errors that can be corrected by the code. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
Convolutional code	is a	type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream	0.90	text
Convolutional code	is a	number of errors that can be corrected by the code	0.90	text
turbo codes.Using the	instance of	These codes proved especially useful for iterative processing including the processing of concatenated codes	0.80	text
satellite links	instance of	Useful for SCCC's and multidimensional turbo codes.Useful as constituent code in low error rate turbo codes for applications	0.80	text
Convolutional code	related to Decoding convolutional codes	Several	0.60	section
Convolutional code	related to Decoding convolutional codes	For	0.60	section
Convolutional code	related to Decoding convolutional codes	Viterbi	0.60	section
Convolutional code	related to Decoding convolutional codes	VLSI	0.60	section
Convolutional code	related to Decoding convolutional codes	CPUs	0.60	section
Convolutional code	related to Decoding convolutional codes	SIMD	0.60	section
Convolutional code	related to Decoding convolutional codes	Longer	0.60	section
Convolutional code	related to Decoding convolutional codes	Fano	0.60	section

Related concept clusters Concept neighborhoods

The concept neighborhoods around Convolutional code bring nearby vocabulary together. In this analysis, examples include Codes, Convolutional and Used. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

Convolutional code
- Codes
- Convolutional
- Used
- Length
- Puncturing
- Decoding
- Rate
- Popular
- Punctured
- Errors
- Symbols
- Block
convolutional code
- Rate
- Codes
- Convolutional
- Used
- Length
- Puncturing
- Decoding
- Popular
- Errors
- Displaystyle
- Punctured
- Often
error-correcting code
- Rate
- Convolutional
- Used
- Puncturing
- Errors
- Displaystyle
- Codes
- Often
- Popular
- Punctured
- Symbols
- Example
code rate
- Rate
- Convolutional
- Puncturing
- Used
- Length
- Constraint
- Errors
- Displaystyle
- Popular
- Punctured
- Symbols
- Codes
block codes
- Convolutional
- Decoding
- Popular
- Typically
- Length
- Turbo
- Also
- Data
- Decoded
- Block
- Codes
- Systematic
turbo codes
- Convolutional
- Decoding
- Turbo
- Length
- Decoded
- Block
- Systematic
- Also
- Recursive
- Used
- Trellis
- Popular
serial concatenated convolutional codes
- Codes
- Convolutional
- Decoding
- Turbo
- Used
- Length
- Rate
- Popular
- Decoded
- Block
- Systematic
- Also
where convolutional codes are used
- Codes
- Convolutional
- Decoding
- Turbo
- Used
- Length
- Rate
- Popular
- Decoded
- Block
- Systematic
- Also

Connections between topic areas Semantic bridges

For Convolutional code, one of the stronger structural bridges in this analysis connects Convolutional code with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Convolutional code — History · splits 59 ⟂ 9

Convolutional code — Decoding convolutional codes · splits 59 ⟂ 9

Convolutional code — Overview · splits 60 ⟂ 8

Convolutional code — Where convolutional codes are used · splits 61 ⟂ 7

Convolutional code — Convolutional encoding · splits 61 ⟂ 7

Convolutional code — Impulse response, transfer function, and constraint length · splits 61 ⟂ 7

Convolutional code — Popular convolutional codes · splits 62 ⟂ 6

Convolutional code — Recursive and non-recursive codes · splits 64 ⟂ 4

Convolutional code — Punctured convolutional codes · splits 65 ⟂ 3

Convolutional code — Turbo codes: replacing convolutional codes · splits 65 ⟂ 3

Map overview Semantic statistics

Convolutional code

Nodes68

Edges67

Triples81

Avg. degree1.97

Density0.029412

Components1

Source & methodology

TTTA analyzes the structure around Convolutional code to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History & Applications, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Convolutional code · EN edition · Analysis: TopicsToTalkAbout

Convolutional code: History & Applications

Convolutional code topic overview

What this topic covers Research coverage

Key facts & relationships

Explore all related topics Closing gaps

Overview

History

Where convolutional codes are used

Convolutional encoding

Recursive and non-recursive codes

Impulse response, transfer function, and constraint length

Trellis diagram

Free distance and error distribution

Decoding convolutional codes

Popular convolutional codes

Punctured convolutional codes

Turbo codes: replacing convolutional codes

Advanced semantic analysis

How Convolutional code connects Entity context

Convolutional code

Top relations

Important terminology

Important terminology

Convolutional code relationships Subject–Predicate–Object triples

Related concept clusters Concept neighborhoods

Connections between topic areas Semantic bridges

Map overview Semantic statistics

Convolutional code

Source & methodology