Difference between revisions of "Cyclic Redundancy Check Value"

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{{#set:abbreviation=* CRC
 
{{#set:abbreviation=* CRC
 
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=== Definition ===
 
=== Definition ===
 
{{#set:definition=The value determined by applying a Cyclic Redundancy Check (CRC) to a dataset.
 
{{#set:definition=The value determined by applying a Cyclic Redundancy Check (CRC) to a dataset.
 
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=== Definition Source ===
 
=== Definition Source ===
 
{{#set:defsource=* AIFDD
 
{{#set:defsource=* AIFDD
 
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=== Note ===
 
=== Note ===
 
{{#set:note=A CRC is a mathematical algorithm applied to the digital expression of data that provides a level of assurance against loss or alteration of data. Best practice recommends that the algorithm consider all tags and data elements within a dataset. When the receiver applies a CRC algorithm to the dataset, a different CRC value indicates that a tag or data element within the dataset has been changed since the sender generated the original CRC value.
 
{{#set:note=A CRC is a mathematical algorithm applied to the digital expression of data that provides a level of assurance against loss or alteration of data. Best practice recommends that the algorithm consider all tags and data elements within a dataset. When the receiver applies a CRC algorithm to the dataset, a different CRC value indicates that a tag or data element within the dataset has been changed since the sender generated the original CRC value.
 
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{{#ask: [[Cyclic Redundancy Check Value]] | ?note= }}
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{{#ask: [[Cyclic Redundancy Check Value]] | ?note= |mainlabel=- }}
 
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Revision as of 09:50, 5 July 2016

Link Semantic Value
Term Cyclic Redundancy Check Value
Status


Mandatory for


Contexts


Categories


Synonyms


Related entries


Broader term

Cyclic Redundancy Check (CRC)

Narrower term


Abbreviation

  • CRC

Definition

The value determined by applying a Cyclic Redundancy Check (CRC) to a dataset.

Definition Source

  • AIFDD

Note

A CRC is a mathematical algorithm applied to the digital expression of data that provides a level of assurance against loss or alteration of data. Best practice recommends that the algorithm consider all tags and data elements within a dataset. When the receiver applies a CRC algorithm to the dataset, a different CRC value indicates that a tag or data element within the dataset has been changed since the sender generated the original CRC value.