Approximation theory: Difference between revisions
imported>Igor Grešovnik (added See also) |
mNo edit summary |
||
| (5 intermediate revisions by 5 users not shown) | |||
| Line 1: | Line 1: | ||
{{subpages}} | |||
In [[mathematics]], '''approximation theory''' is concerned with how [[Function (mathematics)|functions]] can be best [[approximation|approximated]] with simpler functions, and with quantitatively characterising the [[approximation error|errors]] introduced thereby. What is meant by ''best'' and ''simpler'' will depend on the application. | In [[mathematics]], '''approximation theory''' is concerned with how [[Function (mathematics)|functions]] can be best [[approximation|approximated]] with simpler functions, and with quantitatively characterising the [[approximation error|errors]] introduced thereby. What is meant by ''best'' and ''simpler'' will depend on the application. | ||
Approximation theory has many applications, especially in [[numerical computation]], [[physics]], [[engineering]] and [[computer science]]. There are two main applications of approximations. The first is approximating safisticated functions in a computer mathematical library, using simpler operations that can be performed on the computer (e.g. addition and multiplication), such that the result is as close to the actual function as possible. This is typically done with polynomial or rational approximations. The second is obtaining approximate values of real-world function (known on the grid) between the points of the grid.[[Category:Suggestion Bot Tag]] | |||
Latest revision as of 06:00, 12 July 2024
In mathematics, approximation theory is concerned with how functions can be best approximated with simpler functions, and with quantitatively characterising the errors introduced thereby. What is meant by best and simpler will depend on the application.
Approximation theory has many applications, especially in numerical computation, physics, engineering and computer science. There are two main applications of approximations. The first is approximating safisticated functions in a computer mathematical library, using simpler operations that can be performed on the computer (e.g. addition and multiplication), such that the result is as close to the actual function as possible. This is typically done with polynomial or rational approximations. The second is obtaining approximate values of real-world function (known on the grid) between the points of the grid.