東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Computable functions" ]

切換: 標籤 | MARC模式 | ISBD

Handbook of computability and comple...

Brattka, Vasco.

FindBook

Google Book

Amazon

博客來

Handbook of computability and complexity in analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Handbook of computability and complexity in analysis/ edited by Vasco Brattka, Peter Hertling.
其他作者:	Brattka, Vasco.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xxv, 427 p. :ill., digital ;24 cm.
內容註:	Part I, Computability in Analysis -- Computability of Real Numbers -- Computability of Subsets of Metric Spaces -- Computability of Differential Equations -- Computable Complex Analysis -- Part II, Complexity, Dynamics, and Randomness -- Computable Geometric Complex Analysis and Complex Dynamics -- A Survey on Analog Models of Computation -- Computable Measure Theory and Algorithmic Randomness -- Algorithmic Fractal Dimensions in Geometric Measure Theory -- Part III Constructivity, Logic, and Descriptive Complexity -- Admissibly Represented Spaces and Qcb-Spaces -- Bishop-Style Constructive Reverse Mathematics -- Weihrauch Complexity in Computable Analysis -- Index.
Contained By:	Springer Nature eBook
標題:	Computable functions - Handbooks, manuals, etc. -
電子資源:	https://doi.org/10.1007/978-3-030-59234-9
ISBN:	9783030592349

Handbook of computability and complexity in analysis
Handbook of computability and complexity in analysis[electronic resource] /edited by Vasco Brattka, Peter Hertling. - Cham :Springer International Publishing :2021. - xxv, 427 p. :ill., digital ;24 cm. - Theory and applications of computability,2190-619X. - Theory and applications of computability..

Part I, Computability in Analysis -- Computability of Real Numbers -- Computability of Subsets of Metric Spaces -- Computability of Differential Equations -- Computable Complex Analysis -- Part II, Complexity, Dynamics, and Randomness -- Computable Geometric Complex Analysis and Complex Dynamics -- A Survey on Analog Models of Computation -- Computable Measure Theory and Algorithmic Randomness -- Algorithmic Fractal Dimensions in Geometric Measure Theory -- Part III Constructivity, Logic, and Descriptive Complexity -- Admissibly Represented Spaces and Qcb-Spaces -- Bishop-Style Constructive Reverse Mathematics -- Weihrauch Complexity in Computable Analysis -- Index.

Computable analysis is the modern theory of computability and complexity in analysis that arose out of Turing's seminal work in the 1930s. This was motivated by questions such as: which real numbers and real number functions are computable, and which mathematical tasks in analysis can be solved by algorithmic means? Nowadays, this theory has many different facets that embrace topics from computability theory, algorithmic randomness, computational complexity, dynamical systems, fractals, and analog computers, up to logic, descriptive set theory, constructivism, and reverse mathematics. In recent decades, computable analysis has invaded many branches of analysis, and researchers have studied computability and complexity questions arising from real and complex analysis, functional analysis, and the theory of differential equations, up to (geometric) measure theory and topology. This comprehensive handbook contains 11 chapters grouped into parts on computability in analysis; complexity, dynamics, and randomness; and constructivity, logic, and descriptive complexity. Researchers and graduate students in the areas of theoretical computer science and mathematical logic will find systematic introductions into many branches of computable analysis, as well as a wealth of information and references that will help them to navigate the modern research literature in this field. Vasco Brattka is a professor for Theoretical Computer Science and Mathematical Logic at the Universitat der Bundeswehr Munchen. He is editor-in-chief of Computability, the journal of the association, Computability in Europe. Peter Hertling is a professor in the Institute for Theoretical Computer Science, Mathematics and Operations Research at UniBwM. He is an associate editor of Journal of Complexity.

ISBN: 9783030592349

Standard No.: 10.1007/978-3-030-59234-9doiSubjects--Topical Terms:

3505016
Computable functions
--Handbooks, manuals, etc.

LC Class. No.: QA9.59 / .H35 2020

Dewey Class. No.: 511.352

Handbook of computability and complexity in analysis
LDR:03551nmm a2200349 a 4500 001 2244290
003 DE-He213
005 20210622202504.0
006 m d
007 cr nn 008maaau
008 211207s2021 sz s 0 eng d
020 $a 9783030592349 $q (electronic bk.)
020 $a 9783030592332 $q (paper)
024 7 $a 10.1007/978-3-030-59234-9 $2 doi
035 $a 978-3-030-59234-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA9.59 $b .H35 2020
072 7 $a UY $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a UY $2 thema
072 7 $a UYA $2 thema
082 0 4 $a 511.352 $2 23
090 $a QA9.59 $b .H236 2020
245 0 0 $a Handbook of computability and complexity in analysis $h [electronic resource] / $c edited by Vasco Brattka, Peter Hertling.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xxv, 427 p. : $b ill., digital ; $c 24 cm.
490 1 $a Theory and applications of computability, $x 2190-619X
505 0 $a Part I, Computability in Analysis -- Computability of Real Numbers -- Computability of Subsets of Metric Spaces -- Computability of Differential Equations -- Computable Complex Analysis -- Part II, Complexity, Dynamics, and Randomness -- Computable Geometric Complex Analysis and Complex Dynamics -- A Survey on Analog Models of Computation -- Computable Measure Theory and Algorithmic Randomness -- Algorithmic Fractal Dimensions in Geometric Measure Theory -- Part III Constructivity, Logic, and Descriptive Complexity -- Admissibly Represented Spaces and Qcb-Spaces -- Bishop-Style Constructive Reverse Mathematics -- Weihrauch Complexity in Computable Analysis -- Index.
520 $a Computable analysis is the modern theory of computability and complexity in analysis that arose out of Turing's seminal work in the 1930s. This was motivated by questions such as: which real numbers and real number functions are computable, and which mathematical tasks in analysis can be solved by algorithmic means? Nowadays, this theory has many different facets that embrace topics from computability theory, algorithmic randomness, computational complexity, dynamical systems, fractals, and analog computers, up to logic, descriptive set theory, constructivism, and reverse mathematics. In recent decades, computable analysis has invaded many branches of analysis, and researchers have studied computability and complexity questions arising from real and complex analysis, functional analysis, and the theory of differential equations, up to (geometric) measure theory and topology. This comprehensive handbook contains 11 chapters grouped into parts on computability in analysis; complexity, dynamics, and randomness; and constructivity, logic, and descriptive complexity. Researchers and graduate students in the areas of theoretical computer science and mathematical logic will find systematic introductions into many branches of computable analysis, as well as a wealth of information and references that will help them to navigate the modern research literature in this field. Vasco Brattka is a professor for Theoretical Computer Science and Mathematical Logic at the Universitat der Bundeswehr Munchen. He is editor-in-chief of Computability, the journal of the association, Computability in Europe. Peter Hertling is a professor in the Institute for Theoretical Computer Science, Mathematics and Operations Research at UniBwM. He is an associate editor of Journal of Complexity.
650 0 $a Computable functions $v Handbooks, manuals, etc. $3 3505016
650 1 4 $a Theory of Computation. $3 892514
650 2 4 $a Mathematics of Computing. $3 891213
650 2 4 $a Mathematical Logic and Foundations. $3 892656
700 1 $a Brattka, Vasco. $3 1072025
700 1 $a Hertling, Peter. $3 1072026
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Theory and applications of computability. $3 2199731
856 4 0 $u https://doi.org/10.1007/978-3-030-59234-9
950 $a Computer Science (SpringerNature-11645)