國立虎尾科技大學 |

Artificial Adaptive Systems Using Auto Contractive Maps = Theory, Applications and Extensions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Artificial Adaptive Systems Using Auto Contractive Maps/ by Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman, Masoud Asadi-Zeydabadi.
Reminder of title:	Theory, Applications and Extensions /
Author:	Buscema, Paolo Massimo.
other author:	Massini, Giulia.
Description:	VII, 179 p. 97 illus., 74 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-75049-1
ISBN:	9783319750491

Artificial Adaptive Systems Using Auto Contractive Maps = Theory, Applications and Extensions /
Buscema, Paolo Massimo.

Artificial Adaptive Systems Using Auto Contractive MapsTheory, Applications and Extensions /[electronic resource] :by Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman, Masoud Asadi-Zeydabadi. - 1st ed. 2018. - VII, 179 p. 97 illus., 74 illus. in color.online resource. - Studies in Systems, Decision and Control,1312198-4182 ;. - Studies in Systems, Decision and Control,27.

An Introduction -- Artificial Neural Networks -- Auto-Contractive Maps -- Visualization of Auto-CM Output -- Dataset Transformations and Auto-CM -- Comparison of Auto-CM to Various Other Data Understanding Approaches.

This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.

ISBN: 9783319750491

Standard No.: 10.1007/978-3-319-75049-1doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Artificial Adaptive Systems Using Auto Contractive Maps = Theory, Applications and Extensions /
LDR:02840nam a22004095i 4500 001 998009
003 DE-He213
005 20200702221815.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319750491 $9 978-3-319-75049-1
024 7 $a 10.1007/978-3-319-75049-1 $2 doi
035 $a 978-3-319-75049-1
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Buscema, Paolo Massimo. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1289417
245 1 0 $a Artificial Adaptive Systems Using Auto Contractive Maps $h [electronic resource] : $b Theory, Applications and Extensions / $c by Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman, Masoud Asadi-Zeydabadi.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a VII, 179 p. 97 illus., 74 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Systems, Decision and Control, $x 2198-4182 ; $v 131
505 0 $a An Introduction -- Artificial Neural Networks -- Auto-Contractive Maps -- Visualization of Auto-CM Output -- Dataset Transformations and Auto-CM -- Comparison of Auto-CM to Various Other Data Understanding Approaches.
520 $a This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.
650 0 $a Computational intelligence. $3 568984
650 0 $a Data mining. $3 528622
650 0 $a Artificial intelligence. $3 559380
650 0 $a Mathematical logic. $2 bicssc $3 810627
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Mathematical Logic and Foundations. $3 669393
700 1 $a Massini, Giulia. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1289418
700 1 $a Breda, Marco. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1289419
700 1 $a Lodwick, Weldon A. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 867015
700 1 $a Newman, Francis. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1289420
700 1 $a Asadi-Zeydabadi, Masoud. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1289421
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319750484
776 0 8 $i Printed edition: $z 9783319750507
776 0 8 $i Printed edition: $z 9783030091354
830 0 $a Studies in Systems, Decision and Control, $x 2198-4182 ; $v 27 $3 1254124
856 4 0 $u https://doi.org/10.1007/978-3-319-75049-1
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)