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

切換: 標籤 | MARC模式 | ISBD

Pattern recognition and computationa...

Gopi, E. S.

FindBook

Google Book

Amazon

博客來

Pattern recognition and computational intelligence techniques using Matlab

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Pattern recognition and computational intelligence techniques using Matlab/ by E. S. Gopi.
作者:	Gopi, E. S.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xiii, 256 p. :ill., digital ;24 cm.
內容註:	Chapter1: Dimensionality Reduction Techniques -- Chapter2: Linear classifier techniques -- Chapter3: Regression techniques. Chapter4: Probabilistic supervised classifier and unsupervised clustering -- Chapter5: Computational intelligence -- Chapter6: Statistical test in pattern recognition.
Contained By:	Springer eBooks
標題:	Pattern recognition systems. -
電子資源:	https://doi.org/10.1007/978-3-030-22273-4
ISBN:	9783030222734

Pattern recognition and computational intelligence techniques using Matlab
Gopi, E. S.

Pattern recognition and computational intelligence techniques using Matlab[electronic resource] /by E. S. Gopi. - Cham :Springer International Publishing :2020. - xiii, 256 p. :ill., digital ;24 cm. - Transactions on computational science and computational intelligence,2569-7072. - Transactions on computational science and computational intelligence..

Chapter1: Dimensionality Reduction Techniques -- Chapter2: Linear classifier techniques -- Chapter3: Regression techniques. Chapter4: Probabilistic supervised classifier and unsupervised clustering -- Chapter5: Computational intelligence -- Chapter6: Statistical test in pattern recognition.

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques. Presents pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly; Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.

ISBN: 9783030222734

Standard No.: 10.1007/978-3-030-22273-4doiSubjects--Topical Terms:

527885
Pattern recognition systems.

LC Class. No.: TK7882.P3

Dewey Class. No.: 006.4

Pattern recognition and computational intelligence techniques using Matlab
LDR:02379nmm a2200337 a 4500 001 2214229
003 DE-He213
005 20200303085835.0
006 m d
007 cr nn 008maaau
008 201118s2020 sz s 0 eng d
020 $a 9783030222734 $q (electronic bk.)
020 $a 9783030222727 $q (paper)
024 7 $a 10.1007/978-3-030-22273-4 $2 doi
035 $a 978-3-030-22273-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.P3
072 7 $a TJK $2 bicssc
072 7 $a TEC041000 $2 bisacsh
072 7 $a TJK $2 thema
082 0 4 $a 006.4 $2 23
090 $a TK7882.P3 $b G659 2020
100 1 $a Gopi, E. S. $3 1067513
245 1 0 $a Pattern recognition and computational intelligence techniques using Matlab $h [electronic resource] / $c by E. S. Gopi.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xiii, 256 p. : $b ill., digital ; $c 24 cm.
490 1 $a Transactions on computational science and computational intelligence, $x 2569-7072
505 0 $a Chapter1: Dimensionality Reduction Techniques -- Chapter2: Linear classifier techniques -- Chapter3: Regression techniques. Chapter4: Probabilistic supervised classifier and unsupervised clustering -- Chapter5: Computational intelligence -- Chapter6: Statistical test in pattern recognition.
520 $a This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques. Presents pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly; Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.
650 0 $a Pattern recognition systems. $3 527885
650 0 $a Computer vision. $3 540671
650 0 $a Computational intelligence. $3 595739
650 1 4 $a Communications Engineering, Networks. $3 891094
650 2 4 $a Mathematical and Computational Engineering. $3 3226306
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Pattern Recognition. $3 891045
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Transactions on computational science and computational intelligence. $3 3227107
856 4 0 $u https://doi.org/10.1007/978-3-030-22273-4
950 $a Engineering (Springer-11647)