語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Advances in self-organizing maps and...
~
(1998 :)
Advances in self-organizing maps and learning vector quantizationproceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Advances in self-organizing maps and learning vector quantizationedited by Erzsebet Merenyi, Michael J. Mendenhall, Patrick O'Driscoll.
其他題名:
proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
其他作者:
Merenyi, Erzsebet.
團體作者:
出版者:
Cham :Springer International Publishing :2016.
面頁冊數:
xiii, 370 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Neural networks (Computer science)
電子資源:
http://dx.doi.org/10.1007/978-3-319-28518-4
ISBN:
9783319285184$q(electronic bk.)
Advances in self-organizing maps and learning vector quantizationproceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
Advances in self-organizing maps and learning vector quantization
proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /[electronic resource] :edited by Erzsebet Merenyi, Michael J. Mendenhall, Patrick O'Driscoll. - Cham :Springer International Publishing :2016. - xiii, 370 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.4282194-5357 ;. - Advances in intelligent systems and computing ;176..
Self-Organizing Map Learning, Visualization, and Quality Assessment -- Clustering and Time Series Analysis with Self-Organizing Maps and Neural Gas -- Applications in Control, Planning, and Dimensionality Reduction, and Hardware for Self-Organizing Maps -- Self-Organizing Maps in Neuroscience and Medical Applications -- Learning Vector Quantization Theories and Applications I -- Learning Vector Quantization Theories and Applications II.
This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland) WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA) The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.
ISBN: 9783319285184$q(electronic bk.)
Standard No.: 10.1007/978-3-319-28518-4doiSubjects--Topical Terms:
181982
Neural networks (Computer science)
LC Class. No.: QA76.87
Dewey Class. No.: 006.32
Advances in self-organizing maps and learning vector quantizationproceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
LDR
:03131nmm a2200325 a 4500
001
482814
003
DE-He213
005
20160819120834.0
006
m d
007
cr nn 008maaau
008
161007s2016 gw s 0 eng d
020
$a
9783319285184$q(electronic bk.)
020
$a
9783319285177$q(paper)
024
7
$a
10.1007/978-3-319-28518-4
$2
doi
035
$a
978-3-319-28518-4
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.87
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
006.32
$2
23
090
$a
QA76.87
$b
.A244 2016
111
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
245
1 0
$a
Advances in self-organizing maps and learning vector quantization
$h
[electronic resource] :
$b
proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
$c
edited by Erzsebet Merenyi, Michael J. Mendenhall, Patrick O'Driscoll.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2016.
300
$a
xiii, 370 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Advances in intelligent systems and computing,
$x
2194-5357 ;
$v
v.428
505
0
$a
Self-Organizing Map Learning, Visualization, and Quality Assessment -- Clustering and Time Series Analysis with Self-Organizing Maps and Neural Gas -- Applications in Control, Planning, and Dimensionality Reduction, and Hardware for Self-Organizing Maps -- Self-Organizing Maps in Neuroscience and Medical Applications -- Learning Vector Quantization Theories and Applications I -- Learning Vector Quantization Theories and Applications II.
520
$a
This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland) WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA) The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.
650
0
$a
Neural networks (Computer science)
$3
181982
650
0
$a
Self-organizing maps
$v
Congresses.
$3
450620
650
0
$a
Self-organizing systems
$v
Congresses.
$3
384588
650
1 4
$a
Engineering.
$3
210888
650
2 4
$a
Computational Intelligence.
$3
338479
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
252959
700
1
$a
Merenyi, Erzsebet.
$3
739725
700
1
$a
Mendenhall, Michael J.
$3
739726
700
1
$a
O'Driscoll, Patrick.
$3
739727
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
830
0
$a
Advances in intelligent systems and computing ;
$v
176.
$3
567349
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-28518-4
950
$a
Engineering (Springer-11647)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000122651
電子館藏
1圖書
電子書
EB QA76.87 A244 2016
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-3-319-28518-4
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入