HOME > Detail View

Detail View

Advanced neural network-based computational schemes for robust fault diagnosis [electronic resource]

Advanced neural network-based computational schemes for robust fault diagnosis [electronic resource]

Material type
E-Book(소장)
Personal Author
Mrugalski, Marcin.
Title Statement
Advanced neural network-based computational schemes for robust fault diagnosis [electronic resource] / Marcin Mrugalski.
Publication, Distribution, etc
Cham :   Springer International Publishing :   Imprint: Springer,   2014.  
Physical Medium
1 online resource (xxi, 182 p.).
Series Statement
Studies in computational intelligence,1860-949X ; 510
ISBN
9783319015477
요약
The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications.
General Note
Title from e-Book title page.  
Content Notes
Introduction -- Designing of dynamic neural networks -- Estimation methods in training of ANNs for robust fault diagnosis -- MLP in robust fault detection of static non-linear systems -- GMDH networks in robust fault detection of dynamic non-linear systems -- State-space GMDH networks for actuator robust FDI.
Bibliography, Etc. Note
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Neural networks (Computer science). Fault location (Engineering). Robust control.
Short cut
URL
000 00000nam u2200205 a 4500
001 000046043512
005 20200915173259
006 m d
007 cr
008 200814s2014 sz ob 001 0 eng d
020 ▼a 9783319015477
040 ▼a 211009 ▼c 211009 ▼d 211009
050 4 ▼a Q342
082 0 4 ▼a 006.3/2 ▼2 23
084 ▼a 006.32 ▼2 DDCK
090 ▼a 006.32
100 1 ▼a Mrugalski, Marcin.
245 1 0 ▼a Advanced neural network-based computational schemes for robust fault diagnosis ▼h [electronic resource] / ▼c Marcin Mrugalski.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2014.
300 ▼a 1 online resource (xxi, 182 p.).
490 1 ▼a Studies in computational intelligence, ▼x 1860-949X ; ▼v 510
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Introduction -- Designing of dynamic neural networks -- Estimation methods in training of ANNs for robust fault diagnosis -- MLP in robust fault detection of static non-linear systems -- GMDH networks in robust fault detection of dynamic non-linear systems -- State-space GMDH networks for actuator robust FDI.
520 ▼a The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Neural networks (Computer science).
650 0 ▼a Fault location (Engineering).
650 0 ▼a Robust control.
830 0 ▼a Studies in computational intelligence ; ▼v v. 510.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-01547-7
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.32 Accession No. E14032229 Availability Loan can not(reference room) Due Date Make a Reservation Service M

New Arrivals Books in Related Fields