EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link: https://ebookbell.com/faq

We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.

For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Datadriven Identification Of Networks Of Dynamic Systems New Michel Verhaegen

Name: Datadriven Identification Of Networks Of Dynamic Systems New Michel Verhaegen
SKU: BELL-44437350
Price: 31.00 USD
Availability: InStock
Rating: 4.4 (82 reviews)

SKU: BELL-44437350

$ 31.00 ~~$ 45.00~~ (-31%)

4.4

82 reviews

Datadriven Identification Of Networks Of Dynamic Systems New Michel Verhaegen instant download after payment.

Publisher: Cambridge University Press

File Extension: PDF

File size: 7.71 MB

Pages: 320

Author: Michel Verhaegen, Chengpu Yu, Baptiste Sinquin

ISBN: 9781316515709, 1316515702

Language: English

Year: 2022

Edition: New

Product desciption

Datadriven Identification Of Networks Of Dynamic Systems New Michel Verhaegen by Michel Verhaegen, Chengpu Yu, Baptiste Sinquin 9781316515709, 1316515702 instant download after payment.

This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.