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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Zhao, Chunhui
Yu, Wanke

Paperback

Technology & Engineering

ISBN10: 044333675X
ISBN13: 9780443336751
Publisher: Academic Press
Published: Jul 25 2025
Pages: 258
Weight: 0.80
Height: 0.60 Width: 6.00 Depth: 8.90
Language: English
Spatio-Temporal Learning Using Irregular Data for Complex Dynamic Processes introduces learning, modeling, and monitoring methods for highly complex dynamic processes with irregular data. Two classes of robust modeling methods are highlighted, including low-rank characteristic of matrices and heavy-tailed characteristic of distributions. In this class, the missing data, ambient noise, and outlier problems are solved using low-rank matrix complement for monitoring model development. Secondly, the Laplace distribution is explored, which is adopted to measure the process uncertainty to develop robust monitoring models.

The book not only discusses the complex models but also their real-world applications in industry.

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