Discrete-time Dynamic Models (Hardcover)
Ronald K. Pearson
Sold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
New - Hardcover
Condition: New
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
Condition: New
Quantity: 1 available
Add to basketHardcover. Fueled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. While there is an enormous literature on modeling, the difficult first step of selecting an appropriate model structure has received almost no attention. This book fills the gap, providing practical insight into model selection for chemical processes and emphasizing structures suitable for control system design. Fuelled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. This book provides a practical insight into model selection for chemical processes and emphasises structures suitable for control system design. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9780195121988
"The author provides an excellent view of his experiences from industry. An excellent book intended to educate the specialized reader in physical fields, particularly those who are working in the time domain. Pearson has done an excellent job of covering nonstandard topics in time series, which more than justifies the book's existence. The book contains many realistic examples, and a rich collection of scenarios with liberal references to the applied literature. It is extremely readable, and the author is to be commended for his lucid writing style. Overall, the authors presentation is insightful and consistent. It is well written and nicely organized. The books appeal is that it illustrates a wide range of results for many kinds of models that appear in stochastic processes and time series literature. Finally, this book is an important addition in the areas of nonlinear time series, and it has much to offer that is hard to find elsewhere." -- Stergios B. Fotopoulos, Technometrics
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