Name: mathematical modeling for industrial processes (en Inglés)
SKU: 25910446
Price: 841.79 MXN
Availability: InStock
Author: Hyvärinen, L. P.
ISBN: 9783540049432

portada mathematical modeling for industrial processes (en Inglés)

mathematical modeling for industrial processes (en Inglés)

Formato

Libro Físico

Autor

L. P. Hyvärinen

Editorial

Springer

Año

1970

Idioma

Inglés

N° páginas

125

Encuadernación

Tapa Blanda

Dimensiones

25.4x17.8x0.7 cm

Peso

0.25 kg.

ISBN

3540049436

ISBN13

9783540049432

Categorías

Teoría y filosofía económicas

mathematical modeling for industrial processes (en Inglés)

L. P. Hyvärinen (Autor) · Springer · Tapa Blanda

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Reseña del libro "mathematical modeling for industrial processes (en Inglés)"

These notes are based on the material presented in a series of lec- tures in the IBM Systems Research Institute (ESRI) in Geneva durJng 1967-1969 to systems engineers working in the design and programming of computer systems for control and monitoring of i nustrial proc- esses. The purpose of the lectures and this book is to give a survey of dif- ferent approaches in developing models to describe the behavior of the process in terms of controllable variables. It does not cover the theory of control, stability of control systems, nor techniques in data acquisition or problems in instrumentation and sampling. But certain aspects in the organization of data collection and design of experiments are obtained as side products, notably the concept of orthogonality. The reader is assumed to have a working knowledge of elementary prob- ability theory and mathematical statistics. Therefore, the text con- tains no introduction to these concepts. The author is aware of some inaccuracies in not making proper dis- tinction between population parameters and their sample estimates in the text, but this should alw s be evident from the context. The same applies to the occasional replacement of number of degrees of freedom by the number of samples in the data. In practice, computer collected sets of data consist of a high number of samples and the difference between the two is inSignificant.