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Numerical Data Fitting in Dynamical Systems - A Practical Introduction with Applications and Software (Paperback, Softcover reprint of the original 1st ed. 2002)
Loot Price: R8,596
Discovery Miles 85 960
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Numerical Data Fitting in Dynamical Systems - A Practical Introduction with Applications and Software (Paperback, Softcover reprint of the original 1st ed. 2002)
Series: Applied Optimization, 77
Expected to ship within 10 - 15 working days
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Real life phenomena in engineering, natural, or medical sciences
are often described by a mathematical model with the goal to
analyze numerically the behaviour of the system. Advantages of
mathematical models are their cheap availability, the possibility
of studying extreme situations that cannot be handled by
experiments, or of simulating real systems during the design phase
before constructing a first prototype. Moreover, they serve to
verify decisions, to avoid expensive and time consuming
experimental tests, to analyze, understand, and explain the
behaviour of systems, or to optimize design and production. As soon
as a mathematical model contains differential dependencies from an
additional parameter, typically the time, we call it a dynamical
model. There are two key questions always arising in a practical
environment: 1 Is the mathematical model correct? 2 How can I
quantify model parameters that cannot be measured directly? In
principle, both questions are easily answered as soon as some
experimental data are available. The idea is to compare measured
data with predicted model function values and to minimize the
differences over the whole parameter space. We have to reject a
model if we are unable to find a reasonably accurate fit. To
summarize, parameter estimation or data fitting, respectively, is
extremely important in all practical situations, where a
mathematical model and corresponding experimental data are
available to describe the behaviour of a dynamical system.
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