This text teaches, by example, how to create models, simulate performance simulations and analyse results. It takes a quantitative approach and covers a range of event driven and time driven models. In addition it is software independent - to make implementations as generic as possible, which allows for experimentation with different implementations.
* Includes 100 worked examples
* Incorporates a number of disciplines in modeling process
* Algorithms and programs available on associated web site
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
FRANK L. SEVERANCE is a professor of Electrical and Computer Engineering at Western Michigan University, where he teaches and conducts research in non-linear control systems, digital signal processing and system modeling. In addition to being an unrepentant teacher, he plays viola in the University Symphony Orchestra and directs muscials for the Charlotte Community Theater.
Q. What is system modeling?
A. System modeling is the process of describing both natural and engineered systems in precise mathematical terms.
Q. What is simulation?
A. Simulation is the exploitation of a model in order to predict logical consequences of hypothetical situations.
Q. What is this book, System Modeling and Simulation: An Introduction?
A. This book is a uniquely broad and quantitative introduction to creating models, performing simulations and analyzing results in a systematic and rigorous way.
It covers the technical breadth of system modeling by including:
* continuous-time, sampled-time and discrete-time models
* temporal, spatial and hybrid models
* continuous-state and discrete-state models
* deterministic and stochastic models
* both system and signal modeling
It explores the generality of system modeling by considering a myriad of physical, biological and engineered examples. Each example is modeled, simulated and analyzed in detail.
It emphasizes first principles through self-contained chapters on introductory numerical analysis and the generation of random variates and random processes, and an appendix on basic statistical analysis techniques.
System Modeling and Simulation: An Introduction
* teaches, by example, how to
-- create models
-- simulate performance simulations
-- analyze results
* covers a range of event-driven and time-driven models
* uses detailed examples to reinforce the explanations of techniques
* is software and language independent
* includes over 200 exercises, analysis and design problems suitable for project work.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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