Fr. 146.00

Introduction to System Science With Matlab

English · Hardback

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Description

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Informationen zum Autor Gary Marlin Sandquist is Professor Emeritus in Mechanical Engineering at the University of Utah. He owns and operates Applied Science Professionals, LLC, and is a Fellow of the American Society of Mechanical Engineering and the American Nuclear Society. His research focuses on nuclear science and engineering, risk assessment, nuclear and reactor physics, health physics, and more. Zakary Robert Wilde is a doctoral candidate in the Mechanical Engineering Department at Arizona State University and an engineer at Los Alamos National Laboratory. His researches focus on testing, simulation, and visualization of high-speed dynamic events as well as developing simplified models for complex physical and engineering systems. Klappentext Introduction to SYSTEM SCIENCE with MATLABExplores the mathematical basis for developing and evaluating continuous and discrete systemsIn this revised Second Edition of Introduction to System Science with MATLAB(r), the authors Gary Sandquist and Zakary Wilde provide a comprehensive exploration of essential concepts, mathematical framework, analytical resources, and productive skills required to address any rational system confidently and adequately for quantitative evaluation.This Second Edition is supplemented with new updates to the mathematical and technical materials from the first edition. A new chapter to assist readers to generalize and execute algorithms for systems development and analysis, as well as an expansion of the chapter covering specific system science applications, is included.The book provides the mathematical basis for developing and evaluating single and multiple input/output systems that are continuous or discrete. It offers the mathematical basis for the recognition, definition, quantitative modeling, analysis, and evaluation in system science.The book also provides:* A comprehensive introduction to system science and the principles of causality and cause and effect operations, including their historical and scientific background* A complete exploration of fundamental systems concepts and basic system equations, including definitions and classifications* Practical applications and discussions of single-input systems, multiple-input systems, and system modeling and evaluation* An in-depth examination of generalized system analysis methods and specific system science applicationsPerfect for upper-level undergraduate and graduate students in engineering, mathematics, and physical sciences, Introduction to System Science with MATLAB(r) will also earn a prominent place in libraries of researchers in the life and social sciences. Zusammenfassung Introduction to SYSTEM SCIENCE with MATLABExplores the mathematical basis for developing and evaluating continuous and discrete systemsIn this revised Second Edition of Introduction to System Science with MATLAB(r), the authors Gary Sandquist and Zakary Wilde provide a comprehensive exploration of essential concepts, mathematical framework, analytical resources, and productive skills required to address any rational system confidently and adequately for quantitative evaluation.This Second Edition is supplemented with new updates to the mathematical and technical materials from the first edition. A new chapter to assist readers to generalize and execute algorithms for systems development and analysis, as well as an expansion of the chapter covering specific system science applications, is included.The book provides the mathematical basis for developing and evaluating single and multiple input/output systems that are continuous or discrete. It offers the mathematical basis for the recognition, definition, quantitative modeling, analysis, and evaluation in system science.The book also provides:* A comprehensive introduction to system science and the principles of causality and cause and effect operations, including their historical and scientific ...

List of contents

Preface xi
 
1 Introduction 1
 
1.1 System Science 1
 
1.1.1 Definition of System Science 2
 
1.2 Principle of Causality 3
 
1.2.1 Definition 3
 
1.2.2 Common Examples 4
 
1.2.3 Relationship to System Science 6
 
1.3 Overview of System Science 7
 
1.3.1 Historical Background 7
 
1.3.2 Major System Science Achievements in the Twentieth Century 9
 
1.3.3 Measurable Systems and Quantitative Modeling 9
 
1.3.4 Application of Computers to System Science 13
 
1.3.5 Utilization of Computer Software in System Science 14
 
1.3.6 General Applications of System Science 16
 
1.4 Outline and Utilization of Text 17
 
1.4.1 Outline of Text 17
 
1.4.2 Study Schedules by Discipline for this Text 18
 
1.5 Summary 18
 
Bibliography 20
 
Problems 21
 
2 Fundamental System Concepts 25
 
2.1 Definitions of System Concepts and Terms 25
 
2.1.1 Concept and Definition of a System 25
 
2.1.2 System Causes 26
 
2.1.3 System Effects 26
 
2.1.4 Measurability of System Causes and Effects 26
 
2.1.5 Isolation of a System from Its External Environment 27
 
2.1.6 Intrinsic and Extrinsic System Feedback 28
 
2.2 Discussion of System Concepts 28
 
2.2.1 Concept of a System 28
 
2.2.2 Isolation of a System from the Environment 29
 
2.2.3 Identifying and Distinguishing Between Causes and Effects 31
 
2.3 Classification of Systems by Type 32
 
2.3.1 Irrational and Immeasurable Systems 33
 
2.3.2 Continuous and Discrete Systems 35
 
2.3.3 Deterministic and Stochastic Systems 36
 
2.3.4 Feedback Systems 37
 
2.3.5 Controllable Systems 40
 
2.4 System Analysis and Evaluation Using a Computer 41
 
2.4.1 Computer Applications to System Analysis 41
 
2.4.2 Symbolic Computer Applications to System Analysis 41
 
2.5 Summary 44
 
Bibliography 45
 
Problems 46
 
3 Basic System Equations 49
 
3.1 Functional Dependence of System Causes and Effects 49
 
3.1.1 Proportionality Relationship Between Cause and Effect 50
 
3.1.2 The System Kernel 51
 
3.2 Classification of System Equations 54
 
3.2.1 Single-Input, Single-Output Systems 55
 
3.2.2 Single-Input, Multiple-Output Systems 57
 
3.2.3 Multiple-Input, Single-Output Systems 61
 
3.2.4 Multiple-Input, Multiple-Output Systems 63
 
3.3 Summary 66
 
Bibliography 67
 
Problems 67
 
4 Single-Input Systems 75
 
4.1 Definition and Significance of a Single-Input System 75
 
4.2 Single-Input, Single-Output Systems 76
 
4.2.1 Discrete Systems 77
 
4.2.2 Continuous Systems 79
 
4.2.3 Constant System Kernels 81
 
4.2.4 Linear System Kernels 81
 
4.2.5 Exact System Kernels 84
 
4.2.6 Separable System Kernels 87
 
4.2.7 Homogeneous System Kernels 88
 
4.2.8 Bernoulli-Type System Kernels 90
 
4.2.9 Ricatti-Type System Kernels 91
 
4.2.10 Other Special System Kernel Types 93
 
4.3 Single-Input, Multiple-Output Systems 97
 
4.3.1 Discrete System Kernels 98
 
4.3.2 Continuous System Kernels 100
 
4.3.3 Constant System Kernels 103
 
4.3.4 Linear System Kernels with Constant Coefficients 104
 
4.3.5 Linear System Kernels with Variable Coefficients 107
 
4.3.6 Exact System Kernels 111
 
4.3.7 Separable System Kernels 112
 
4.3.8 Homogeneous System Kernels 114
 
4.3.9 Autonomous System Kernels 1

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