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.

Preface xi1 Introduction 11.1 System Science 11.1.1 Definition of System Science 21.2 Principle of Causality 31.2.1 Definition 31.2.2 Common Examples 41.2.3 Relationship to System Science 61.3 Overview of System Science 71.3.1 Historical Background 71.3.2 Major System Science Achievements in the Twentieth Century 91.3.3 Measurable Systems and Quantitative Modeling 91.3.4 Application of Computers to System Science 131.3.5 Utilization of Computer Software in System Science 141.3.6 General Applications of System Science 161.4 Outline and Utilization of Text 171.4.1 Outline of Text 171.4.2 Study Schedules by Discipline for this Text 181.5 Summary 18Bibliography 20Problems 212 Fundamental System Concepts 252.1 Definitions of System Concepts and Terms 252.1.1 Concept and Definition of a System 252.1.2 System Causes 262.1.3 System Effects 262.1.4 Measurability of System Causes and Effects 262.1.5 Isolation of a System from Its External Environment 272.1.6 Intrinsic and Extrinsic System Feedback 282.2 Discussion of System Concepts 282.2.1 Concept of a System 282.2.2 Isolation of a System from the Environment 292.2.3 Identifying and Distinguishing Between Causes and Effects 312.3 Classification of Systems by Type 322.3.1 Irrational and Immeasurable Systems 332.3.2 Continuous and Discrete Systems 352.3.3 Deterministic and Stochastic Systems 362.3.4 Feedback Systems 372.3.5 Controllable Systems 402.4 System Analysis and Evaluation Using a Computer 412.4.1 Computer Applications to System Analysis 412.4.2 Symbolic Computer Applications to System Analysis 412.5 Summary 44Bibliography 45Problems 463 Basic System Equations 493.1 Functional Dependence of System Causes and Effects 493.1.1 Proportionality Relationship Between Cause and Effect 503.1.2 The System Kernel 513.2 Classification of System Equations 543.2.1 Single-Input, Single-Output Systems 553.2.2 Single-Input, Multiple-Output Systems 573.2.3 Multiple-Input, Single-Output Systems 613.2.4 Multiple-Input, Multiple-Output Systems 633.3 Summary 66Bibliography 67Problems 674 Single-Input Systems 754.1 Definition and Significance of a Single-Input System 754.2 Single-Input, Single-Output Systems 764.2.1 Discrete Systems 774.2.2 Continuous Systems 794.2.3 Constant System Kernels 814.2.4 Linear System Kernels 814.2.5 Exact System Kernels 844.2.6 Separable System Kernels 874.2.7 Homogeneous System Kernels 884.2.8 Bernoulli-Type System Kernels 904.2.9 Ricatti-Type System Kernels 914.2.10 Other Special System Kernel Types 934.3 Single-Input, Multiple-Output Systems 974.3.1 Discrete System Kernels 984.3.2 Continuous System Kernels 1004.3.3 Constant System Kernels 1034.3.4 Linear System Kernels with Constant Coefficients 1044.3.5 Linear System Kernels with Variable Coefficients 1074.3.6 Exact System Kernels 1114.3.7 Separable System Kernels 1124.3.8 Homogeneous System Kernels 1144.3.9 Autonomous System Kernels 1164.3.10 System Kernels Associated with Classical Second-Order Ordinary Differential Equations (ODEs) 1184.3.11 Equivalence of Single-Input System Equations with Ordinary Differential and Difference Equations of Any Order 1244.4 Treatment of Single-Input Systems Using MATLAB Symbolic Toolbox 1284.5 Summary 131Bibliography 131Problems 1325 Multiple-Input Systems 1415.1 Definition and Mathematical Significance 1415.2 Multiple-Input, Single-Output Systems 1425.2.1 Discrete Systems 1435.2.2 Continuous Systems 1465.2.3 Constant System Kernels 1475.2.4 Exact System Kernels 1485.2.5 Linear System Kernels 1515.2.6 Separable System Kernels 1535.2.7 Homogeneous System Kernels 1545.2.8 Inversion of the System Kernel 1555.2.9 Equivalence of Multiple-Input, Single-Output System Equations and First-Order Partial Differential Equations 1575.3 Multiple-Input, Multiple-Output Systems 1615.3.1 Discrete Systems 1625.3.2 Continuous System Kernels 1645.3.3 Constant System Kernels 1665.3.4 Exact System Kernels 1665.3.5 Linear System Kernels 1675.3.6 Separable System Kernels 1715.3.7 Equivalence of Multiple-Input, Multiple-Output Systems and Partial Differential Equations 1725.3.8 Reduction of Multiple-Input, Multiple-Output Systems Equations 1735.3.9 Integral Equation Form of the System Equation 1755.3.10 Elimination of Individual Output Solutions to Reduce the System Equation 1765.4 Summary 177Bibliography 178Problems 1786 System Modeling 1836.1 Graphical Representation of Systems 1836.1.1 Block Diagramming 1846.1.2 Signal-Flow Graphs 1896.1.3 Organization Diagrams 1946.2 Modeling System Inputs, Outputs, and Kernels 1996.2.1 Single-Input, Single-Output System 2046.2.2 Physical Systems 2066.2.3 Nonphysical Systems 2096.2.4 Experimental Modeling 2126.2.5 Stochastic Modeling 2236.2.6 Heuristic Modeling 2266.3 Paradigm for System Modeling, Analysis, and Evaluation 2286.4 Summary 229Bibliography 229Problems 2307 Analysis Methods for Systems with Linear Kernels 2457.1 Background and Justification 2457.2 Linearization Methods 2477.2.1 Taylor Series Expansion 2487.2.2 Perturbation Methods 2517.2.3 Variable Coefficient Elimination 2527.3 Single-Input Linear Systems 2547.3.1 Single-Input, Single-Output Systems 2547.3.2 Single-Input, Multiple-Output Linear Systems 2587.4 Multiple-Input Linear Systems 2657.4.1 Multiple-Input, Single-Output 2667.4.2 Multiple-Input, Multiple-Output Continuous System Equations 2707.5 Summary 272Bibliography 273Problems 2748 Generalized System Analysis Methods 2798.1 Simplification and Reduction of System Kernels 2798.1.1 Conversion of Variable System Kernels to Constant Kernels 2808.1.2 Reduction of System Kernels 2828.2 System Normalization and Parameter Reduction 2888.2.1 System Variable Normalization 2888.2.2 Parameter Reduction and Minimization 2928.2.3 Sensitivity Analysis of System Parameters 2978.3 Systems with Feedback 3008.3.1 System Kernel Feedback Gain 3018.3.2 Effect of Feedback on Linear Kernels 3048.3.3 Single-Input, Single-Output Systems with Feedback 3068.3.4 Inversion of System Kernels with Feedback 3088.4 Computer-Aided Analysis of Systems 3108.5 Summary 313Bibliography 313Problems 3149 System Science Applications 3219.1 Classification of System Science by Topics 3219.2 System Science Applications to Space, Time, Matter, and Energy in Physical Science 3289.2.1 First Law of Thermodynamics 3289.2.2 Particle Diffusion Model 3319.2.3 Relativistic Mechanics Model 3339.2.4 System Problems for Matter, Energy, Space, and Time 3399.3 Earth Science Applications of System Science 3529.3.1 Atmospheric Model 3539.3.2 Geothermal Model 3559.3.3 Terrestrial Water Balance Model 3579.3.4 Topical System Applications in the Earth Sciences 3609.4 Life Systems Applications of System Science 3669.4.1 Continuous and Discrete Growth Models 3669.4.2 The Mammalian Lung Model 3679.4.3 Topical System Problems in Life Science 3699.5 Applications of System Science to Human Life 3819.5.1 Hemodynamic Circulatory System 3819.5.2 Model for Medical Diagnosis Using Radioactive Nuclides 3869.5.3 Quantitative Model for Stress 3889.5.4 Topical System Problems Associated with Human Life 3909.6 Applications of System Science to Human Society 4019.6.1 World Cultural and Economic Regions 4019.6.2 Solow Model for Economic Growth 4039.6.3 Model for Cost of Crime to Society 4069.6.4 Energy Consumption and GNP 4139.6.5 Topical System Problems in Human Society 4149.7 Applications of System Science to the Arts 4239.7.1 Quantitative Assessment of Language 4249.7.2 Art Awareness Model 4279.7.3 Topical System Problems in the Arts 4279.8 Applications of System Science to Technology 4309.8.1 Nuclear Reactor Stability with Xenon-135 Dependence 4319.8.2 Fluid Flow with Friction 4419.8.3 Models for Forecasting Electrical Power Demand 4439.8.4 Topical System Problems in Technology 4459.9 Applications of System Science to Religion 4509.9.1 Quality of Life and Belief in God Model 4509.9.2 Models for the Great Religions 4559.9.3 Topical System Problems in Religion 4569.10 Applications of System Science to History 4629.10.1 Expansion Model for Aggressive Societies 4629.10.2 Historical Growth in Weapons Trade 4659.10.3 Additional Modeling Problems 466General System Science Bibliography 46810 System Modeling Paradigms 47510.1 Background 47510.2 Modeling Paradigm 47610.3 Essential System Modeling Paradigm Steps 47710.3.1 Step-1 Explore and Document 47710.3.2 Step-2 Define and Contain 48110.3.3 Step-3 Select and Develop 48110.3.4 Step-4 Construct and Quantify 48210.3.5 Step-5 Analyze and Evaluate 48210.3.6 Step-6 Assess and Re-Evaluate 48210.3.7 Step-7 Finalize and Confirm 48310.3.8 Step-8 Resolve and Accept 48310.3.9 Step-9 Publish and Disseminate 48310.4 Example of Analysis Process after System Identification using MATLAB 48310.5 Final Words 486Index 489