Produktbild: Zeroing Neural Networks

Zeroing Neural Networks Finite-time Convergence Design, Analysis and Applications

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.12.2022

Verlag

John Wiley & Sons Inc

Seitenzahl

432

Maße (L/B/H)

23.5/15.7/2.7 cm

Gewicht

764 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-98599-0

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.12.2022

Verlag

John Wiley & Sons Inc

Seitenzahl

432

Maße (L/B/H)

23.5/15.7/2.7 cm

Gewicht

764 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-98599-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Zeroing Neural Networks
  • List of Figures xv

    List of Tables xxxi

    Author Biographies xxxiii

    Preface xxxv

    Acknowledgments xlv

    Part I Application to Matrix Square Root 1

    1 FTZNN for Time-varying Matrix Square Root 3

    1.1 Introduction 3

    1.2 Problem Formulation and ZNN Model 4

    1.3 FTZNN Model 4

    1.3.1 Model Design 5

    1.3.2 Theoretical Analysis 7

    1.4 Illustrative Verification 8

    1.5 Chapter Summary 11

    References 11

    2 FTZNN for Static Matrix Square Root 13

    2.1 Introduction 13

    2.2 Solution Models 14

    2.2.1 OZNN Model 14

    2.2.2 FTZNN Model 15

    2.3 Illustrative Verification 17

    2.3.1 Example 1 18

    2.3.2 Example 2 20

    2.4 Chapter Summary 21

    References 21

    Part II Application to Matrix Inversion 23

    3 Design Scheme I of FTZNN 25

    3.1 Introduction 25

    3.2 Problem Formulation and Preliminaries 25

    3.3 FTZNN Model 26

    3.3.1 Model Design 26

    3.3.2 Theoretical Analysis 29

    3.4 Illustrative Verification 30

    3.4.1 Example 1: Nonrandom Time-varying Coefficients 30

    3.4.2 Example 2: Random Time-varying Coefficients 34

    3.5 Chapter Summary 35

    References 36

    4 Design Scheme II of FT ZNN 39

    4.1 Introduction 39

    4.2 Preliminaries 40

    4.2.1 Mathematical Preparation 40

    4.2.2 Problem Formulation 41

    4.3 NT-FTZNN Model 41

    4.4 Theoretical Analysis 43

    4.4.1 NT-FTZNN in the Absence of Noises 43

    4.4.2 NT-FTZNN in the Presence of Noises 44

    4.5 Illustrative Verification 46

    4.5.1 Example 1: Two-dimensional Coefficient 47

    4.5.2 Example 2: Six-dimensional Coefficient 52

    4.5.3 Example 3: Application to Mobile Manipulator 54

    4.5.4 Example 4: Physical Comparative Experiments 54

    4.6 Chapter Summary 57

    References 57

    5 Design Scheme III of FTZNN 61

    5.1 Introduction 61

    5.2 Problem Formulation and Neural Solver 61

    5.2.1 FPZNN Model 62

    5.2.2 IVP-FTZNN Model 63

    5.3 Theoretical Analysis 64

    5.4 Illustrative Verification 70

    5.4.1 Example 1: Two-Dimensional Coefficient 70

    5.4.2 Example 2: Three-Dimensional Coefficient 73

    5.5 Chapter Summary 78

    References 78

    Part III Application to Linear Matrix Equation 81

    6 Design Scheme I of FTZNN 83

    6.1 Introduction 83

    6.2 Convergence Speed and Robustness Co-design 84

    6.3 R-FTZNN Model 90

    6.3.1 Design of R-FTZNN 90

    6.3.2 Analysis of R-FTZNN 91

    6.4 Illustrative Verification 93

    6.4.1 Numerical Example 93

    6.4.2 Applications: Robotic Motion Tracking 98

    6.5 Chapter Summary 101

    References 102

    7 Design Scheme II of FTZNN 105

    7.1 Introduction 105

    7.2 Problem Formulation 106

    7.3 FTZNN Model 106

    7.4 Theoretical Analysis 108

    7.4.1 Convergence 108

    7.4.2 Robustness 112

    7.5 Illustrative Verification 118

    7.5.1 Convergence 118

    7.5.2 Robustness 121

    7.6 Chapter Summary 122

    References 122

    Part IV Application to Optimization 125

    8 FTZNN for Constrained Quadratic Programming 127

    8.1 Introduction 127

    8.2 Preliminaries 128

    8.2.1 Problem Formulation 128

    8.2.2 Optimization Theory 128

    8.3 U-FTZNN Model 130

    8.4 Convergence Analysis 131

    8.5 Robustness Analysis 134

    8.6 Illustrative Verification 136

    8.6.1 Qualitative Experiments 136

    8.6.2 Quantitative Experiments 139

    8.7 Application to Image Fusion 143

    8.8 Application to Robot Control 146

    8.9 Chapter Summary 149

    References 149

    9 FTZNN for Nonlinear Minimization 151

    9.1 Introduction 151

    9.2 Problem Formulation and ZNN Models 151

    9.2.1 Problem Formulation 152

    9.2.2 ZNN Model 152

    9.2.3 RZNN Model 154

    9.3 Design and Analysis of R-FTZNN 154

    9.3.1 Second-Order Nonlinear Formula 155

    9.3.2 R-FTZNN Model 159

    9.4 Illustrative Verification 161

    9.4.1 Constant Noise 161

    9.4.2 Dynamic Noise 163

    9.5 Chapter Summary 165

    References 166

    10 FTZNN for Quadratic Optimization 169

    10.1 Introduction 169

    10.2 Problem Formulation 170

    10.3 Related Work: GNN and ZNN Models 172

    10.3.1 GNN Model 172

    10.3.2 ZNN Model 173

    10.4 N-FTZNN Model 174

    10.4.1 Models Comparison 175

    10.4.2 Finite-Time Convergence 176

    10.5 Illustrative Verification 178

    10.6 Chapter Summary 181

    References 181

    Part V Application to the Lyapunov Equation 183

    11 Design Scheme I of FTZNN 185

    11.1 Introduction 185

    11.2 Problem Formulation and Related Work 186

    11.2.1 GNN Model 186

    11.2.2 ZNN Model 187

    11.3 FTZNN Model 187

    11.4 Illustrative Verification 190

    11.5 Chapter Summary 193

    References 193

    12 Design Scheme II of FTZNN 197

    12.1 Introduction 197

    12.2 Problem Formulation and Preliminaries 197

    12.3 FTZNN Model 198

    12.3.1 Design of FTZNN 199

    12.3.2 Analysis of FTZNN 200

    12.4 Illustrative Verification 202

    12.5 Application to Tracking Control 205

    12.6 Chapter Summary 207

    References 207

    13 Design Scheme III of FTZNN 209

    13.1 Introduction 209

    13.2 N-FTZNN Model 210

    13.2.1 Design of N-FTZNN 210

    13.2.2 Re-Interpretation from Nonlinear PID Perspective 211

    13.3 Theoretical Analysis 212

    13.4 Illustrative Verification 219

    13.4.1 Numerical Comparison 219

    13.4.2 Application Comparison 224

    13.4.3 Experimental Verification 228

    13.5 Chapter Summary 229

    References 229

    Part VI Application to the Sylvester Equation 231

    14 Design Scheme I of FTZNN 233

    14.1 Introduction 233

    14.2 Problem Formulation and ZNN Model 233

    14.3 N-FTZNN Model 235

    14.3.1 Design of N-FTZNN 235

    14.3.2 Theoretical Analysis 237

    14.4 Illustrative Verification 243

    14.5 Robotic Application 248

    14.6 Chapter Summary 251

    References 251

    15 Design Scheme II of FTZNN 255

    15.1 Introduction 255

    15.2 ZNN Model and Activation Functions 256

    15.2.1 ZNN Model 256

    15.2.2 Commonly Used AFs 257

    15.2.3 Two Novel Nonlinear AFs 257

    15.3 NT-PTZNN Models and Theoretical Analysis 258

    15.3.1 NT-PTZNN1 Model 258

    15.3.2 NT-PTZNN2 Model 262

    15.4 Illustrative Verification 266

    15.4.1 Example 1 266

    15.4.2 Example 2 269

    15.4.3 Example 3 273

    15.5 Chapter Summary 274

    References 274

    16 Design Scheme III of FTZNN 277

    16.1 Introduction 277

    16.2 ZNN Model and Activation Function 278

    16.2.1 ZNN Model 278

    16.2.2 Sign-bi-power Activation Function 279

    16.3 FTZNN Models with Adaptive Coefficients 282

    16.3.1 SA-FTZNN Model 282

    16.3.2 PA-FTZNN Model 284

    16.3.3 EA-FTZNN Model 286

    16.4 Illustrative Verification 289

    16.5 Chapter Summary 294

    References 294

    Part VII Application to Inequality 297

    17 Design Scheme I of FTZNN 299

    17.1 Introduction 299

    17.2 FTZNN Models Design 299

    17.2.1 Problem Formulation 300

    17.2.2 ZNN Model 300

    17.2.3 Vectorization 300

    17.2.4 Activation Functions 301

    17.2.5 FTZNN Models 302

    17.3 Theoretical Analysis 303

    17.3.1 Global Convergence 303

    17.3.2 Finite-Time Convergence 304

    17.4 Illustrative Verification 309

    17.5 Chapter Summary 314

    References 314

    18 Design Scheme II of FTZNN 317

    18.1 Introduction 317

    18.2 NT-FTZNN Model Deisgn 318

    18.2.1 Problem Formulation 318

    18.2.2 ZNN Model 318

    18.2.3 NT-FTZNN Model 319

    18.2.4 Activation Functions 319

    18.3 Theoretical Analysis 320

    18.3.1 Global Convergence 320

    18.3.2 Finite-Time Convergence 321

    18.3.3 Noise-Tolerant Convergence 326

    18.4 Illustrative Verification 327

    18.5 Chapter Summary 334

    References 335

    Part VIII Application to Nonlinear Equation 337

    19 Design Scheme I of FTZNN 339

    19.1 Introduction 339

    19.2 Model Formulation 339

    19.2.1 OZNN Model 340

    19.2.2 FTZNN Model 340

    19.2.3 Models Comparison 341

    19.3 Convergence Analysis 341

    19.4 Illustrative Verification 343

    19.4.1 Nonlinear Equation f (u) with Simple Root 343

    19.4.2 Nonlinear Equation f (u) with Multiple Root 346

    19.5 Chapter Summary 347

    References 347

    20 Design Scheme II of FTZNN 349

    20.1 Introduction 349

    20.2 Problem and Model Formulation 349

    20.2.1 GNN Model 350

    20.2.2 OZNN Model 350

    20.3 FTZNN Model and Finite-Time Convergence 351

    20.4 Illustrative Verification 354

    20.5 Chapter Summary 356

    References 356

    21 Design Scheme III of FTZNN 359

    21.1 Introduction 359

    21.2 Problem Formulation and ZNN Models 359

    21.2.1 Problem Formulation 360

    21.2.2 ZNN Model 360

    21.3 Robust and Fixed-Time ZNN Model 361

    21.4 Theoretical Analysis 362

    21.4.1 Case 1: No Noise 362

    21.4.2 Case 2: Under External Noises 363

    21.5 Illustrative Verification 367

    21.6 Chapter Summary 370

    References 371

    Index 375