俄罗斯和德国大地电磁专著,利用随机信号进行地球物理勘探
2022-01-04 22:22:42 12.6MB 大地电磁经典
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本书的主旨是让读者熟练掌握MATLAB,在解决工程应用时,具备所需要的基本编程概念和技能。本书在函数、内容与结构、练习题、函数接口等方面较前一版有改动。全书分成两大部分:第一部分讲述用MATLAB进行程序设计及解决实际问题,包括MATLAB程序设计概念与组织、选择、循环、字符串操作、单元阵列及结构、高级文件输入/输出及高级函数等;第二部分针对实际应用,包括用MATLAB绘图、解线性代数方程组、进行基本统计、集合、排序和索引、处理声音和图像,以及高等数学中的曲线拟合、复数计算、微积分等。
2021-12-30 22:23:12 21.47MB MatLab 国外经典教程 第4版 英文
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Using the FreeRTOS Real Time Kernel - A Practical Guide_opened 中文版
2021-12-30 16:03:00 3.02MB FreeRTOS 中文版
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Table of Contents: Chap 1 - Background and WLAN Overview Chap 2 - Synchronization Chap 3 - Modulation and Coding Chap 4 - Antenna Diversity Chap 5 - RF Distortion Analysis for WLAN. Chap 6 - Medium Access Control for Wireless LANs. Chap 7 - Medium Access Control (MAC) for HiperLAN/2 Networks Chap 8 - Rapid Prototyping for WLANs
2021-12-26 23:16:42 5.13MB OFDM WLAN
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Dedication v Biographies of the authors vii Preface xv Abbreviations xix 1. THE OPTIMIZATION PROBLEM 1 1.1 Introduction 1 1.2 The Basic Optimization Problem 4 1.3 General Structure of Optimization Algorithms 8 1.4 Constraints 10 1.5 The Feasible Region 17 1.6 Branches of Mathematical Programming 22 References 24 Problems 25 2. BASIC PRINCIPLES 27 2.1 Introduction 27 2.2 Gradient Information 27 2.3 The Taylor Series 28 2.4 Types of Extrema 31 2.5 Necessary and Sufficient Conditions for Local Minima and Maxima 33 2.6 Classification of Stationary Points 40 2.7 Convex and Concave Functions 51 2.8 Optimization of Convex Functions 58 References 60 Problems 60 3. GENERAL PROPERTIES OF ALGORITHMS 65 3.1 Introduction 65 3.2 An Algorithm as a Point-to-Point Mapping 65 3.3 An Algorithm as a Point-to-Set Mapping 67 3.4 Closed Algorithms 68 3.5 Descent Functions 71 3.6 Global Convergence 72 3.7 Rates of Convergence 76 References 79 Problems 79 4. ONE-DIMENSIONAL OPTIMIZATION 81 4.1 Introduction 81 4.2 Dichotomous Search 82 4.3 Fibonacci Search 85 4.4 Golden-Section Search 92 4.5 Quadratic Interpolation Method 95 4.6 Cubic Interpolation 99 4.7 The Algorithm of Davies, Swann, and Campey 101 4.8 Inexact Line Searches 106 References 114 Problems 114 5. BASIC MULTIDIMENSIONAL GRADIENT METHODS 119 5.1 Introduction 119 5.2 Steepest-Descent Method 120 5.3 Newton Method 128 5.4 Gauss-Newton Method 138 References 140 Problems 140 6. CONJUGATE-DIRECTION METHODS 145 6.1 Introduction 145 6.2 Conjugate Directions 146 6.3 Basic Conjugate-Directions Method 149 6.4 Conjugate-Gradient Method 152 6.5 Minimization of Nonquadratic Functions 157 6.6 Fletcher-Reeves Method 158 6.7 Powell's Method 159 6.8 Partan Method 168 References 172 XI Problems 172 7. QUASI-NEWTON METHODS 175 7.1 Introduction 175 7.2 The Basic Quasi-Newton Approach 176 7.3 Generation of Matrix Sk 177 7.4 Rank-One Method 181 7.5 Davidon-Fletcher-Powell Method 185 7.6 Broyden-Fletcher-Goldfarb-Shanno Method 191 7.7 Hoshino Method 192 7.8 The Broyden Family 192 7.9 The Huang Family 194 7.10 Practical Quasi-Newton Algorithm 195 References 199 Problems 200 8. MINIMAX METHODS 203 8.1 Introduction 203 8.2 Problem Formulation 203 8.3 Minimax Algorithms 205 8.4 Improved Minimax Algorithms 211 References 228 Problems 228 9. APPLICATIONS OF UNCONSTRAINED OPTIMIZATION 231 9.1 Introduction 231 9.2 Point-Pattern Matching 232 9.3 Inverse Kinematics for Robotic Manipulators 237 9.4 Design of Digital Filters 247 References 260 Problems 262 10. FUNDAMENTALS OF CONSTRAINED OPTIMIZATION 265 10.1 Introduction 265 10.2 Constraints 266 Xll 10.3 Classification of Constrained Optimization Problems 273 10.4 Simple Transformation Methods 277 10.5 Lagrange Multipliers 285 10.6 First-Order Necessary Conditions 294 10.7 Second-Order Conditions 302 10.8 Convexity 308 10.9 Duality 311 References 312 Problems 313 11. LINEAR PROGRAMMING PART I: THE SIMPLEX METHOD 321 11.1 Introduction 321 11.2 General Properties 322 11.3 Simplex Method 344 References 368 Problems 368 12. LINEAR PROGRAMMING PART II: INTERIOR-POINT METHODS 373 12.1 Introduction 373 12.2 Primal-Dual Solutions and Central Path 374 12.3 Primal Affine-Scaling Method 379 12.4 Primal Newton Barrier Method 383 12.5 Primal-Dual Interior-Point Methods 388 References 402 Problems 402 13. QUADRATIC AND CONVEX PROGRAMMING 407 13.1 Introduction 407 13.2 Convex QP Problems with Equality Constraints 408 13.3 Active-Set Methods for Strictly Convex QP Problems 411 13.4 Interior-Point Methods for Convex QP Problems 417 13.5 Cutting-Plane Methods for CP Problems 428 13.6 Ellipsoid Methods 437 References 443 Xlll Problems 444 14. SEMIDEFINITE AND SECOND-ORDER CONE PROGRAMMING 449 14.1 Introduction 449 14.2 Primal and Dual SDP Problems 450 14.3 Basic Properties of SDP Problems 455 14.4 Primal-Dual Path-Following Method 458 14.5 Predictor-Corrector Method 465 14.6 Projective Method of Nemirovski and Gahinet 470 14.7 Second-Order Cone Programming 484 14.8 A Primal-Dual Method for SOCP Problems 491 References 496 Problems 497 15. GENERAL NONLINEAR OPTIMIZATION PROBLEMS 501 15.1 Introduction 501 15.2 Sequential Quadratic Programming Methods 501 15.3 Modified SQP Algorithms 509 15.4 Interior-Point Methods 518 References 528 Problems 529 16. APPLICATIONS OF CONSTRAINED OPTIMIZATION 533 16.1 Introduction 533 16.2 Design of Digital Filters 534 16.3 Model Predictive Control of Dynamic Systems 547 16.4 Optimal Force Distribution for Robotic Systems with Closed Kinematic Loops 558 16.5 Multiuser Detection in Wireless Communication Channels 570 References 586 Problems 588 Appendices 591 A Basics of Linear Algebra 591 A. 1 Introduction 591 XIV A.2 Linear Independence and Basis of a Span 592 A.3 Range, Null Space, and Rank 593 A.4 Sherman-Morrison Formula 595 A.5 Eigenvalues and Eigenvectors 596 A.6 Symmetric Matrices 598 A.7 Trace 602 A.8 Vector Norms and Matrix Norms 602 A.9 Singular-value Decomposition 606 A. 10 Orthogonal Projections 609 A.l 1 Householder Transformations and Givens Rotations 610 A. 12 QR Decomposition 616 A. 13 Cholesky Decomposition 619 A. 14 Kronecker Product 621 A. 15 Vector Spaces of Symmetric Matrices 623 A. 16 Polygon, Polyhedron, Polytope, and Convex Hull 626 References 627 B Basics of Digital Filters 629 B.l Introduction 629 B.2 Characterization 629 B. 3 Time-Domain Response 631 B.4 Stability Property 632 B.5 Transfer Function 633 B.6 Time-Domain Response Using the Z Transform 635 B.7 Z-Domain Condition for Stability 635 B.8 Frequency, Amplitude, and Phase Responses 636 B.9 Design 639 Reference 644 Index 645
2021-12-21 16:10:10 5.1MB optimization
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Differential Evolution A Practical Approach to Global Optimization 差分进化算法
2021-12-20 11:30:44 10.59MB 差分进化 全局优化
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工科必备,最实用的、最全面的傅里叶积分闭式解
2021-12-19 16:27:37 23.59MB Fourier Integrals
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A Practical Guide To Quantitative Finance Interviews pdf,
2021-12-16 11:09:35 11.56MB pdf
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Recommender systems are practically a necessity for keeping a site's content current, useful, and interesting to visitors. Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Practical Recommender Systems goes behind the curtain to show readers how recommender systems work and, more importantly, how to create and apply them for their site. This hands-on guide covers scaling problems and other issues they may encounter as their site grows. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
2021-12-13 11:08:15 12.86MB Practical Re
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最新的STA 书籍,介绍非常详细,写的通俗易懂,作者 J. Bhasker
2021-12-12 22:02:05 3.55MB STA ASIC J. Bhasker
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