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稀疏傅里叶变换(英文版)

稀疏傅里叶变换(英文版)

  • 字数: 260
  • 出版社: 世界图书出版公司
  • 作者: (美)海塞姆·哈桑|责编:陈亮//刘慧
  • 商品条码: 9787519266455
  • 版次: 1
  • 开本: 16开
  • 页数: 260
  • 出版年份: 2020
  • 印次: 1
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内容简介
傅里叶变换是计算信号频域表示的最基本工具之一。 它在信号处理、通信、音频和视频压缩、医学成像、基因 组学、天文学以及许多领域中发挥着核心作用。由于其广 泛使用,傅里叶变换的快速算法能使大量应用受益。目前 的最快算法是快速傅里叶变换(FFT),它在接近线性的时 间内运行,使其成为很多领域不可或缺的工具。然而,今 天,特别是对于大数据问题,FFT算法的运行速度还是赶不 上需求量。因此,在次线性时间内运行的更快的算法,即 甚至不采样所有数据点,已经变得必要。本书通过开发稀 疏傅里叶变换算法来解决上述问题。本书的研究内容曾获 得2016年美国计算机协会(ACM)的年度最佳博士论文奖。
目录
Chapter 1 Introduction 1.1 Sparse Fourier Transform Algorithms 1.2 Applications of the Sparse Fourier Transform 1.3 Book Overview PART Ⅰ THEORY OF THE SPARSE FOURIER TRANSFORM Chapter 2 Preliminaries 2.1 Notation 2.2 Basics Chapter 3 Simple and Practical Algorithm 3.1 Introduction 3.2 Algorithm Chapter 4 Optimizing Runtime Complexity 4.1 Introduction 4.2 Algorithm for the Exactly Sparse Case 4.3 Algorithm for the General Case 4,4 Extension to Two Dimensions Chapter 5 Optimizing Sample Complexity 5.1 Introduction 5.2 Algorithm for the Exactly Sparse Case 5.3 Algorithm for the General Case Chapter 6 Numerical Evaluation 6.1 Implementation 6.2 Experimental Setup 6.3 Numerical Results PART Ⅱ APPLICATIONS OF THE SPARSE FOURIER TRANSFORM Chapter 7 GHz-Wide Spectrum Sensing and Decoding 7.1 Introduction 7.2 Related Work 7.3 BigBand 7.4 Channel Estimation and Calibration 7.5 Differential Sensing of Non-Sparse Spectrum 7.6 A USRP-Based Implementation 7.7 BigBand's Spectrum Sensing Results 7.8 BigBand's Decoding Results 7.9 D-BigBand's Sensing Results 7.10 Conclusion Chapter 8 Faster GPS Synchronization 8.1 Introduction 8.2 GPS Primer 8.3 QuickSync 8.4 Theoretical Guarantees 8.5 Doppler Shift and Frequency Offset 8.6 Testing Environment 8.7 Results 8.8 Related Work 8.9 Conclusion Chapter 9 Light Field Reconstruction Using Continuous Fourier Sparsity 9.1 Introduction 9.2 Related Work 9.3 Sparsity in the Discrete vs. Continuous Fourier Domain 9.4 Light Field Notation 9.5 Light Field Reconstruction Algorithm 9.6 Experiments 9.7 Results 9.8 Discussion 9.9 Conclusion Chapter 10 Fast ln-Vivo MRS Acquisition with Artifact Suppression 10.1 Introduction 10.2 MRS-SFT 10.3 Methods 10,4 MRS Results 10.5 Conclusion Chapter 11 Fast Multi-Dimensional NMR Acquisition and Processing 11.1 Introduction 11.2 Multi-Dimensional Sparse Fourier Transform 11.3 Materials and Methods 11.4 Results 11.5 Discussion 11.6 Conclusion Chapter 12 Conclusion 12.1 Future Directions Appendix A Proofs Appendix B The Optimality of the Exactly k-Sparse Algorithm 4.1 Appendix C Lower Bound of the Sparse Fourier Transform in the General Case Appendix D Efficient Constructions of Window Functions Appendix E Sample Lower Bound for the Bernoulli Distribution Appendix F Analysis of the QuickSync System F.1 Analysis of the Baseline Algorithm F.2 Tightness of the Variance Bound F.3 Analysis of the QuickSync Algorithm Appendix G A 0.75 Million Point Sparse Fourier Transform Chip G.1 The Algorithm G.2 The Architecture G.3 The Chip References Author Biography

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