Patch-based Near-Optimal Image Denoising http://users.soe.ucsc.edu/~priyam/PLOW/download.php

In this paper, we consider the source localization for a mixed near-field (NF) and far-field (FF) narrowband signals impinging on a uniform linear array (ULA) with the symmetrical geometric configuration. A computationally efficient direction-of-arrivals (DOAs) and range estimation method for the mixed NF and FF signals is proposed, where the DOAs of the NF and FF signals are estimated separately, and the computationally burdensome eigendecomposition is avoided. Comparing to some existent method

Principles of Planar Near-Field Antenna Measurements 介绍天线近场测量的基础知识 Contents Preface xi 1 Introduction 1 1.1 The phenomena of antenna coupling 1 1.2 Characterisation via the measurement process 4 1.2.1 Free space radiation pattern 6 1.2.2 Polarisation 7 1.2.3 Bandwidth 8 1.3 The organisation of the book 11 1.4 References 12 2 Maxwell’s equations and electromagnetic wave propagation 13 2.1 Electric charge 13 2.2 The EM field 14 2.3 Accelerated charges 16 2.4 Maxwell’s equations 18 2.5 The electric and magnetic potentials 24 2.5.1 Static potentials 24 2.5.2 Retarded potentials 24 2.6 The inapplicability of source excitation as a measurement methodology 28 2.7 Field equivalence principle 28 2.8 Characterising vector EM fields 30 2.9 Summary 33 2.10 References 33 3 Introduction to near-field antenna measurements 35 3.1 Introduction 35 3.2 Antenna measurements 35 3.3 Forms of near-field antenna measurements 40 3.4 Plane rectilinear near-field antenna measurements 43 3.5 Chambers, screening and absorber 44 3.6 RF subsystem 47 3.7 Robotics positioner subsystem 52 3.8 Near-field probe 56 3.9 Generic antenna measurement process 58 3.10 Summary 60 3.11 References 60 4 Plane wave spectrum representation of electromagnetic waves 63 4.1 Introduction 63 4.2 Overview of the derivation of the PWS 64 4.3 Solution of the scalar Helmholtz equation in Cartesian coordinates 65 4.3.1 Introduction to integral transforms 65 4.3.2 Fourier transform solution of the scalar Helmholtz equation 65 4.4 On the choice of boundary conditions 78 4.5 Operator substitution (derivative of a Fourier transform) 79 4.6 Solution of the vector Helmholtz equation in Cartesian coordinates 81 4.7 Solution of the vector magnetic wave equation in Cartesian coordinates 83 4.8 The relationship between electric and magnetic spectral components 84 4.9 The free-space propagation vector k 87 4.10 Plane wave impedance 88 4.11 Interpretation as an angular spectrum of plane waves 90 4.12 Far-field antenna radiation patterns: approximated by the angular spectrum 92 4.13 Stationary phase evaluation of a double integral 95 4.14 Coordinate free form of the near-field to angular spectrum transform 101 4.15 Reduction of the coordinate free form of the near-field to far-field transform to Huygens’ principle 104 4.16 Far-fields from non-planar apertures 106 4.17 Microwave holographic metrology (plane-to-plane transform) 107 4.18 Far-field to near-field transform 108 4.19 Radiated power and the angular spectrum 112 4.20 Summary of conventional near-field to far-field transform 115 4.21 References 117 5 Measurements – practicalities of planar near-field antenna measurements 119 5.1 Introduction 119 5.2 Sampling (interpolation theory) 120 5.3 Truncation, spectral leakage and finite area scan errors 121 5.4 Antenna-to-antenna coupling (transmission) formula 125 5.4.1 Attenuation of evanescent plane wave mode coefficients 136 5.4.2 Simple scattering model of a near-field probe during a planar measurement 137 5.5 Evaluation of the conventional near-field to far-field transform 138 5.5.1 Standard techniques for the evaluation of a double Fourier integral 139 5.6 General antenna coupling formula: arbitrarily orientated antennas 143 5.7 Plane-polar and plane-bipolar near-field to far-field transform 148 5.7.1 Boundary values known in plane-polar coordinates 150 5.7.2 Boundary values known in plane-bipolar coordinates 151 5.8 Regular azimuth over elevation and elevation over azimuth coordinate systems 156 5.9 Polarisation basis and antenna measurements 159 5.9.1 Cartesian polarisation basis – Ludwig I 159 5.9.2 Polar spherical polarisation basis 160 5.9.3 Azimuth over elevation basis – Ludwig II 161 5.9.4 Copolar and cross-polar polarisation basis – Ludwig III 163 5.9.5 Circular polarisation basis – RHCP and LHCP 165 5.10 Overview of antenna alignment corrections 169 5.10.1 Scalar rotation of far-field antenna patterns 169 5.10.2 Vector rotation of far-field antenna patterns 171 5.10.4 Rotation of copolar polarisation basis – generalized Ludwig III 173 5.10.5 Generalized compound vector rotation of far-field antenna patterns 174 5.11 Brief description of near-field coordinate systems 175 5.11.1 Range fixed system 176 5.11.2 Antenna mechanical system 177 5.11.3 Antenna electrical system 178 5.11.4 Far-field azimuth and elevation coordinates 178 5.11.5 Ludwig III copolar and cross-polar definition 178 5.11.6 Probe alignment definition (SPP) 178 5.11.7 General vector rotation of antenna radiation patterns 179 5.12 Directivity and gain 180 5.12.1 Directivity 180 5.12.2 Gain – by substitution method 181 5.12.3 Gain-transfer (gain-comparison) method 182 5.13 Calculating the peak of a pattern 183 5.13.1 Peak by polynomial fit 183 5.13.2 Peak by centroid 185 5.14 Summary 186 5.15 References 187 6Pr obe pattern characterisation 189 6.1 Introduction 189 6.2 Effect of the probe pattern on far-field data 189 6.3 Desirable characteristics of a near-field probe 191 6.4 Acquisition of quasi far-field probe pattern 193 6.4.1 Sampling scheme 194 6.4.2 Electronic system drift (tie-scan correction) 197 6.4.3 Channel-balance correction 198 6.4.4 Assessment of chamber multiple reflections 200 6.4.5 Correction for rotary errors 202 6.4.6 Re-tabulation of probe vector pattern function 205 6.4.7 Alternate interpolation formula 209 6.4.8 True far-field probe pattern 211 6.5 Finite element model of open-ended rectangular waveguide probe 213 6.6 Probe displacement correction 217 6.7 Channel-balance correction 217 6.8 References 218 7 Computational electromagnetic model of a planar near-field measurement process 219 7.1 Introduction 219 7.2 Method of sub-apertures 220 7.3 Aperture set in an infinite perfectly conducting ground plane 223 7.3.1 Plane wave spectrum antenna–antenna coupling formula 225 7.4 Vector Huygens’ method 227 7.5 Kirchhoff–Huygens’ method 229 7.6 Generalized technique for the simulation of near-field antenna measurements 233 7.6.1 Mutual coupling and the reaction theorem 234 7.7 Near-field measurement simulation 237 7.8 Reaction theorem 239 7.8.1 Lorentz reciprocity theorem (field reciprocity theorem) 240 7.8.2 Generalized reaction theorem 244 7.8.3 Mutual impedance and the reaction theorem 247 7.9 Summary 247 7.10 References 248 8 Antenna measurement analysis and assessment 249 8.1 Introduction 249 8.2 The establishment of the measure from the measurement results 249 8.2.1 Measurement errors 250 8.2.2 The sources of measurement ambiguity and error 253 8.2.3 The examination of measurement result data to establish the measure 256 8.3 Measurement error budgets 259 8.3.1 Applicability of modelling error sources 259 8.3.2 The empirical approach to error budgets 260 8.4 Quantitative measures of correspondence between data sets 261 8.4.1 The requirement for measures of correspondence 261 8.5 Comparison techniques 263 8.5.1 Examples of conventional data set comparison techniques 263 8.5.2 Novel data comparison techniques 267 8.6 Summary 282 8.7 References 283 9 Advanced planar near-field antenna measurements 285 9.1 Introduction 285 9.2 Active alignment correction 285 9.2.1 Acquisition of alignment data in a planar near-field facility 287 9.2.2 Acquisition of mechanical alignment data in a planar near-field facility 289 9.2.3 Example of the application of active alignment correction 291 9.3 Amplitude only planar near-field measurements 296 9.3.1 PTP phase retrieval algorithm 297 9.3.2 PTP phase retrieval algorithm – with aperture constraint 301 9.4 Efficient position correction algorithms, in-plane and z−plane corrections 303 9.4.1 Taylor series expansion 305 9.4.2 K-correction method 311 9.5 Partial scan techniques 315 9.5.1 Auxiliary translation 315 9.5.2 Rotations of the AUT about the z-axis 319 9.5.3 Auxiliary rotation – bi-planar near-field antenna measurements 320 9.5.4 Near-field to far-field transformation of probe corrected data 329 9.5.5 Applicability of the poly-planar technique 335 9.5.6 Complete poly-planar rotational technique 338 9.6 Concluding remarks 342 9.7 References 344 Appendix A: Other theories of interaction 347 A.1 Examples of postulated mechanisms of interaction 347 Appendix B: Measurement definitions as used in the text 354 Appendix C: An overview of coordinate systems 357 C.1 Antenna mechanical system (AMS) 357 C.2 Antenna electrical system (AES) 357 C.3 Far-field plotting systems 358 C.4 Direction cosine 358 C.5 Azimuth over elevation 360 C.6 Elevation over azimuth 361 C.7 Polar spherical 362 C.8 Azimuth and elevation (true-view) 364 C.9 Range of spherical angles 365 C.10 Transformation between coordinate systems 366 C.11 Coordinate systems and elemental solid angles 367 C.12 Relationship between coordinate systems 368 C.13 Azimuth, elevation and Roll angles 371 C.14 Euler angles 373 C.15 Quaternion 374 C.16 Elemental solid angle for a true-view coordinate system 377 Appendix D: Trapezoidal discrete Fourier transform 380 Appendix E: Calculating the semi-major axis, semi-minor axis and tilt angle of a rotated ellipse 384 Index 389

ifft实现代码matlab cpp实施近场SAR 近场SAR的cpp实现。 原始代码是用MATLAB编写的。 如何设定 使用犰狳进行矩阵/多维数据集转换，并使用opencv进行绘图。 HDF5用于存储数据。 犰狳可以在这里下载。 尽管我个人强烈建议使用自制软件来安装所有程序。 签出此：。 该页面还包括犰狳的其他先决条件。 在Mac和Linux上： 首先，请在安装Armadillo之前安装OpenBlas和LAPACK。 brew install openblas 。 其他库也可以类似的方式安装。 不建议使用：OpenCV可以从下载。 这是最新的更新。 可以在以下位置找到Mac上的OpenCV安装指南：。 不再使用OpenCV。 文件 测试文件 Test.cpp创建一个由5个斑点组成的模拟目标，并将目标处理为接收到的信号（.cpp文件中的S_echo）。 然后计算接收到的信号以重建目标。 该.cpp文件旨在测试并给出重建算法的简单演示。 make test和./test来构建和运行程序。 test2d.cpp 这是重建真实2D信号的主程序。 信号存储在“ real2d.txt”和“ i

snr matlab代码大规模MIMO和智能反射表面的功率缩放定律和近场特性 这是与以下科学文章相关的代码包： EmilBjörnson和Luca Sanguinetti，“通信协会IEEE开放期刊”出现。 该软件包包含一个基于Matlab的仿真环境，该环境可复制本文中的一些数值结果和图形。 我们鼓励您也进行可重复的研究！ 文章摘要 大型阵列的使用可能是无线通信中容量问题的解决方案。 当使用Massive MIMO接收器和半双工中继器时，信噪比（SNR）随着阵列元素N的数量线性增加。 此外，智能反射表面（IRS）最近引起了人们的注意，因为它们可以中继信号以达到随N ^ 2增长的SNR，这似乎是一个主要好处。 在本文中，我们对任意大小的平面阵列使用确定性传播模型，以证明所提到的SNR行为和相关的功率缩放定律仅适用于远场。 它们不能用于研究N→∞的状态。 我们得出了一个精确的通道增益表达式，该表达式捕获了三个基本的近场行为，并使用它重新审视了功率定律。 我们得出了新的有限渐近SNR极限，但也得出结论，在实践中不太可能达到这些极限。 我们进一步证明，尽管具有更快的SNR增长，但IRS辅助设置

以樱桃番茄为研究对象，采用近红外漫反射法，建立了BP网络模型，研究了樱桃番茄中糖的含量。 使用平滑和主成分分析（PCA）从实验光谱数据中提取光谱特征。 将预处理的光谱数据作为网络的输入，将测量的樱桃番茄的含糖量作为输出，建立80-12-1网络模型结构，交叉验证的确定系数为0.8328，并且平均绝对偏差为0.5711。 结果表明，建立的BP神经网络模型可以快速有效地实现樱桃番茄糖含量的无损检测。

近场校准可以在室内进行，避免受到环境和安全问题的影响，使其具有重要的研究价值。 然而，该应用受到校准效率和精度的限制。 提出了一种基于码分多址（CDMA）方案的近场标定方法，以减少标定时间，提高标定精度。 在提出的方法中，与每个天线相关的校准信号通过唯一的扩频码序列而不是连续波（CW）来区分。 通过推导得到校准精度与信噪比（SNR）之间的关系，仿真结果验证了理论推导结果的正确性。 如果SNR高于15dB，则幅度/相位的校准精度可以分别达到0.1分贝（dB）和1度（deg）。 该方法可以很好地应用于大规模相控阵天线的标定。

基于英文版epub电子版转换而成 1. A4排版后，共383页 2. 标准字体10pt，章节标题15pt 3. 调整页边距 4. 带目录 适合在PC上使用PDF阅读软件阅读.

THE SINGULARITY IS NEAR Ray Kurzweil

这组文件可用于构建具有近乎完美重构的多相滤波器组。 滤波器组使用两个均匀调制的 DFT 滤波器组实现，这些滤波器组频移 1/2 通道宽度。 有效地，使用了两次过采样。 通道数必须是 2 的倍数。 可以自由选择每个通道的抽头数。 提供了用于设计原型过滤器的脚本，该脚本基于“root-raised-error-function”。 原型具有完全线性的相位。 每通道 128 个抽头，可实现 -300 dB 的平均重建误差。 相邻通道的通道分离度优于150 dB，相距较远的通道的通道分离度优于300 dB。 处理速度约为 200 kSamples/秒，对于 32 个抽头/通道，与通道数量无关。 有了足够的内存，大量的通道（例如 64K）是可行的。