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模拟信号的数字化传输---增量调制系统
用SIMULINK建立简单增量调制系统的模型并进行
（3） 正弦信号
（4） 语音信号
的传输。
改变抽样频率和量化台阶大小，观察重建信号以及量化噪声信号的波形；对于语音信号主观评价声音质量的变化。
-Digitized analog signal transmission systems--- delta modulation delta modulation SIMULINK easy set up of the model s
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从ML-EM 重建算法入手，分析了贝叶斯模型的一些关键点，针对采用传统方法求解MAP问题的局限性，提出一种用于正电子成像的贝叶斯神经网络重建算法，为了保留边缘信息，引入了二进制的保边缘变量，并应用共轭神经网络求解，模拟的重建结果表明，应用这种算法可以得到比ML-EM 算法更好的重建图像@-From the ML-EM reconstruction algorithm start with an analysis of Bayesian model some of the key points,
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计算机视觉的基本任务之一是从摄像机获取的图像信息出发计算三维空间中物体的几何信息，并由此重建和识别物体。这两者之间的关系就是由摄像机的几何成像模型来决定，即由摄像机的参数来决定。实现了张正友和tasi的matlab标定程序！-The basic tasks of computer vision is one of the images from the camera to obtain information from the calculation of three-dimensional g
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这篇文章讲述基于相空间重构的模糊集用于复时间序列的暂态模式。文章详细说明关于时间序列的构建、说明暂态识别的概念、原理，优化函数的选择和优化结果等均有很好的步骤和完整实验结果。-This article describes the phase space reconstruction based on fuzzy sets for the transient model complex time series. Article details the construction of time se
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全变差图像处理Matlab程序，for the paper: "Algorithms and Software for Total Variation Image Reconstruction via First-Order Methods, Numerical Algorithms"-Software for Total Variation Image Reconstruction (for Matlab Version 7.5 or later)
"mxTV" is a software
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ct投影重建（shep-logan模型的生成投影以及重建）-ct projection reconstruction (shep-logan model for the generation of projection and reconstruction)
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可根据所给参数绘制出头模型图形，并对其进行投影和反投影重建的算法，可正常运行，得到较为理想的结果。-Can be drawn according to the parameters of his early model of graphics, and its projection and back projection reconstruction algorithm, running, get more desirable results.
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自重构的人工免疫网络模型Since the reconstruction of the artificial immune network model-Since the reconstruction of the artificial immune network model
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激光谐振腔 自再现模型 条形腔 矩形腔 圆形腔-Since the laser resonator cavity rectangular cavity reconstruction model circular cavity strip
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提出利用电云进行模型重构的算法，该算法基于点云的几何形状特征，很好的算法。-Proposed the use of electric cloud model reconstruction algorithm based on the geometric shape of the point cloud, a good algorithm.
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对EEG的原始数据进行小波分解和重构以及做ar模型功率谱估计-EEG raw data wavelet decomposition and reconstruction, ar model power spectrum estimation
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采用压缩感知的方法，结合信号的小波树模型，对一维信号进行压缩重构。-Using Compressed sensing methods, combined with wavelet tree model of the signal, achieve the goal of the one-dimensional signal compression and reconstruction.
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基于压缩感知的图像修复,，基于图像在复数小波变换上的稀疏性，利用迭代硬阈值方法
求解重构模型，进而获得重构图像.-Based on compressed sensing image restoration, image-based complex wavelet transform on the sparsity of the iterative method for solving hard threshold reconstruction model, and then get the
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基于R-L模型的CT扫描和滤波反投影重建的程序实现-Based on CT scan and filter back projection reconstruction RL model program
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利用matlab自带的BP神经网络工具箱对duffing混沌背景模型进行相空间重构与预测，程序中已经给出duffing函数，主函数中也给出了主要注释，方便大家学习交流。-BP' s own use matlab neural network toolbox for duffing chaotic background model and prediction of phase space reconstruction, the program has been given duffing
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Re-implementation of Simakov, Frolova and Basri "Dense Shape Reconstruction from a Moving Oject under Arbitrary, Unknown Lighting", 2003
This re-imp is restricted to linear lighting model (eq. 10 in the paper)-Re-implementation of Simakov, Frolova
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CT图像重建算法的实现，包括ART算法，FBP滤波反投影算法，能得出清晰的人头模型图像。-CT image reconstruction algorithm, including the ART algorithm, FBP filtered back-projection algorithm that can draw a clear head model image.
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本文首先研究了ISAR成像的基本原理，在理想转台模型的基础上对距离-多普勒(R-D)成像算法做了分析，对目前常用的运动补偿技术进行了对比和研究，并将这些技术用于雅克-42飞机的实测数据中。然后，论文系统地论述了压缩感知主体理论，重点对信号重构中的基追踪(BP)算法和正交匹配追踪(OMP)算法进行了深入的研究和讨论，并通过正弦信号的仿真结果验证了两种方法的有效性。-Firstly, the basic principle of ISAR imaging study, based on an ide
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Our world is three-dimensional, but camera image is two-dimensional, in order to obtain
the three-dimensional information of objective object’s by the two-dimensional images, we
need to rebuild the three-dimensional model of the target so that we
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This paper proposes a new variant of the least square autoregressive (LSAR) method for speech reconstruction, which can estimate
via least squares a segment of missing samples by applying the linear
prediction (LP) model of speech. First, we show t
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