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这是一本描述MIMO多输入多输出天线通信系统基础知识的书，包括MIMO发展现在现状，MIMO目前面临的问题，MIMO的信道模型，空时分组码，分层空时码，以及信道估计等。-This is a descr iption of MIMO multiple-input multiple-output antenna communication system based on knowledge of books, including MIMO development is now status quo,
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多元线性分析的源代码附有中文说明，可用于解决多元线性分析的问题-Multiple linear analysis with the Chinese descr iption of the source code can be used to solve the problem of multiple linear analysis
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Descr iption
A wrapper to the zxing library (http://code.google.com/p/zxing/). This submission includes files to encode a QR code from a string message, and decode a string message from an image containing an existing QR code. With little work the
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试者工作特征曲线 （receiver operating characteristic curve，简称ROC曲线），又称为感受性曲线（sensitivity curve）。得此名的原因在于曲线上各点反映着相同的感受性，它们都是对同一信号刺激的反应，只不过是在几种不同的判定标准下所得的结果而已。接受者操作特性曲线就是以虚报概率为横轴，击中概率为纵轴所组成的坐标图，和被试在特定刺激条件下由于采用不同的判断标准得出的不同结果画出的曲线。-PLOTROC Plot receiver operating
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潮流程序，多初学入门者很好使，，分了多个模块，每个模块均有说明
-Trend of the program, more than the novice beginners to very good make, and divided into multiple modules, each module has a descr iption of
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一个滤除50Hz及其整倍数的陷波器生成代码，以及对其产生原理的说明。-A filter and a whole multiple of 50Hz notch generated code, and a descr iption of its principle of generation.
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基于OpenMP的压缩感知多描述并行处理算法.pdf-The compressed sensing based multiple descr iption OpenMP parallel processing algorithms. Pdf
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数学建模 训练题目 心脏病的判别 主要采用多元线性回归模型 采用matlab编程 ，附有题目，论文，完整代码，以及程序运行的完整说明，希望对大家有用-Mathematical modeling training subject criterion of heart disease mainly using multiple linear regression model using matlab programming, with the title, thesis, complete code
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关于如何选取核函数的matlab文件，内有多个核函数及说明-About how to choose the kernel function matlab file, there are multiple kernels and descr iption
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Matlab example simulating a BPSK transmission and reception in Rayleigh channel. The scr ipt performs the following
(a) Generate random binary sequence of +1’s and -1’s.
(b) Multiply the symbols with the channel and then add white Gaussian
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多核变换，稀疏变换，核变换自适应学习，图形图像变换(Descr iption
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Multi-Kernel-Path package is a Matlab program that computes the entire regularization
path for multiple-kernel learning problems. More precisely, it solves any learning
problem with a smooth loss
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