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RFMs
利用有理函数模型进行空间前方交会程序，已知同名像点和2张卫星影像的有理函数RPC文件用于求地面点坐标。(Space forward intersection process using rational function model, known as points and 2 with the same satellite images of the rational function RPC file is used to beg the ground point coordinates.)
- 2021-02-04 21:39:57下载
- 积分：1
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Analytical
贝叶斯决策代码 贝叶斯原理分类 输入样本数据进行处理 (MATLAB Bayesian)
- 2010-05-11 16:43:32下载
- 积分：1
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PolyRoots
The package provides methods for computing the roots of cluster polynomials
- 2011-05-13 08:03:04下载
- 积分：1
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ziranzhixiangxing
线列阵指向性图，用于水声领域换能器基阵的指向性仿真(Line array directivity diagram for the field of underwater acoustic change point simulation of energy converter arrays)
- 2012-05-04 20:13:39下载
- 积分：1
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ofdm-stbc-mimo
OFDM SPACE TIME BLOCK CODE MIMO MIMO PDF
- 2014-10-08 16:57:12下载
- 积分：1
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Newton-Raphson-power-flow
通用的牛顿拉夫逊法潮流计算程序，可以自行输入支路参数矩阵，节点参数矩阵。(Universal Newton Raphson power flow )
- 2014-01-02 19:20:32下载
- 积分：1
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paper4_vertify_zoom_lens_function1114
说明： 用于matlab模拟透镜的光线追迹，可以更改程序中的相关参数模拟任意面型的透镜对光线的聚焦或发散效果。(Ray tracing for matlab analog lens.)
- 2019-10-09 11:51:48下载
- 积分：1
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Mcodes_for_coa
通信系统的Matlab代码，包括括通信原理书中的大多代码可直接使用。
(Matlab code of the communication system, including most of the code including communication theory book can be used directly.)
- 2012-07-26 14:21:16下载
- 积分：1
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cami
Matlab图像处理基本操作及摄像机标定(Calibration of Matlab camera and image processing basic operation)
- 2015-04-14 20:57:21下载
- 积分：1
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Relevance-Vector-Machine
说明： 相关向量机（Relevance Vector Machine，简称RVM）是Micnacl E.Tipping于2000年提出的一种与SVM（Support Vector Machine）类似的稀疏概率模型，是一种新的监督学习方法。
它的训练是在贝叶斯框架下进行的，在先验参数的结构下基于主动相关决策理论（automatic relevance determination，简称ARD）来移除不相关的点，从而获得稀疏化的模型。在样本数据的迭代学习过程中，大部分参数的后验分布趋于零，与预测值无关，那些非零参数对应的点被称作相关向量（Relevance Vectors），体现了数据中最核心的特征。同支持向量机相比，相关向量机最大的优点就是极大地减少了核函数的计算量，并且也克服了所选核函数必须满足Mercer条件的缺点。(Relevance Vector Machine (RVM) is a sparse probability model similar to SVM (Support Vector Machine) proposed by Micnacl E. Tipping in 2000. It is a new supervised learning method.
Its training is carried out under the Bayesian framework. Under the structure of prior parameters, it is based on Automatic Relevance Determination (ARD) to remove the irrelevant points, so as to obtain the sparse model. In the iterative learning process of sample data, the posterior distribution of most parameters tends to zero, which is independent of the predicted value. The points corresponding to non-zero parameters are called Relevance Vectors, which represent the most core features of the data. Compared with support vector machine, the biggest advantage of correlation vector machine is that it greatly reduces the computation amount of kernel function, and also overcomes the shortcoming that the selected kernel function must meet Mercer's condition.)
- 2021-03-23 21:20:53下载
- 积分：1
