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TWOorderFLL
二阶锁频环Matlab代码，使用叉积鉴频器，内有仿真图(TwoOrderPLL Matlab)
- 2016-10-22 16:17:42下载
- 积分：1
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MATLAB
MATLAB基础教程课件，浅显易懂，还有一个pdf的start手册(MATLAB-based Tutorial courseware, easy to understand, there is a pdf manual in start)
- 2009-11-10 17:29:10下载
- 积分：1
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Mie_S12
计算mie散射过程中的散射幅度函数，对研究粒子散射问题有较大帮助(Mie scattering process of calculating the scattering amplitude function, the study of particle scattering problems have more to help)
- 2006-10-27 19:17:11下载
- 积分：1
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Correlation-matrix
本程序主要针对数据处理中相关矩阵的计算进行编写！(This program is mainly for calculating the correlation matrix be written)
- 2014-09-11 13:23:13下载
- 积分：1
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JPEG-matlab
matlab实现的JPEG图像压缩程序
可成功运行(matlab implementation of JPEG image compression program which can be run successfully)
- 2013-07-30 19:24:27下载
- 积分：1
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tubianjiance
傅里叶对直流突变信号的监测，与小波算法进行对比分析(Fourier DC mutation signal monitoring, and comparative analysis of wavelet algorithm)
- 2013-03-29 10:56:22下载
- 积分：1
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载波
说明： 利用matlab仿真实现载波的平方环载波同步,costas环载波同步和符号同步(The square loop carrier synchronization, Costas loop carrier synchronization and symbol synchronization are realized by MATLAB simulation)
- 2020-10-24 10:50:55下载
- 积分：1
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acdc
The acdc algorithm for finding the
approximate general (non-orthogonal)
joint diagonalizer (in the direct Least
Squares sense) of a set of Hermitian
matrices.
- 2014-10-11 16:39:32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
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show
matlab show FFT and so on
- 2011-01-01 22:14:27下载
- 积分：1
