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new_MatrixInverse
材料科学中退火算法的最新模拟方法，大家看看拉。(Materials Science in the latest simulation annealing algorithm, we look at Latin America.)
- 2010-06-07 16:40:38下载
- 积分：1
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23_52
用MATLAB语言编制定的用于流体计算和传热的程序(Compiled with the MATLAB language for set procedures for fluid and heat transfer calculations)
- 2010-06-20 23:48:35下载
- 积分：1
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Huffman
基于MATLAB的例程 实现HUFFMAN编码算法 不定长编码 基于不同符号的概率分布(Variable-length coding based on the probability distribution of different symbols based on MATLAB routines to achieve HUFFMAN coding algorithm)
- 2014-11-03 16:35:50下载
- 积分：1
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plateloss
finite difference scheme for the thin plate equation with loss
- 2014-11-11 08:52:15下载
- 积分：1
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cdma2
在简要介绍MATLAB语言的基础上，对使用MATLAB语言仿真的CDMA通信系统进行描述。(in MATLAB briefed on the basis of on the use of MATLAB simulation of CDMA communications system description.)
- 2007-04-28 10:12:54下载
- 积分：1
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of14
this simulation script set allows for an OFDM transmission to be
simulated.
- 2011-07-30 23:37:39下载
- 积分：1
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Planck2.m
A matlab function to calculate the Planck function
- 2014-11-18 03:34:06下载
- 积分：1
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DataDistributionFunctionEstimationMethodAndItsAppl
讨论了区间数据分布函数估计的方法及其应用(Discussed the range of data distribution function estimation method and its application)
- 2009-02-24 11:13:24下载
- 积分：1
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Securing-at-the-Physical-Layer
通过物理层技术的设计实现无线通信的保密。(Securing Wireless Communications at the Physical layer)
- 2011-11-14 10:19:34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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