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ora
ora code is usefull apart with the codes sent above
- 2010-11-16 21:13:33下载
- 积分：1
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DOA
经典DOA估计算法matlab仿真，延迟相加，MUSIC，ESPRIT。有详细注释，步骤清晰，适合初学者学习(Classic DOA estimation algorithm matlab simulation, delayed addition, MUSIC, ESPRIT. There are detailed notes, clear steps for beginners to learn)
- 2013-12-18 10:41:40下载
- 积分：1
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EWT20140424
Empirical Wavelet Transform
- 2015-04-11 21:54:31下载
- 积分：1
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speechrecognitionUsingLPCandBOF
Speech recognition using LPC and Bank of Filter method, operated in Matlab(Speech recognition using LPC and Bank of Filter method,operated in Matlab)
- 2010-06-22 00:39:03下载
- 积分：1
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trackingPtrajectoryPtime
采用matlab语言编写，对运动中的人像进行跟踪，显示其运动轨迹，并可以计算人像通过特定位置时的时间（帧）(Matlab language to track the movement portrait display its trajectory, and can calculate the time when the portrait through a specific position (frame))
- 2013-04-19 17:06:53下载
- 积分：1
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Basic-Interface
Bookmark
//
// ImageAndTextCell.h
// SimpleTreeController
//
// Created by System Administrator on 7/13/11.
// Copyright 2011 __MyCompanyName__. All rights reserved.
//
- 2014-01-21 17:47:36下载
- 积分：1
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gp
说明： MATLAB实现股票价格预测 源程序代码(MATLAB source code to achieve stock price prediction)
- 2016-11-01 20:19:25下载
- 积分：1
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AQMC_stage2
1.AQMC较正的matlab源代码，适用于各种DAC及正交调制器引起的IQ不平衡较正(Than positive 1.AQMC matlab source code, suitable for all kinds caused by the DAC and quadrature modulator IQ imbalance correction)
- 2021-04-23 15:28:47下载
- 积分：1
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ENEE634_report1
Least Mean Square algorithm
- 2009-12-29 00:53:38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
