InstallGuide

kground: Abnormally high CSF 3-OMD occurs frequently for RLS patients indicating either increased L-dopa synthesis, limitations in L-dopa decarboxylation or increased MAT/COMT activity, or some combination of these. Increased tyrosine hydroxylase activity was found on both the RLS autopsy and the rodent iron-deprivation model of RLS, suggesting increased DA synthesis in RLS. We, therefore, hypothesized elevated 3-OMD in RLS results from increased DA synthesis and that this should occur accordingly with increased HVA. It would then also reflect both the more severe iron insufficiency pathology of RLS and greater clinical severity, shown by the objective measure of PLMS/hr. Methods: Patients off RLS medications and matched controls had

可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择，主要用于神经网络(Reversible Jump MCMC Bayesian Model Selection This demo demonstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.)

特徵粹取（feature extraction）是特徵選取（feature selection）的延伸，簡單地說，我們希望將資料群由高維度的空間中投影到低維度的空間，因此，我們必須找出一組基底向量（base）來進行線性座標轉換，使得轉換後的座標，能夠符合某一些特性。 我們可以將特徵粹取分成「包含類別資訊」和「不包含類別資訊」兩大類。包含類別資訊指的是我們已經知道哪些資料分別歸屬於哪一類；而不包含類別資訊的特徵粹取則適用於我們不知道手上的資料點分別該歸屬於哪一類，甚至連該劃分成幾類都不知道的情況。對於這兩大類資料，可以分述如下： 對於「不包含類別資訊」的資料，我們通常使用「主要分量分析」（principal component analysis），簡稱 PCA。 (Cuiqu features (feature extraction) is feature selection (feature selection) extension, simply put, we want to base the projection data the high-dimensional space to low-dimensional space, so we have to find a set of basis vectors ( base) to the linear coordinate conversion, so that after the coordinate conversion, can meet a number of features. We can feature Cuiqu into " category contains information" and " does not contain a category of information," two categories. Contains categories of information refers to what we already know what kind of information are attributed to Cuiqu features include categories of information are not applicable to information we do not know the points are in the hands of the home in which category, and even that is divided into several class do not know the situation. For these two categories of information, can be divided as follows: For information " does not include the categories of information" , we usually use the " )

对测试信号进行emd 分解，计算其在各个频带中的能量分布(The EMD of the test signal is decomposed, and the energy distribution in each frequency band is calculated)

说明：  空时自适应信号处理，用于合成孔径雷达东目标检测，ACP，AEP方法(Space time adaptive signal processing, used for SAR East target detection, ACP, AEP methods)

matlab实现一些模式识别的基础算法，方便初学者学习和实践(matlab the basis of pattern recognition algorithm, easy for beginners to learn and practice)

64QAM基带系统接收机matlab代码：添加AWGN噪声，进行接收端匹配滤波器，8倍下采样，解调信号。(64QAM baseband system receiver matlab code: add AWGN noise, matched filter receiving end, eight times the down-sampling, the demodulated signal.)

离散系统的MATLAB实现。学习利用matlab求解系统频率响应的方法；学习利用matlab求解系统输出响应的方法； (MATLAB realization of discrete systems. Learning methods for solving systems using matlab frequency response learning methods for solving systems using matlab output response )

用music方法测量目标角，此方法在雷达定位中得到验证可行。(The music method to scan the actual target angle )

关于主成分分析(PCA)的MATLAB程序(MATLAB)