spyeffection11

三维Lee滤波，对三维SAR图像和超声波图像的相干斑进行抑制(3D Lee filter, three-dimensional SAR images and ultrasound images to suppress the speckle)

温度场的数值模拟程序，主要是应用matlab编程实现(temperature field of numerical simulation program, is the application of Matlab programming)

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.)

Good paper on TDOA. I hope this will help you all !!!

对8PSK完美建模，其中通过改变码元速率和载波频率，再计算相应的环路滤波器的参数，即可实现多种QPSK模型的解调，且该模型可通过SYSTEM generator进行量化，从而生成ISE能直接使用的HDL代码。(Perfect modeling of 8PSK, wherein by changing the symbol rate and carrier frequency, and calculate the corresponding parameters of the loop filter, to achieve a variety of demodulated QPSK model, and the model can be quantified by SYSTEM generator, thereby generating ISE HDL code can be used directly.)

本资源主要对矩阵分解中的LU分解、LDL’分解、乔列斯基分解，以及无约束最优化领域中的最速下降法、牛顿法、拟牛顿法的原理、步骤和算法进行了简要介绍，并对各种方法进行了Matlab编程实验，得到了较好的结果。 本资源包含了《矩阵分解及无约束最优化方法的原理和应用简介》文档以及其中用到的全部Matlab程序，非常适合初学者学习与研究。(The resources are mainly in the matrix decomposition LU decomposition, LDL decomposition, Cholesky decomposition, and unconstrained optimization field steepest descent method, Newton s method, the principle of quasi-Newton methods, procedures and algorithms are briefly introduced, and various methods of Matlab programming experiment, get a better result. This resource contains a matrix decomposition and unconstrained optimization methods Introduction to the principles and applications which uses all the documents and Matlab program, ideal for beginners learning and research.)

基于matlab的数字图像压缩编码基于matlab的数字图像压缩编码(Matlab-based digital image compression coding)

PTOTEUS中所有元件中英文对照表，有需要的朋友可以下载使用(PTOTEUS all the components in bilingual form)

data compression using linear vector quantizer

采用了小波去噪的思想，music高阶谱分析算法，基于互功率谱的时延估计。( Using wavelet denoising thought, music higher order spectral analysis algorithm, Based on the time delay estimation of power spectrum.)