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《数值线性代数》（Lloyd N.Trefethen & David Bau, III）课本算法matlab源码("Numerical Linear Algebra" (Lloyd N.Trefethen & David Bau, III) textbook algorithm matlab source code)

考虑单独变量之间的相关性，将其变成扩展变量，再用留一法进行数据处理，最后用SVM进行回归(Consider the correlation between individual variables, to expand into the variable, and then leave one for data processing, and finally with SVM regression)

图像检索的 matlab代码 方法常见(Select the image bitmap file you wish to search for in the databse Press Select. Press Search.)

数字信号的传输：1、实现滚降系数分别为0，0.5，1时信号时域频域和功率谱密度以及眼图的波形，并比较异同。 2、对(2/4/8)PSK,DPSK通信系统进行蒙特卡罗仿真，通过功率谱密度、误比特率来比较他们的性能(采用最佳接收方式)。 (Digital signal transmission: 1, to achieve roll-off coefficients were 0,0.5,1 time domain when the signal frequency and power spectral density, as well as eye-diagram of the waveform, and compare the similarities and differences. 2, (2/4/8) PSK, DPSK communication system, Monte Carlo simulation, through the power spectral density, bit error rate to compare their performance (to adopt the best way to receive).)

LSVM : Langrangian Support Vector Machine algorithm LSVM solves a support vector machine problem using an iterative algorithm inspired by an augmented Lagrangian formulation

数值积分方法练习与函数调用：利用ode23或ode45求解线性时不变系统微分方程 =Ay(t)并绘出y（t）的曲线，式中 =0， =4 (Using ode45 ode23 or to solve the linear differential equation when the same system = Ay (t) and draw y (t) curve, type = 0, = 4 )

说明：  《模糊系统与模糊控制教程》共31章，内容包括模糊数学与模糊逻辑中一些对于模糊系统理论有用的概念和原理，模糊系统的各组成部分，设计模糊系统的四种方法，模糊控制与非自适应模糊控制方法，以及若干不属于本书主体结构但很重要的专题等内容。(Book a course of fuzzy systems and fuzzy control, a total of 31 chapters, including some of the fuzzy mathematics and fuzzy logic for useful concepts and principles of fuzzy system theory, fuzzy system of each component, design the four methods of fuzzy system, fuzzy control with the adaptive fuzzy control method, and some do not belong to book the main structure but very important project, etc.)

MMT is a Matlab toolbox implementing the multi-task Lasso models, including: (i) the Lasso (ii) the standard multi-task Lasso, i.e. the group Lasso (iii) the structured input-output multi-task Lasso, a.k.a. the two-graph guided multi-task Lasso proposed in [1]. The last case (iii) subsumes the special cases: tree-guided and the feature-graph guided multi-task Lasso. The core optimization algorithm for solving this model is developed in C to enhance greater computational efficiency. In particular, current scalability of the coefficient matrix that has been tested for MMT is 104*104! The structured input-output multi-task Lasso model is well-suited for addressing the expression quantitative trait loci (eQTL) mapping problems which are of the intrinsic high-dimensional nature. Details can be found in [1].

matlab code neural network rbf

多种esprit算法的对比仿真分析，通过对比，可以知道哪种算法最适合(Contrast variety esprit algorithm simulation analysis, by contrast, can know what the most appropriate algorithm)