Least-square-method

Solve the standard basis pursuit program using a primal-dual algorithm,The key code of GBP is provided by Justin Romberg Reference: E. Candes and J. Romberg, “l1-Magic: Recovery of Sparse Signals via Convex Programming,” 2005.

digital modulation System will automatically delete the directory of debug and release, so please do not put files on these two directory.

第一步是计算输人信号单边功率谱密度（ESD）。使用快 ％速傅里叶（FFr）算法将信号从时域转换到频域。因为FFr算法的输出是离散谱，而这 ％里我们需要的是连续谱，因此需要引人不同的比例因子来实现从离散谱到连续谱的转换。 ％在第二步中，我们利用迭代算法计算出相对于特定阂值的ESD的最高和最低频率，从而 ％估算出被检测信号所占用的带宽。这种算法同时适用于基带信号和已调制信号。最后， ％在第三步中，我们给出了输出图形的原代码。(The first step is calculating the input signal unilateral power spectral density (ESD). The use of fast Fourier speed (FFr) algorithm for the signal conversion from time domain to frequency domain. FFR algorithm because the output is a discrete spectrum, which we need is a continuous spectrum, so the need for food of different scale factor to achieve from the discrete spectrum to continuous spectrum conversion. In the second step, we use iterative algorithm to calculate a specific threshold in relation to the ESD of the highest and lowest frequency, thus estimated to be occupied by the signal detection bandwidth. This algorithm applies to both baseband signal and modulation signals. Finally, in the third step, we give the graphical output of the original code.)

MATLAB例程无功补偿器statcom的仿真图，运行良好(MATLAB routines reactive power compensator statcom simulation map, well)

王正林的《精通matlab科学计算》 的全部源码，学习matlab的好资料。 (WangZhengLin "proficient in matlab scientific computing" all the source code, good material for learning the matlab)

白志东给出的对于高维数据两总体均值检验的程序，可以参考下(high dimension)

ls-svm理论算法详解,原作者论文原著(ls-svm Detailed theoretical algorithm, the original author of the paper)

pattern classification homework 3

有序样品的最优分割的算法及其在MATLAB中的实现(Segmentation of sequence data in Matlab)

模拟退火算法——组合优化 模拟退火算法主要用于解决组和优化问题，它是模拟物理中晶体物质的退火过程而开发的一种优化算法。在对固体物质进行模拟退火处理时，通常先将它加温熔化，使其中的粒子可自由运动，然后随着温度的逐渐下降，粒子也逐渐形成了低能态的晶格。若在凝结点附近的温度下降速率足够慢，则固体物质一定会形成最低能态的基态。 对于组合优化问题来说，它也有这样的类似过程。组合优化问题解空间中的每一点都代表一个具有不同目标函数值的解。所谓优化，就是在解空间中寻找目标函数最小（大）解的过程。若把目标函数看成能量函数，某一控制参数视为温度 T，解空间当作形态空间，那么寻找基态的过程也就是求目标函数极小值的优化过程。 (Simulated annealing algorithm- combinatorial optimization Simulated annealing algorithm used to solve optimization problems and the group, it is the physical simulation of the crystal material in the annealing process and the development of an optimization algorithm. Solid substances in the simulated annealing process, it is usually heated it first melts, so that the particles are free to exercise, then gradually decreased as the temperature of the particles gradually formed a lower state of the lattice. If the temperature drops near the condensation rate slow enough, the solids will form the lowest energy state of the ground state. For combinatorial optimization problems, it also has such a similar process. Combinatorial optimization problem the solution space of each point represents a different objective function value of the solution. The so-called optimization, is in the solution space to find the minimum objective function (large) solution process. If the objective function a)