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说明：  matlab均值粒子群算法源程序，个人编写，得到满意的结果，老师说不错(Mean particle swarm algorithm matlab source code, personal preparation, with satisfactory results, the teacher is quite good)

说明：  在MATLAB下做的开关电源设计仿真研究(Done under the MATLAB simulation of switching power supply design)

code for leach in matlab

matlab程序非线性优化设计方法时下流行的关于非线性规划的源程序,包括SQP方法、乘子法程序、二次规划、非线性最小二乘法、共轭梯度法、拟牛顿法、线搜索技术、信赖域方法、最速下降法与牛顿法等(matlab program nonlinear optimization design method popular on nonlinear programming source code, including the SQP method, the multiplier method procedures, quadratic programming, nonlinear least squares method, the conjugate gradient method, quasi-Newton method, the linesearch technology, trust region methods, the steepest descent method and Newton method)

说明：  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社，2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性，首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次，它允许指定不同的推理过程，如精确推理和期望传播(EP)。第三，它允许指定似然函数，如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的，允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)

说明：  一些用matlab编写的经典遗传算法算例。可以用于解决许多优化问题(using Matlab to prepare some of the classic examples of genetic algorithm. Many can be used to solve optimization problems)

说明：  Matlab下美军F16战斗机的非线性模型(Nonlinear F-16 Fighter Model)

This is very important code for image segmentation comparisons, this code calculates RI, GCE and VI for segmentation comparisons.

几种准正交空时码性能的比较，分析不同编码方式的优劣( Code Performance comparison of several quasi-orthogonal space time, analyze the pros and cons of different encoding)

用互相关法求相对剩余静校正量；并用时差统计法或相关函数统计法分离，最后可求出记录道的绝对剩余静校正量。(Using cross correlation method the relative residual statics and separated by the difference method or statistical correlation function statistics of the last track can be obtained an absolute residual statics.)