SimulationExperimentWithDodgingHandicapsByRobot

希望对大家有用，是关于matlab的视频(It is useful ,i think)

说明：  传热的数值算法，包括matlab动态显示(numerical method of heat transfer problem.)

the file is for light

Emotion finder matlab code and with some images works fine

《MATLAB 神经网络30个案例分析》源程序和数据，给需要的人。(MATLAB neural network analysis of 30 cases of source and data to the need.)

another code from the sample code category

仿真了电力线信道与电力线通信中的窄带噪声(The simulation of the power line and the power line communication channel narrowband noise)

光学微球腔尺寸参数与相对折射率的关系仿真程序(The simulation program on Optical microsphere cavity dimension parameters and the refractive )

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.)

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