sa_Ex7_5

mix 快速图象分割 内含4个Matlab应用程序

说明：  一种基于JAKE模型的改进的瑞利衰落信道仿真(A model of the Rayleigh fading channel simulation)

K-近邻支持向量机回归，工具箱，全程Matlab(K-Support Vector machine Matlab， This function process the SVM regression model using a linear epsilon insensitive cost)

water tale sampler aaze.ir

通过运用粒子算法来求出一个复杂的函数的最优解，并运用3维仿真方法将它很好的仿真出来！(Particles through the use of a complex algorithm to find the optimal solution function and the use of three-dimensional simulation of a good simulation of it out!)

自己编的，利用MATLAB进行DPSK和PSK编码，可用于数字通信的课程学习中。(Own, and the use of MATLAB for DPSK and PSK encoding, digital communication can be used to study in the curriculum.)

m/m/m排队模型的仿真，很好的资料！！(m/m/m queuing model of the simulation, very good information! !)

Code to operate with Midlin equation to extract inharmonic frequencies

提供了34个无约束优化算法的测试函数，用于测试算法的有效性和准确性(Provides 34 unconstrained optimization test functions for testing the validity and accuracy of the algorithm)

这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of pseudo-inputs or basis vectors for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the pseudo-inputs , with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. spgp_lik is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using spgp_pred . I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing the hyperparameters sensibly. Its current limitations are that 1) it is slow and memory intensive for high dimensional data sets 2) it is heavi)