LMF-ambg

plot an ellipse using matlab

model Simulink of arduino

matlab阵列信号处理工具箱DBT,版本2.20,阵列信号处理必备(Directory stored in the source wavelet coding, including the commonly used wavelet transform procedures for)

插值计算 底质遥感反射率 水面之下遥感反射率(interp1 bottom reflectance underwater irradaince reflectance)

數位訊號處理 在matlab下進行模擬的程式碼教學~好書推薦(Digital signal processing carried out under simulated in matlab code teaching ~ Good Books Recommended)

用matlab实现的boosts开关变换器的仿真图，一共四幅图，对于学习非线性电路的同学有用(Matlab achieved by switching converter boosts the simulation map, a total of four maps, non-linear circuit for the students to learn useful)

Three level voltage source inverter with RL load

实现脉冲消隐以在通信系统去除较大干扰,保证误码率性能(Realization of pulse blanking to remove larger interference in communication system, guaranting the bit error rate performance)

基于Haar wavelet的小波方法实现图像压缩，并附有图像实例(Haar wavelet-based method of implementation of wavelet image compression, together with examples of images)

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)