cedif

说明：   此函数用于研究Mallet算法及滤波器设计 此函数用于消噪处理 分解的高频系数采用db9较好,即它的消失矩较大 分解的有用信号小波高频系数基本趋于零 对于噪声信号高频分解系数很大，便于阈值消噪处理(this function for research Mallet filter algorithm design and function for Denoising decomposition of high-frequency coefficients Terminal better that it's vanishing moments larger decomposition of useful signal, high-frequency coefficients tends to zero for high-frequency signal noise decomposition coefficient great ease threshold Denoising)

Kalman filter examples, kalman_update

MT8880应用实例合集，总共有十余个例子(MT8880 Application collection, a total of more than ten examples of)

一篇很好的文章，建议大家看看,基于反馈的图像检索算法优化(a good paper worth to read)

说明：  使用动态矩阵预测控制模型对蒸发换热器进行控制(DMC heatexchanger)

检测直线的hough变换，峰值检测，线检测和链接的用matlab实现 (line detection hough transform, peak detector, linear detection and link with the realization of Matlab)

创建连续系统模型，为初学者提供一个参考，希望有所帮助(Creating Continuous-Time Models)

MIMO OFDM matlab仿真,考虑雨衰 阴影 和多径影响，包含收发两个客户端的链路级通信程序,借鉴了主成分分析算法（PCA），数据模型归一化，模态振动，基于负熵最大的独立分量分析。( MIMO OFDM matlab simulation, Consider shadow rain attenuation and multipath effects Contains two clients receive link-level communications program, It draws on principal component analysis algorithm (PCA), Normalized data model, modal vibration, Based on negative entropy largest independent component analysis.)

关于室内定位的算法，该算法是在MATLAB环境下实现的程序。(Positioning on the interior of the algorithm, which are in the MATLAB environment realize procedure.)

Start with the runlocalization track.m which is the entrance function to your lab. This function reads two les determined by simoutle and maple input arguments which contain information about sensor readings and the map of the environment respectively, runs a loop for all the sensor readings and calls the ekf localize.m to perform one iteration of EKF localization on the readings and plots the estimation(red)/ground truth(green) and odometry(blue) information.(This lab consists of two parts: 1. A preparatory case study with a standard Kalman lter where you learn more about the behavior of the Kalman lter. Very little extra code is needed. 2. The main lab 1 problem in which you need to complete an implementation of an Extended Kalman lter based robot localization.)