my_clustering

用matlab实现smith圆图的基本思路和指导。(Using matlab circle diagram smith realize the basic ideas and guidance.)

说明：  详细介绍了matlab图像处理函数，并总结了函数的适用情况。实验问题详细的答案讲解。(Details of the matlab image processing function, and summarizes the functions of the application. Detailed answers to explain the experimental problem.)

本次实验是无线楼宇数据传输仿真，即在楼内实现点对点的无线数据通信，需要获得的关键是两点之间的距离和楼层衰减。通过了解914M的楼宇通信特性，建立楼宇数据通信系统的仿真模型，采用无线收发芯片NRF905,实现楼宇内的数据通信仿真分析。 (this experiment is building wireless data transmission simulation, in the building of peer-to-peer wireless data communications, need, the key is the distance between two points and the floor attenuation. 914 M by understanding the communication characteristics of the buildings, the establishment of building data communications system simulation models, adoption of wireless transceiver chip NRF905 achieve buildings on the simulation analysis of data communications.)

matlab 函数检索表 matlab 函数大全(matlab function)

所有数据融合（包括dmp输出数据，如加速度计数据， 陀螺仪，6轴四元数和内部磁力计数据）通过7态13测量 EKF（扩展卡尔曼滤波器）/无限卡尔曼滤波器（UKF）/ Cubature卡尔曼滤波器（CKF）算法/ 平方根均方卡尔曼滤波器（SRCKF）算法。(All data fusion (including the data of dmp output, such as the accelerometer data, gyroscope, 6-axis quaternion and internal magnetometer data) via a 7-state, 13-mesurement EKF(Extended Kalman filter)/Unscented Kalman Filter(UKF)/Cubature Kalman Filters (CKF) Algorithm/ Square-Root Cubature Kalman Filters (SRCKF) Algorithm.)

一个MATLAB报告，是电力系统负荷预测方面的(Report of a communication theory, written in great detail, is what MATLAB side)

An implementation of Unscented Kalman Filter for nonlinear state estimation. (Nonlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded formulation for nonlinear state estimation. However, it may cause significant error for highly nonlinear systems because of the propagation of uncertainty through the nonlinear system. The Unscented Kalman Filter (UKF) is a novel development in the field. The idea is to produce several sampling points (Sigma points) around the current state estimate based on its covariance. Then, propagating these points through the nonlinear map to get more accurate estimation of the mean and covariance of the mapping results. In this way, it avoids the need to calculate the Jacobian, hence incurs only the similar computation load as the EKF. For tutorial purpose, this code implements a simplified version of UKF formulation, where we assume both the process and measurement noises are additive to avoid augment of state and a)

svpwm of open loop three level inverter

matlab code for hmm understanding

设计学习手记对matlab的入门具有极其重要作用，因此本人强烈推荐(good book)