matlab_faction

huffman coding and huffman decoding

pb的小例子,是PB中的游标的经品,实现查询功能.(pb small examples, PB cursor on the goods and realize the inquiry.)

This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with standard update of the covariance matrix P. The covariance matrix reflects the uncertainties of the predictions. To improve the numerical stability Potter developed a square root update (fcn_KF_SRP) of the covariance matrix P. Another version is the square root covariance update via triangularization (fcn_KF_SRT). This file generates a model. Then the three Kalman filters perform an estimation of the model parameter. At the end the results are compared. Sources: Simon, D. (2006): Optimal state estimation Kaminski, P. (1971): Discrete Square Root Filtering: A Survey of Current Techniques Golub, G. (1996): Matrix Computations

共振解调的过程如下：首先对采集到的信号进行傅里叶变换，然后利用传感器自身的谐振频率进行分析，对滤波后的信号进行包络，包络以后去除了高频部分，得到包络信号，再对改进的包络信号进一步进行低通滤波，最后对最终得到的信号进行傅立叶变换求其频谱图。共振解调的原理及其过程可以用图2 来进行表述。(The process of resonance demodulation is as follows: First, Fourier transform is performed on the collected signal, and then the resonance frequency of the sensor is used for analysis. The filtered signal is enveloped, and the high frequency part is removed after enveloping to obtain an envelope. The signal is further subjected to low-pass filtering on the improved envelope signal. Finally, the spectrum of the resulting signal is Fourier-transformed. The principle of resonant demodulation and its process can be expressed in Figure 2.)

E-book for WiMAX_Technology

基于MATLAB的锁相环程序，内附详细说明(PLL based on MATLAB program, like a friend to study a)

this code is about hough transform

A complete basic matlab tutorial

PLS GIVE MATLAB CODING .......

这是在matlab的基础上开发出的pid控制器源代码(It is developed on the basis of matlab pid controller source code)