cycloconverter_single_phase_Step_up

An Introduction to MATLAB and SIMULINK

pid fun in matlab codes

说明：  This is the worked example of using MOESP, the example found in: Subspace Methods for System Identification, written by: Tohru Katayama , "Springer 2005", page 160 example 6.6.

一个SOFC中燃烧室的模型搭建，包括m函数，simulink模型(a burner model for solid oxide fuel cells(SOFＣ),it include m.file, and simulink model )

阵列信号处理中的空时自适应处理算法的MATLAB实现代码(MATLAB Implementation Code of Space-Time Adaptive Processing Algorithms in Array Signal Processing)

Encryption algorithms are becoming more necessary to ensure data is securely transmitted over insecure communication channels. FOX is a recently developed algorithm and its structure is based on the already proven IDEA (International Data Encryption Algorithm) cipher. FOX is a symmetric (private key) block cipher. Its top-level structure uses the Lai-Massey scheme and the round functions used in the scheme are substitution permutation networks (SPN). Its flexibility lies in the fact that it can be efficiently implemented in hardware and software. We report some of the first results of implementing the cipher on an FPGA

覆盖了全书的信号与线性系统、随机过程、模拟调制、模拟数字转换、基带数字传输、带限信道的数字传输、载波调制的数字传输、信道容量和编码、扩频通信系统以及数字调制方法的SIMULINK仿真的 源代码(Book covers the signal and linear systems, stochastic processes, analog modulation, analog-to-digital conversion, base-band digital transmission, band-limited digital transmission channel, the digital transmission carrier modulation, channel capacity and coding, spread spectrum communication systems, and digital modulation SIMULINK simulation method source code)

说明：  此代码描述的是跳频系统在不采用两路分集的情况下的性能仿真，主要也是对误码率的仿真函数(This code describes the frequency-hopping system without two-way diversity in cases where performance simulation, is largely a function of the BER simulation)

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

利用匹配追踪对信号进行稀疏分解，得到其稀疏表示形式(The use of matching pursuit for sparse decomposition of the signals, by their sparse representation)