MATLABdemos

OFDM系统在AWGN和多径信道下的仿真。包括cyclic prefix,pilot,channel estimation，误比特率曲线以及实验报告（英文）(OFDM system in AWGN and multipath channel simulation. Including the cyclic prefix, pilot, channel estimation, bit error rate curve and the experimental report (English))

A_Star算法路径规划演示 包括完整的程序和仿真结果，可以运行(A_Star path planning algorithm demo includes a complete program and simulation results, you can run crorrect)

通信的数字化是它能与计算机技术和数字信号处理技术相结合的基础，而实现通信数字化的前提是信源能提供的各种用于传递的消息，例如语音、图像、数据、文字等都必须以数字化形式表示。而信源编码是数字通信系统中的重要组成部分，他是保证信号有效传输的一种重要方式。霍夫曼编码依据字符出现的概率来构造异字头的平均长度最短的码字，有时称之为最佳编码，其优越的性能被广泛使用在数字通信系统中。霍夫曼编码已经成为数据压缩的灵魂算法。本文介绍了无失真编码算法的构造，霍夫曼编码的规则和特点，同时分析了对信源进行优化的方法，最后通过MATLAB仿真来讨论比较二元霍夫曼编码、三元霍夫曼编码以及信源扩展编码的效率，来实现霍夫曼码的优化构造。(The digital communication is it can and computer technology and digital signal processing technology in combination of the base, and realize the digital communication is the premise of source can provide all kinds of used to deliver news, such as voice, video and data and text must take the digital form said. And the source coding digital communication system is the important component, he is to ensure the effective transmission signal is an important way. Huffman coding based on the probability of characters appear to construct different "the average length of the shortest code words, sometimes called the best coding, superior performance is widely used in digital communication system. Huffman coding has become the soul of data compression algorithm. This paper introduces the structure of the encoding algorithm without distortion, Huffman coding rules and characteristics, and analysis of the source of the optimization method, and finally by MATLAB simulation to discuss compares two yu)

谱减法实例，已经做过实验，可以运行，只要载入数据即可(Spectral subtraction instance, has done the experiment, you can run, as long as the data can be loaded)

Commande repère tournant de la MAS

Introduction to Random Signals and Applied Kalman Filtering

Decoding Jpeg image in matlab programm

说明：  机床时频域信号特征提取，包括均方根值、峰值、峰值因子、峭度因子、脉冲因子、裕度系数、波形因子、功率谱密度、频率方差、均方频率(Eigenvalue extraction)

In many applications, such as biomedical engineering, it is often required to obtain specific periodic source signals. In this paper, we propose a two-stage based approach for extracting periodic signals. At the first stage, the autocorrelation property of the desired source signal is exploited to roughly extract the desired source signal. At the second stage, the extracted signal is further processed as cleanly as possible, based on the higher-order statistics. Simulations on artificially generated data and real-world ECG data have showed its better performance, compared with many existing extraction algorithms.

Application of Parallel Redundancy in a Wi-Fibased WNCS using OPNET