MULTILEVELTest22

说明：  Matlab课件，简单实用，对于写论文和做仿真的同学很有用(Matlab)

说明：  simulink工具箱的入门PPT讲解，有附带m文件，强烈推荐(simulink toolbox PPT talks, with m files are strongly recommended)

粗糙集的相关文档，自己搜集的资料看，供大家学习(Related Documentation rough set, they collect information look for everyone to learn)

为了提高移动通信系统中数据传输的有效性能,降低GMSK调制系统的误码率. 首先对GMSK调制系统进行分析,得到不同BT值GMSK调制的移动通信系统误码率和带宽的关系.通过引入具有纠错性能的编码技术,降低信息传输的误码率,提高系统的有效性. 本文给出了引入编码技术的GMSK调制系统的仿真模型,仿真结果表明,在相同的信噪比下,系统的误码率降低了1～2dB.(This paper mainly intends to improve the performance of the communication system and decrease the error bit rate of the information. First , the GMSKmodulation system was analyzed , and the relation of the BER and bandwidth in the different BT value was obtained. By introducing the encoding technology , the error bit rate of the information was lowered so that the performance of systemwas improved. This paper presents a simulated model . The results show that the BER of the system in the same SNR can lower 1 to 2 dB.)

DF加中继基于门限的中继选择，适合基础者学习。(DF plus relay threshold-based relay selection, suitable foundation to learn.)

simon hykin problem 3.40

Transformation from ab to dq and dq to ab

肌电功率谱，积分肌电等；不含预处理过程。(sEMG power spectrum, integral EMG and so on; no pretreatment process.)

Exercices of Graphs, not resolves. SOme explanaitons

Robust Non-negative Dictionary Learning for Visual Tracking The provided codes could be either embedded into the benchmark framework of paper Online Object Tracking: A Benchmark (CVPR2013) (You can find details here: http://visual-tracking.net/) or run on individual sequence. To run the benchmark, just put the entire folder into the /trackers folder in the benchmark code base, and modify the configTrackers.m in util folder. DLT gets an AUC of 0.436, which ranks 5th among 26 in the benchmark by 19/03/2014. We don t tune parameters for single sequence in this case, all the parameters are stored in trackparam_DLT.m. To run on individual video, you need to modify the dataPath and title in run_individual.m. If you run MATLAB version after 2012, and have a CUDA compatible GPU installed, you may enjoy the fast computation speed by GPU, just set useGPU to true in trackparam_DLT.m and run_individual.m!