gaotonglvboqi

信号功率谱分析，方法三、四，已在此详细编写(Signal power spectral analysis, methods, three, four, has been prepared in detail here)

详细讲解信号处理的pdf,里面包含了FFT，小波，希尔伯特-黄变换等内容，是信号处理方面很好的参考资料(Explain in detail the signal processing pdf, which contains the FFT, wavelet, Hilbert- Huang Transform, etc., is a good reference for signal processing, data)

详细讲解了小波变换原理，运用。matlab的小波工具箱等。对初学者有较大的帮助。(Elaborate on the principles of wavelet transform, apply. matlab wavelet toolbox and so on. For beginners, a greater help.)

ISAR成像RD算法，设定目标点数为74时的仿真程序(RD SAR imaging algorithm, set a target of 74 points when the simulation program)

基于MATLAB的mimo系统正交频分多址ofdm，空时编码stbc代码,用于mimo系统仿真(Based on MATLAB mimo system orthogonal frequency-division multiple access ofdm, space-time coding stbc codes for mimo system simulation)

针对二维矩形条带装箱问题提出了一种启发式布局算法，即底部左齐择优匹配算法（lowest—level left align bestfit，简称LLABF）．LLABF算法遵循最佳匹配优先原则，该原则综合考虑完全匹配优先、宽度匹配优先、高度匹配优先、组合宽度匹配优先及可装入优先等启发式规则．与BL（bottom-left），IBL（improved-bottom-left）与BLF（bottom—left-fill）等启发算法不同的是，LLABF能够在矩形装入过程中自动选择与可装区域匹配的下一个待装矩形．计算结果表明，LLABF结合遗传算法（genetie algorithm,简称GA）解决二维条带装箱问题更加有效．(A heuristic placement algorithm for two-dimensional rectangular strip packing problem is proposed, which is called bottom-level left align best fit algorithm (LLABF). Different from BL (bottom-left), IBL (improved-bottom-left) and BLF (bottom-left-fill) heuristic algorithms, LLABF can automatically select the next rectangle to be loaded that matches the mountable region during the rectangular loading process. Genetie algorithm (GA) is more effective to solve the two-dimensional strip packing problem.)

matlab实验fir数字滤波器设计与软件实现(fir digital filter design and software implementation )

双孤子模拟程序，对光纤中的孤子进行仿真，实验结果较理想(Two-soliton simulation program, the soliton fiber simulation, more satisfactory results)

对车辆运动及动力学进行建模并同过MPC算法实现控制器设计(modeling for the vehicle motion and dynamics and the controller is designed with the MPC algorithm.)

kass的经典snake的matlab实现，用于图像边缘检测分割等(Kass snake classic realize the matlab for image segmentation, such as edge detection)