lpcsyn

说明：  根据需要输入模糊参数，生成相应的模糊图像，并对模糊图像进行恢复，验证运动模糊图像的恢复算法(Input fuzzy parameters needed to generate the corresponding blurred image，and restore the blurred image to authenticate the algorithm)

多传感器数据融合的梯度下降法。方法较为简单，代码基本可以实现滚转角与俯仰角的解算，需要再调参数会更精确(Multi-sensor data fusion gradient descent. The method is simple, basic code can roll angle and pitch angle of the solver, you need to re-tune the parameters would be more accurate)

PV系统阴影遮挡模拟源代码，2013a metlab开发(the code for simulation of the shaded PV system)

三相桥双极性PWM控制Simulink仿真，叠加一些其他信号，另加一滤波器观看PWM经过低通滤波后的波形，适合电力电子初学者(Three-phase bridge bipolar PWM control Simulink simulation, superimposed a number of other signals, plus a watch PWM filter through after the low-pass wave filter for power electronics for beginners)

这个程序是关于图像的方针，直方图方法； 画出直方图。(This program is about the principle of the image, histogram method draw histogram.)

车灯线光源的优化设计方案 (Headlight design optimization)

方向图 包括 线阵 面阵 圆阵 有详细注释(Pattern including circular array of linear surface array detailed notes)

根据毕奥-萨伐尔定律推导了运动电荷产生的磁感应强度的公式，用曲面显示运动电荷产生的磁感应强度的分布规律。 通电线段的磁感应强度公式 磁感应线的半径形成等比数列，精确显示了二维磁感应线(Derivation based on the Biot- Savart law of magnetic induction generated by the moving charge formula, the distribution of magnetic induction surface display generated by the moving charge.)

粒子群算法，为最优化问题的一种解法，调用方法和参数包含在主文件里。使用matlab实现(Particle swarm optimization for optimization problems, a solution, calling the method and parameters included in the main file. Using matlab to achieve)

The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files. - space_time_coding.m (perform space time coding) - subspace_channel_estimation_STBC.m (channel estimation) - one_shot.m (show an example) To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window. Reference: [1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202 - 217(The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files. - space_time_coding.m (perform space time coding) - subspace_channel_estimation_STBC.m (channel estimation) - one_shot.m (show an example) To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window. Reference: [1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202- 217)