road_q(t)

关于低密度奇偶校验码的生成，采用matlab编写，主要是校验矩阵的产生 (on low-density parity-check code generation, prepared using Matlab, mainly for the selection of calibration matrix)

在系统辨识前，对输入输出数据进行平滑处理，列举了移动平均法、loess、sgolay等几种平滑方法进行分析比较(System identification, data input and output smoothing, moving average method, loess, sgolay cited several smoothing methods were analyzed and compared)

This is a source code for controlling volume via DSP techniques

利用独立分量分析中的FastICA算法对盲信号源进行了分离。最终通过实验结果表明，独立分量分析可以有效地实现分离。(FastICA algorithm using independent component analysis and blind source separation. Eventually through the experimental results show that the independent component analysis can be effectively separated.)

基于K-L变换下的人脸检测程序，用matlab编写的(KL transform based face detection under the program, using matlab)

遗传算法-优化算法-模板-可以供学习参考(Genetic algorithms- Optimization- Template)

粒子群算法实现二维路径规划 MATLAB程序 可直接运行(Particle swarm optimization for two dimensional path planning)

电子工业出版社的《自适应滤波器》西蒙·赫金 书中例题的代码(Electronic Industry Press Adaptive Filter by Simon Haykin The code examples in the book)

产生右图所示图像f1(m,n)，其中图像大小为256×256，中间亮条为128 ×32，暗处=0，亮处=100。对其进行FFT： ① 同屏显示原图f1(m,n)和FFT(f1)的幅度谱图； ② 若令f2(m,n)=（-1）m+n f1(m,n)，重复以上过程，比较二者幅度 谱的异同，简述理由； ③ 若将f2(m,n)顺时针旋转90 度得到f3(m,n)，试显示FFT(f3)的幅 度谱，并与FFT(f2)的幅度谱进行比较； ④ 若将f1(m,n) 顺时针旋转90 度得到f4(m,n)，令f5(m,n)=f1(m,n)+f4(m,n)，试显 示FFT(f5)的幅度谱，并指出其与FFT(f1)和FFT(f4)的关系； ⑤ 若令f6(m,n)=f2(m,n)+f3(m,n)，试显示FFT(f6)的幅度谱，并指出其与FFT(f2)和 FFT(f3)的关系，比较FFT(f6)和FFT(f5)的幅度谱。(Generating an image f1 (m, n) shown in the figure, wherein the image size is 256 256, the intermediate light bar 128 32 0 = dark, bright Department 100. Its FFT: ① screen display picture f1 (m, n) and the FFT (f1) of the amplitude spectrum ② If so f2 (m, n) = (-1) m+n f1 (m, n), repeat The above process, comparing the amplitude spectrum of the similarities and differences between the two, brief reasons ③ If f2 (m, n) 90 degrees clockwise to get f3 (m, n), try to display FFT (f3) the amplitude spectrum and with the FFT (f2) comparing the amplitude spectrum ④ If f1 (m, n) obtained by 90 degrees clockwise f4 (m, n), so f5 (m, n) = f1 (m, n)+f4 (m, n ), try to display FFT (f5) amplitude spectrum, and pointed out its relationship with the FFT (f1) and FFT (f4) of ⑤ If so f6 (m, n) = f2 (m, n)+f3 (m, n) and try to display the FFT (f6) amplitude spectrum, and pointed out its relationship with the FFT (f2) and FFT (f3), comparing FFT (f6) and FFT (f5) amplitude spectrum.)

设一个小孩在平面上沿着某曲线行走，此曲线由时间参数曲线确定。假设小孩借助于一个长度为 的硬木棒拖着或推着一个玩具，试求玩具的平面轨迹。(set up a child in a plane curve walk along this curve by the time parameter curve. Using a hypothetical child for the length of the hard wooden dragging or pushing a toy, toys trial for the plane trajectory.)