MATLAB

用MATLAB实现的BPSK调制解调源程序(In MATLAB source code for BPSK modulation and demodulation)

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.)

Space time coding in MIMO sistems

lorenzx相位图 吸收引子 混沌 chaos(lorenz system phase)

eemd的matlab源程序 能够较好的实现信号的预处理(EEMD matlab source code to achieve the signal preprocessing better)

book for kalman filter using matlab image processing

基于SVM的人脸识别，识别率很高的，MATLAB代码，已验证完毕(SVM-based face recognition, recognition rate high, MATLAB code, has completed verification)

《visual c++matlab图像处理与识别实用案例精选》源码(" Visual c++ matlab image processing and recognition of practical cases selected" source)

说明：  利用遗传算法优化BP神经网络权值和阈值，然后进行训练，利用训练好的模型进行预估。附实例(The use of genetic algorithm to optimize BP neural network weights and thresholds, and then training, training a good use of forecast models. Attached examples)

对初学者适合的matlab命令集学习，还是很不错的，查找语句时有帮助(Right of the matlab command set suitable for beginners to learn, still very good, to find statements from time to time to help)