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说明：  随机过程在三国杀中的数学建模及matlab仿真报告(Three killed in Stochastic Process in Mathematical Modeling and Simulation Report matlab)

matlab 但是防守对方似懂非懂是发生的发生地(matlab but the defense is the other occurrence took place Sidongfeidong)

matlab neuron system spike tran2

针对20个已知类别数据，前15个训练样本和带刺的5个样本，通过该程序可识别出待测的样本属于哪一类。(Data for the 20 known types, the first 15 training samples and barbed 5 samples can be identified by the program which type of samples tested.)

Amin Koohi的基于MFCC特征参数提取的说话人识别程序，可运行。(Based on MFCC feature parameter extraction of speaker recognition program Amin Koohi.)

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.)

this a matlab work about DSP 0.

机械方面基于matlab的连杆分析程序，凸轮设计程序(Mechanical matlab-based linkage analysis program, the cam design program)

find final scaling contrast map

A database of facial expression images was collected. Ten expressors posed 3 or 4 examples of each of the six basic facial expressions (happiness, sadness, surprise, anger, disgust, fear) [4] and a neutral face for a total of 219 images of facial expressions.