matlab

Spread spectrum merupakan sistem dimana sinyal yang dikirimkan memiliki bandwidth yang jauh lebih lebar daripada bandwidth sinyal informasinya sendiri. Proses pelebaran bandwidth sinyal informasi ini dilakukan pada sisi pengirim dan disebut spreading. Sebaliknya, proses penyempitan kembali bandwidth sinyal informasi dilakukan di sisi penerima, dan disebut despreading. Pada gambar 1 berikut menunjukkan proses yang terjadi pada sistem spread spectrum.

matlab使用教程，ppt转pdf版的，需要的可以参考一下(Using matlab tutorial, turn PDF version of the PPT, need to consult)

瑞利衰落信道下，分簇协作的频谱感知，设定一个门限值，在AND规则下大于门限值的仿真(Rayleigh fading channel, the clustering collaborative spectrum sensing, adaptive collaboration)

Principal component analysis

实现高斯背景建模，并且提取运动目标。具有良好的适用性(Gaussian background modeling to achieve, and extract the moving target. Good applicability)

美国数学建模2010年预防犯罪的代码，利用连续加权的方法，其中需要画圆这里可以很好的利用此程序(American Mathematical modeling of the code of crime prevention in 2010, using the continuous weighting method, which need to draw a circle where you can put to good use this procedure)

程序先进行卷积编码，然后进行viterbi译码，程序有纠错功能，中间出现误码，程序解码时会自动纠正(Convolution coding program first and then viterbi decoding program has error correction, the error appears in the middle, when the program will automatically correct decoding)

认知无线中的能量检测，仿真了高斯信道和瑞利信道的检测概率、虚警概率与判决门限的关系曲线以及两者之间的关系曲线(The detection probability, false alarm probability and the decision threshold of the Gauss channel and the Rayleigh channel are simulated by the energy detection in cognitive radio.)

说明：  针对铣削过程建立的动力学方程，推导出可用以指导加工的稳定性叶瓣图，获得各主轴转速下对应的极限切深。(According to the dynamic equation of milling process, the stable lobe diagram which can be used to guide machining is derived, and the corresponding limit cutting depth of each spindle speed is obtained.)

针对灰度图像，提出一种基于知识的人脸检测方法。 提出了一种给予支持向量机的人脸检测方法。 提出了一种基于小波分解的LDA人脸识别方法。 提出了一种基于小波和DCT的人脸识别方法。 提出了一种机遇CEDT和支持向量机的人脸分类和识别方法。 (For gray-scale images, a knowledge-based face detection methods. A support vector machine method of face detection. A wavelet decomposition of the LDA-based face recognition methods. A wavelet and DCT-based face recognition methods. A CEDT opportunities and support vector machine classification and face recognition.)