A complete description of the book and the full network support, will enable rea...

signal processing about OFDM simulation

ML in robitics assingment

QASKENCO Map a message to a QASK square signal constellation.

第一步是计算输人信号单边功率谱密度（ESD）。使用快 ％速傅里叶（FFr）算法将信号从时域转换到频域。因为FFr算法的输出是离散谱，而这 ％里我们需要的是连续谱，因此需要引人不同的比例因子来实现从离散谱到连续谱的转换。 ％在第二步中，我们利用迭代算法计算出相对于特定阂值的ESD的最高和最低频率，从而 ％估算出被检测信号所占用的带宽。这种算法同时适用于基带信号和已调制信号。最后， ％在第三步中，我们给出了输出图形的原代码。(The first step is calculating the input signal unilateral power spectral density (ESD). The use of fast Fourier speed (FFr) algorithm for the signal conversion from time domain to frequency domain. FFR algorithm because the output is a discrete spectrum, which we need is a continuous spectrum, so the need for food of different scale factor to achieve from the discrete spectrum to continuous spectrum conversion. In the second step, we use iterative algorithm to calculate a specific threshold in relation to the ESD of the highest and lowest frequency, thus estimated to be occupied by the signal detection bandwidth. This algorithm applies to both baseband signal and modulation signals. Finally, in the third step, we give the graphical output of the original code.)

实现MATLAB下的音频AGC,关键是要有高效的算法。效果不错。(MATLAB realize the audio AGC, the key is to have efficient algorithms. Good results.)

matlab的同步电机的仿真技术 可用于7.0以上(matlab simulation of synchronous motor technology can be used for more than 7.0)

permutar matriz y generador de arreglo de numeros aleatorios irrepetibles

DMC的matlab实现,很实用的matlab代码(DMC s matlab realize, very practical matlab code)

介绍了在提取穿越次数特征、粗网格特征以及密度特征提取的基础上应用SVM进行手写体阿拉伯数字识别的方法。(Introduced the extraction across a number of features, coarse grid and density feature extraction on the basis of the application of SVM method for handwritten digits recognition.)

笔者自行编写的Matlab环境下的人脸识别算法小实验， 采用的是经典的PCA算法，主要内容是采用SVD方法提取出象素空间上的 PCA主分量特征，分类算法上仅是基于最小距离分类 (The author of the Matlab environment to prepare the face recognition algorithm under small experiment using classical PCA algorithm, the main contents of SVD method is used to extract pixel space on the PCA principal component features, the only classification algorithm is based on the minimum distance classifier)