houghpeaks_s

自己做用FPGA实现VGA显示时，图像提取信息的matlab程序！！！(FPGA realization of their own with VGA display, the image information extraction matlab program! ! !)

惯性初始对准，利用解析法描述初始对准过程(The inertia of the initial alignment, analytical description of the initial alignment process)

基线校正代码，包括小波基线校正及滤波器基线校正，可用于光谱数据的预处理。(Baseline correction codes, including wavelet baseline correction and filter baseline correction, can be used for preprocessing of spectral data.)

说明：  对萨德系统AN/TPY-2雷达的威力范围进行仿真计算。原创！！(The power range of SAD AN/TPY-2 radar is simulated. Original!!)

DVB-T 2K signal generation Eq. (2.1.4) vs. 2N-IFFT.DVB-T 2K 信号发生器matlab源代码。(DVB-T 2K signal generation Eq. (2.1.4) vs. 2N-IFFT.DVB-T 2K signal generator matlab source code.)

GPON 标准 GPON ITU 标准 G984.1-2003 (GPON ITU standard G984.1-2003)

说明：  信号的频谱及时频分析图以及加噪声后的性能分析，跳频信号的wvd分析(Performance analysis of the signal spectrum frequency analysis chart in a timely manner as well as the added noise)

克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后　进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)

阵列声源声场模拟的matlab程序（包括声柱，同相点声源等）( simulation of spk arriys’acoustic performance )

The sign language recognition to create a to store the training image, the video capture infront the user image and each sign language assign the letter the preprocessing the image then image is convert into rgg to cbcr. The image is segmented feature extract the shape and skin color then use the svm classification.