TD-SCDMA

kalman滤波全程序的范例，可以进行一维和二维计算(kalman filter example of the whole procedure can be carried out one-dimensional and two-dimensional calculation)

对音频信号进行DWT变换，可嵌入水印信息(DWT transform audio signals can be embedded watermark)

利用MATLAB进行带通数字调制与解调——M元正效幅度键控调制。(we use MATLAB for bandpass digital modulation and demodulation- M Yuan positive effect amplitude shift keying modulation to achive a good understanding.)

说明：  boost电路仿真，元件采用的是igbt，用触发脉冲触发的(boost simuliation The components are IGBT and triggered by trigger pulse.)

基于fft的三维高斯粗糙面生成，可以快速模拟三维高斯粗糙面，便于更深层次的研究(3d gauss rough surface)

乘子迭代过程，五个文件,实现迭代运算，有效提高性能(Multiplier iteration process ONE，Implement iterative operation, effectively improve the performance to realize iterative operation, effectively improve the performance)

《射频电路设计——理论与应用》一书课后习题第四章Matlab程序代码("RF circuit design-- Theory and Application," a book chapter IV Swimming Exercises Matlab code)

matlab机器学习中用于聚类，适用于样本数量相对较少的情况。(matlab machine learning for clustering, applies to a relatively small number of samples.)

该程序是一种维纳滤波的matlab实现程序，该方法通过分块处理，大大降低计算复杂度(The program is a Wiener filter matlab procedures, the method by block processing, greatly reducing the computational complexity)

克里金法假定采样点之间的距离或方向可以反映可用于说明表面变化的空间相关性。克里金法工 具可将数学函数与指定数量的点或指定半径内的所有点进行拟合以确定每个位置的输出值。克里金法是一个多步过程；它包括数据的探索性统计分析、变异函数建模 和创建表面，还包括研究方差表面。当您了解数据中存在空间相关距离或方向偏差后，便会认为克里金法是最适合的方法。该方法通常用在土壤科学和地质中。(This function completes what I have started with the functions variogram and variogramfit. It is not intended to be a highly optimized code for performing kriging but may have educational value. Note that for using kriging, you should download the latest version of variogramfit. kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform an ordinary kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the alg)