ASK-and-PSK

flow optical in vehicle recognition

卡尔曼滤波用于系统辨识,推荐大家下载，网上很难找到(Kalman filter for system identification, we recommend downloading difficult to find online)

基于白噪声法路面不平度仿真程序，可以仿真得到路面不平度的时域激励。(Method based on white noise process simulation of road roughness, road roughness can be simulated by time-domain excitation.)

this code helps u to apply smoothing filter on the image

说明：  005小波变换及其MATLAB工具的应用(005 DWT and MATLAB application tools)

Extremely high performance radio-access technology that offers full vehicular speed mobility and that can readily coexist with HSPA and earlier networks. OFDM/OFDMA technology is introduced for the LTE downlink, supporting very high data rates of up to 300Mbps while Single-Carrier FDMA (SC-FDMA) is used in the uplink with data rates of 80Mbps possible. Additionally, LTE supports operation both in paired and unpaired spectrum (FDD and TDD) using channel bandwidths of approximately 1.4MHz up to 20MHz. The frequency domain scheduling can be done in OFDMA. One of the main challenges in OFDMA is the high peak-to-average radio of the transmitted signal, which requires linearity in the transmitter. The linear amplifiers have low efficiency therefore, OFDMA is not an optimized solution for a mobile uplink where the

重力异常的向上延拓程序，很实用，推荐地球物理学生学习(Gravity anomaly upward extension procedure is very useful, recommended geophysics students)

利用二阶最小化，实现射影变形下的目标跟踪，windows下版本。(Minimize the use of second-order to achieve the objectives under the projective deformation tracking, windows version of.)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

cooperative communication theory