gaussianiir-20111112

小波变换C语言实现,包含小波变换中各种算法，可以进一步了解算法的具体过程(Wavelet Transform C Language Realization)

an exemple of source that i was programming last night

正确读取雷达基数据，适合初学者使用，是个不错的例子。(Read correctly radar base data, suitable for beginners to use, is a good example.)

24G高集成度微波雷达芯片,一发二收，可组成阵列天线，数据处理后精度可达mm级(24 GHz transceiver MMIC with one transmitter and two receiver units • Fully integrated low phase noise VCO • Switchable prescaler with 1.5 GHz and 23 kHz output • On chip power and temperature sensors • Gilbert based homodyne quadrature receiver • Single ended RF input terminals)

对图像进行预处理，主要的预处理是通过Matlab软件对图像进行直方图均衡化、增加对比度等操作(Nogata will increase the degree of balancing operation, etc.)

Tutorial One (You should run it in the Command Window)

计算mie散射相关参数，根据颗粒粒径 ，入射光波长 ，颗粒折射率，介质折射率，计算不同角度下散射光强，不同粒径下的消光系数。(Calculate the mie scattering related parameters, calculate the scattered light intensity at different angles and the extinction coefficient at different particle sizes according to particle size, incident light wavelength, particle refractive index, and medium refractive index.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

MATLAB图像处理中的实力应用 ，在文字识别，车牌识别中有较为广泛的应用，第2部分(MATLAB image processing in the strength of applications, in character recognition, license plate recognition to have a fairly wide range of applications, Part 2)

自己编写的2维动态模型，运用卡尔曼滤波仿真。(I have written two-dimensional dynamic model, the use of Kalman filter simulation.)