MatlaB

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speech recognition for DSP

一、穆勒矩阵构成 穆勒矩阵是一个4*4的矩阵，完整描述了介质的偏振属性。可通过水平线偏振光H、垂直线偏振光V，45°线偏振光P，右旋圆偏振光R入射，并分别探测水平线偏振光H、垂直线偏振光V，45°线偏振光P，右旋圆偏振光R出射情况下的能量值，即16种偏振态组合下的强度结果，HH/ HV/ HP/ HR，PH/ PV/ PP/ PR，VH/ VV/ VP / VR和RH/ RV/ RP/ RR。进而Mueller矩阵可按照公式（1）计算得到：(First, the Muller matrix The Muller matrix is a 4*4 matrix that completely describes the polarization properties of the medium. The horizontal line, vertical line polarized light polarized light H V, 45 degrees P linearly polarized light, right circularly polarized incident detection and R, respectively, H vertical horizontal line polarized light polarized light V, 45 degrees P linearly polarized light, right circularly polarized light R emitted under the condition of energy intensity results of 16 kinds of polarization combinations HH/ HV/, HP/ HR, PH/ PV/ PP/ PR VH/, VV/ VP and RH/ RV/ RP/ RR / VR. Furthermore, the Mueller matrix can be calculated according to formula (1):)

共散射点正演模拟，而且有P波和S波速度扫描和速度谱制作的程序。(Forward modeling of scattering centers, and a P-wave and S-wave velocity and velocity spectra produced by the scanning process.)

二维FDTD总场散场的一个MATLAB程序，(FDTD finish at a total field of a MATLAB program,)

用matlab gui做的洛伦兹吸引子示例，演示了混沌中的洛伦兹吸引子轨迹。(Matlab gui to do with the Lorenz attractor example, in demonstration of the chaotic trajectory of the Lorenz attractor.)

说明：  改进的AR时间序列分析模型，加入了窗口的概念，源码里有实例(Improved AR time series analysis model, adding the concept of the window, there are instances where the source)

由Matlab进行数据处理，向DSP传递图像数据，再由DSP反馈处理后的数据，发挥两者优势，从而快速评估图像质量(From the Matlab data processing, transfer the image data to the DSP, and then processed by the DSP feedback data, play two advantages to quickly assess the image quality)

Image processing Fillters

Pattern search (also known as direct search, derivative-free search, or black-box search) is a family of numerical optimization methods that does not require a gradient. As a result, it can be used on functions that are not continuous or differentiable. One such pattern search method is "convergence" (see below), which is based on the theory of positive bases. Optimization attempts to find the best match (the solution that has the lowest error value) in a multidimensional analysis space of possibilities.