image-fusion

说明：  FNFB模擬，本論文旨在針對一自平衡兩輪電動車，發展兩種智慧適應運動控制策略及其嵌入式控制器研製技術。本文使用三星S3C2410 ARM處理器製作一台嵌入式控制器，用以實現所提的智慧適應型運動控制策略。藉由已發展的非線性數學模型，兩種結合模糊基礎網路(FBFN)之智慧適應型運動控制策略被提出，用以達成速度追蹤與轉向角速度控制。第一種智慧適應型運動控制方法使用模糊基礎網路近似學習模型不確定與時變的摩擦力，而第二種智慧適應型運動控制方法則採用模糊基礎網路直接學習該非線性控制器的能力。電腦模擬及實驗結果證實本文所建立的控制器有能力提供適當的控制動作，使得車體依照駕駛者的需求動作。(FNFB simulationThis thesis develops techniques for intelligent adaptive motion control and implementation of a self-balancing two-wheeled transporter. An embedded controller using Samsung S3C2410 ARM-9 processor is constructed to implement proposed motion control laws. With the nonlinear model of the vehicle, two kinds of intelligent adaptive motion controllers using fuzzy basis-function networks (FBFNs) are respectively proposed to achieve speed tracking )

这个程序是三种分集合并方式的比较，选择合并，等增益合并，最大比值合并(This program gives the comparison of improvements offered by the 3 combining techniques, namely Selection Diversity, Equal Gain and Maximal Ratio.)

FIR 滤波器 matlab/simulink dsp builder(FIR filter Matlab/Simulink dsp builder)

2D hertz contact program (MATLAB)

ALAMOUTI SPACE TIME BLOCK CODING

球形液罐模型仿真，就是对液位就行控制，使之稳定。(Spherical tank model simulation, is the level control on the line to make it stable.)

说明：  人脸检测的程序和文章，基于matlab。(face detection )

说明：  ucc_ean128条形码的详细规则，可用于开发此条形码时的参考资料。(ucc_ean128 detailed rules for the bar code, bar code can be used to develop this reference.)

本程序对语音信号加上不同长度的汉明窗，研究不同的窗长对语音信号的自相关函数的影响(Hamming window, the application on the speech signal plus different lengths study different window length of the autocorrelation function of the speech signal)

包括图像分析的四部分代码：matlab扩散和高斯函数，线性扩散，线性复扩散，非线性扩散。(It contains four parts： [1]MATLAB function:diffusion.m gauss.m [2]Linear diffusion Applying linear diffusion to images creating linear scale-space. MATLAB code: demo_lin.m Image: haifa1.bmp [3]Linear complex diffusion Applying linear complex diffusion creating Gaussian and Laplacian scale-spaces. MATLAB code: demo_cmplin.m [4]Nonlinear diffusions: Perona-Malik ["Anisotropic diffusion"] Catte et al. regularization of P-M Complex ramp-preserving diffusion Nonlinear edge preserving diffusions.The classical Perona-Malik process: the value of the diffusion coefficient is reduced near edges estimated by the first derivative. Best applied to step edges. A regularized version by Catte et al- the gradient estimation for controlling the process is smoothed by a Gaussian. Proved to be mathematically well-posed. Ramp preserving complex diffusion- best for ramp-type edges. Results are smoother with almost no staircasing effects. MATLAB code: demo_nldif.m Image: ct_scan.bmp)