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一种基于广义Hough变换的破碎图形的识别方法(Generalized Hough transform based on the recognition of broken graphics)

说明：  用matlab实现神经网络的算法，代码简练可运行。(The algorithm of neural network is written in the matlab environment.The code is simple and good,It can run very well.)

汽车系统动力学的操纵动力学部分，经检查正确(Automotive parts handling dynamics of system dynamics, the check for the correct)

cordic向量迭代求取IQ信号幅值，及相位 反cordic求正弦、余弦值(use cordic to computer the magnitude of IQ signal and cos、sin )

matlab 用于sis模型的研究 一篇论文 希望有用(matlab sis)

The optimal tire force distribution to maximize acceleration/deceleration of a four-wheel vehicle during cornering is studied

MULTIMEDIA SIGNAL PROCESSING IMAGE PROCESSING

我自己编的串音误差计算函数，对公式进行了一定化简，比本网站其他同类计算函数运算速度要快。用于盲源分离的质量评价，另外还包含ICA中有关性能评价指标的文章。(My own series of crosstalk error calculation function, to the formula for a certain simplification, other than this site similar calculation function operation faster. Quality Evaluation for blind source separation, also contains articles on the ICA performance uation index.)

网上大多数matlab代码跑出来的结果不准确，在原有基础上改了一下，但只能在证据之间不产生冲突情况下使用(Most of the MATLAB codes on the Internet run out of inaccurate results. They have been modified on the original basis, but can only be used in cases where there is no conflict between the evidences.)

针对基于小波变换的红外图像增强方法视觉效果不够理想的缺点, 提出了一种基于平稳小波变换和Retinex 的红外图像增强方法, 利用Retinex 增强算法增强图像的视觉效果, 并改善其亮度均匀性。首先, 对红外图像经平稳小波变换后的最大尺度低频子带图像进行多尺度Retine x 增强 然后, 利用贝叶斯萎缩阈值法对高频子带图像进行阈值去噪, 并根据低频子带图像的局部对比度和模糊规则计算高频子带的增益系数, 从而得到增强后的高频子带图像 最后, 由低频子带图像和高频子带图像重构得到增强后的图像。针对大量图像进行了实验和增强效果的定性与定量评价, 并与双向直方图均衡法、二代小波变换法、Curvelet 变换法和多尺度Retinex法作了比较。结果表明, 所提出的方法增强了图像细节, 抑制了噪声, 并明显改善了图像的整体视觉效果。(As infrared image enhancement method based on wavelet transformation has the problem of unperfect visual effect , and Retinex enhancement algorithm can enhance visual effect of the image by improving brightness uniformity , amethod based on stationary wavelet transformation and Retinexis proposed.Firstly , the infrared image is decomposed into high-frequency detail and low-frequency approximation components at various resolutions, and the low frequency subband image of the largest scale is enhanced by multiscale Retinex algorithm.Then, the highfrequency subband images are denoised by Bayesian shrinkage method, and the gain coefficients of high-frequency subbands are available by calculating the local contrast of the enhanced low-frequency subband based on fuzzy rules to get the enhanced high-frequency subband images .Finally, the enhanced image is reconstructed by the low-frequency subband and high-frequency subbands .Experiments with qualitative and quantitative uation are carried ou)