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博士论文，分数阶微积分在现代信号分析与图象处理中应用给出了详细的分析和探讨，论文覆盖面广，有着很多的实验结果和详尽的分析。(Ph.D. thesis, fractional calculus in a modern signal analysis and image processing application gives a detailed analysis and discussion, research papers covering a wide range, has a lot of experimental results and detailed analysis.)

边缘保留平滑滤波器的实现代码，用于图形图像处理问题(Edge-preserving smoothing filter to achieve code for graphics and image processing problems)

s变换；广义s变换；高斯邻域；时频分析；滤波(s transformation generalized s transformation Gaussian neighborhood time-frequency analysis Filtering)

基于基元共生矩阵的纹理特征提取。通过5个基本的方格来检测图像并生成图像的基元共生矩阵，并从矩阵中提取其纹理特征信息。(Texton occurrence matrix based texture feature extraction)

分水岭分割方法，是一种基于拓扑理论的数学形态学的分割方法。(Watershed segmentation method is a method of mathematical morphology segmentation topological theory.)

目前最重要的图像变化检测评价标准：roc曲线，以及roc曲线下面积。(ROC curve of image change detection)

介绍了DAB 接收机中的OFDM 同步算法，重点对OFDM 接收机方案中基于保护间隔的符号定时估计、频 率偏移估计进行了分析，提出了适用于Eureka147DAB 系统的同步算法；并对各种算法进行了计算机仿真，本文介绍的算法满 足DAB 接收机的要求，有很大的应用价值。(Introduced the DAB the OFDM receiver synchronization algorithms, focusing on OFDM receiver scheme based on the protection of the interval estimation, frequency symbol timing Rate migration estimates are analyzed and some appropriate Eureka147DAB system in the synchronization algorithms And kinds of the computer simulation algorithm, this paper introduces the algorithm of the full The requirements of the foot DAB receiver, a large application value. )

改进的图像分割算法：运用SLIC超像素分割和DBSCAN聚类算法相结合的方法实现图像分割(Image Segmentation using SLIC SuperPixels and DBSCAN Clustering)

计算haar尺度函数和小波基系数矩阵，用于数值计算，如解偏微方方程，自己编写的。(Computing haar wavelet scaling function and the coefficient matrix for the numerical calculation, such as the solution of partial differential equations side, I have written.)

说明：  本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.)