特征向量

说明：  次文件夹包含两个程序，可以对振动信号进行包络分析，适合信号处理入门的朋友(do envelope analysis on vibration signal)

实现肺实质初始分割及采用滚球法（形态学开运算）进行修补肺实质轮廓凹陷。(Achieve initial segmentation and the use of the pulmonary parenchyma ball method (morphological opening operation) to repair the lung parenchyma contour depression.)

基于matlab的各种三维画图，种类比较齐全(All kinds of three-dimensional drawings based on MATLAB are quite complete)

数学形态滤波。包括打开，滤波，处理，去噪等一系列功能。代码实验无误(Mathematical morphology filtering. A series of functions, including open, filtering, processing, denoising. Code experiment is correct)

利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)

实现文章“Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries”中的降噪算法(Realize the article " Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries" in the noise reduction algorithm)

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

java 图形算法实现源代码，有坐标放大缩小。(java graphics algorithm source code, coordinates Zooming.)

可以实现bmp图象的sobel边缘检测运算，并含有可图象重建功能。简单，易懂，使用了DIB接口，适合作数字图象处理的初学者作参考(Bmp images can be achieved sobel edge detection operator, and contains the reconstruction of functional images. Simple, understandable, the use of the DIB interface, suitable for beginners of digital image processing for information)

针对图像进行快速傅里叶变换，方便进行频频分析与处理。(Fast Fourier transform for the image, to facilitate frequent analysis and processing.)