read_gdf

CAVLC tables generator

本人写的中值和均值滤波的代码，主要用于SAR成像滤波，希望管理员给予通过(I wrote the median and mean filtering code, mainly for SAR image filtering, administrators hope to give through)

二维光子晶体禁带的遗传优化算法MATLAB源码(Two-dimensional photonic crystal band gap genetic optimization algorithm MATLAB source)

切比雪夫最佳一致逼近设计多带线性相位FIR滤波器(Chebyshev best uniform approximation design multi-band linear phase FIR filter)

图像配准定义为：对从不同传感器、不同时相、不同角度所获得的两幅或多幅图像进行最佳匹配的处理过程.图像配准需要分析各分量图像上的几何畸变，然后采用一种几何变换将图像归化到统一的坐标系统中。在配准过程中，通常取其中的一幅图像作为配准的标准，称之为参考图像；另一幅图像作为配准图像(Image registration algorithm)

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.

traveling problem salesman

固定阵列孔径，随机阵元间隔MVDR,OPT,LMS方法波束形成(Fixed array aperture, random array element interval MVDR, OPT, LMS beamforming)

有关ifr iir 的学习电子书，介绍了这两种的使用方法(a pdf for ifr and iir , they are two kinds of filter)

说明：  该课题为基于MATLAB的bp神经网络的交通标志识别系统，可以识别禁令标志，警示标志，指示标志三种标志，带GUI界面，流程为，输入测试图，训练，定位，分割，识别。可自动识别是三种中的哪一种。定位是采用颜色的方法，分割是几何位置分割，识别bp神经网络。注释详细。(This project is a traffic sign recognition system based on BP neural network of MATLAB. It can recognize three kinds of signs: prohibition sign, warning sign and indication sign. It has GUI interface. The flow is: input test chart, training, positioning, segmentation and recognition. Which of the three can be automatically identified. The location is based on the color method, and the segmentation is based on the geometric position segmentation to recognize the BP neural network. Note details.)