math(1)

Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1] Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. The algorithm is patented in the US the owner is the University of British Columbia.

本程序是一个数据分类的程序，首先使用KL变换对数据进行降维和去噪，然后用BP神经网络对预处理过后的数据进行分类，并且留有部分的测试集(This program is a data classification program, the first to use KL transform data dimensionality reduction and de-noising, then BP neural network to classify the data after preprocessing, and left part of the test set)

MATLAB code for convolution of two signals in time domain

3-D FDTD code of patch antenna in free space with Mur s boundary condition

选择db10 小波和db10 小波两个小波函数实现了小波变换(Choose two db10 wavelet and wavelet db10 wavelet function implementation of wavelet transform)

说明：  信号z变换工具箱，包括GUI界面，解压直接使用，(signal z transformation toolkit, including the GUI interface, extracting direct use,)

Digital Signal Processing Using MATLAB, 3rd Edition proakis source code

This code is used for broad and narrow weed leaf classification

microprocessor basic theory

ANALOG AMP SIMULATION