TheFilterDesign

Matlab Simulation FilesMatlab Simulation Files(Matlab Simulation Files)

tool for measuring images

程序1：周期信号（方波）的展开 程序2：用图形表示DSB调制波形及其包络线 程序3：通过傅里叶变换找出被随机信号淹没的信号频率 程序4：DSB-AM 双边带幅度调制和解调 程序5：AM调制和解调(Procedure 1: periodic signal (square wave) Program 2: graph DSB modulation waveform and its envelope Application 3: through the Fourier transform to find out the submerged by random signal signal frequency Program 4: DSB- AM double sideband amplitude modulation and demodulation Program 5: AM modulation and demodulation)

说明：  emd 分解能够有效地进行分解以及进行数据变成(hgvjhsbsjjknfjsnlknfklsflskklssslkfkslslkfnssfsnm n,m,)

DTW is one of the method to identify speech and signature or any biometric hope to enjoy it

用matlab的核函数对钓鱼岛实现分类（模式识别作业）(Kernel function using matlab realize the Diaoyu Islands classification (pattern recognition operations))

计算方法程序，龙贝格算法的matlab程序，精简明了，注释全面，自己的计算方法作业，很认真的编写的(Calculation program, Romberg algorithm matlab program, streamlining and clear, comprehensive notes, his method of operation of calculation, it is prepared carefully)

雷达信号处理 雷达作用距离 功率，距离，RCS(Pulse compression simulation MATLAB version, GUI procedures)

学自控的人应该好好看看哦！直接用其强大的函数功能。(good!)

Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve contentbased face retrieval by constructing semantic codewords for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attributeembedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the results show that theproposed methods can achieve up to 43.5 relative improvement in MAP compared to the existing methods.