matlab_c++

这个程序是用来雷达信号测距模拟的。这个信号时线性调频信号(This program is used to simulated radar signal ranging. Chirp signal when this signal)

wilkinson method for ber computation

阵列信号处理中的多波束形成，采用FFT方法进行多波束形成。附报告、源程序、仿真结果截图，内容详尽，希望对您有所帮助(Array signal processing in multi-beam forming, using the FFT method for multi-beam forming. Attached to the report, the source, the simulation results screenshots, detailed, I hope for your help)

只是一个图象处理以及视频截取图象的程序。(only a video image processing and image interception procedures.)

讲的是扩频通信系统中载波同步和码同步算法的Matlab程序(About the spread spectrum communication system, synchronization and carrier synchronization algorithms for Matlab program code)

设计IIR滤波器,对滤波器系数按4bit和5bit量化。(Design of IIR filter coefficients of the filter and 5bit quantified by 4bit.)

理解随机信号功率谱分析原理和方法。 (1) 生成信号，被淹没在在噪声中； (2) 试用周期图法估计信号的功率谱； (3) 选用不同窗，使用修正周期图法估计信号的功率谱； (4) 对一段语音信号，使用LD算法估计其功率谱； (5) 详细列出功率谱估计的步骤和原理。 (understanding of random signal power spectrum analysis principles and methods. (1) generate signals being drowned in the noise; (2) The probationary period plan estimates the signal power spectrum; (3), different windows, the use of map amendment cycle method to estimate the power spectrum signal; (4) a voice signal, the use of LD algorithm to estimate the gong spectrum; (5) a detailed breakdown of the power spectrum estimation steps and principle.)

Systemidentificcation，系统辨识 (Systemidentificcation, system identification)

说明：  scalable router and hierarchical model based on architecture and models

The local binary pattern (LBP) is a simple yet very efficient operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. Perhaps the most important property of the LBP operator in real-world applications is its invariance against monotonic gray level changes caused, for example, by illumination variations. Another equally important is its computational simplicity, which makes it possible to analyze images in challenging real-time settings. LBP is also very flexible: it can be easily adapted to different types of problems and used together with other image descriptors