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its a matlad code for ridge segmentation for fingerpprint recognition project

流形学习matlab实现源码，好东西大家一起分享(Manifold learning matlab source code to achieve good things to share with everyone)

说明：  参考文件MAT-FILE打包下载visualC加加MATLAB(MAT-FILE)

说明：  uwb信道仿真程序，包括多种算法(UWB channel simulation program, including a variety of algorithms.)

知名的 baseflight 四轴飞行器移植到匿名四轴的硬件上(Renowned baseflight quadrocopter transplanted into anonymous axis hardware)

In this paper, we have proposed a new PAPR reduction technique in MIMO-OFDM systems. It achieves the result which proves the PAPR of 2×2 MIMO-OFDM systems. The parameters of the simulation are determined by standard IEEE 802.11n. From the simulation results, it is shown the proposed method has better PAPR performance in this system. Additionally, when the number of sub-blocks is increased, high PAPR reduction performance can be obtained.

说明：  整个系统分为数据采集和数据分析两大部分，以友好的图形界面与用户进行交互沟通。 声音数据采集部分实现数据采集功能,根据用户选择的采样频率和预设的采样时间来从声卡获得用户需要的数据。并且将采集到的数据及其频谱图以图形方式很直观的呈现于用户面前。 图像采集分析部分，读入图像后，根据选择，对其进行Linear Conformal、Affine、Projective、Polynomial、Piecewise Linear、Sinusoidal、Barrel、Pin Cushion变换(The whole system is divided into data collection and data analysis of two parts, with a friendly graphical interface to communicate with the user interaction. Sound data collection part of the data collection function, according to user-selected sampling frequency and sampling time to the default user from the sound card to obtain the data needed. And the collected data and the spectrum is very intuitive graphically presented in front of the user. Image acquisition and analysis section, read the image, based on the choice of its Linear Conformal, Affine, Projective, Polynomial, Piecewise Linear, Sinusoidal, Barrel, Pin Cushion Transformation )

相干信号的DOA估计，MUSIC算法与MMUSIC算法的测向功能对比(DOA estimation of coherent signals, compared with MMUSIC algorithm MUSIC algorithm finding function)

proakis书籍中的matlab仿真代码(proakis books of matlab simulation code)

数据资料是数学模型与实际问题接轨的重要途径和手段，有时还可以直接从数据资料中发现规 律组建模型。数据分析和处理是统计学研究的主要内容，也是计算数学的工作领域，近年来随 着计算机科学的发展，对“海量”数据的分析形成了一门新的交叉学科“数据挖掘”。这一章仅 介绍用统计学的最小二乘法构造拟合数据模型，以及用计算数学的函数插值方法处理数据解决 实际问题。(Is a mathematical model of data integration an important practical problem with the ways and means, and sometimes directly from the data can also be found in the law of the formation model. Statistical data analysis and processing is the main research, but also work areas of computational mathematics, computer science in recent years, along with the development of the " mass" analysis of the data formed a new cross-disciplinary " data mining." This chapter describes only the structure with a statistical method of least squares fit data models, and computational mathematics and data processing function interpolation methods to solve practical problems.)