MATLAB-algorithm

基于Matlab的QPSK调制解调的仿真程序,希望对大家有所帮助(Matlab-based simulation of QPSK modulation and demodulation process, want to help everyone)

用MATLAB实现功率谱的线性均方估计随着信噪比的变化的改变情况(MATLAB realization of the power spectrum with a linear mean square estimation changes with the change in the situation SNR)

DK-SVD，CVPR文章 Discriminative K-SVD dictionary learning for face recognition 源码，效果好于原始SRC(DK-SVD，the source code of CVPR paper Discriminative K-SVD dictionary learning for face recognition, its has a better performance than the classical SRC classifier )

对space borne GPS 接收机 Phoenix的数据处理matlab 程序(data processing for the Phoenix space-borne GPS receiver)

改程序主要是针对雷达信号处理中的应用，结合matlab处理(Reform program is mainly aimed at the application of radar signal processing, combined with matlab processing)

光纤中纤芯基模的有效折射率计算程序,二分法求解！(fiber core base mode of the effective refractive index calculation procedures for dichotomy!)

the book describes the object oriented feature in matlab programming language in detail, and discuss how to programming in object oriented matlab.

ofdm无线局域网，比较有代表性的一本书，理论和实践结合起来了(ofdm wireless LAN, more representative of a book。- A Theoretical and Practical Guide)

《MATLAB神经网络30个案例分析》中的第7个例子，案例7 RBF网络的回归-非线性函数回归的实现。希望对大家有一定的帮助！ (The MATLAB neural network analysis of 30 cases of example, 7 cases of RBF network return- the return of nonlinear function implementation. Hope to have certain help to everybody! )

说明：  半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性，因此，半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)