xialiaowenti

matlab的87个实例，基本上涵盖了matlab得许多操作函数和图像处理方法，对大家的学习很有帮助。(87 instances of matlab, matlab have basically covered many operations functions and image processing method, all very helpful.)

A QPSK simulation using simulink. very useful to understand the scheme at every level of QPSK modulation.

利用的图像处理中的梯度直方图，再加上词袋模型的知识，编得还可以(Gradient histogram of image processing, plus knowledge bag of words model series was also)

使用MATLAB软件，应用吉布斯采样方法，对信号进行抽样(use MATLAB)

很好的matlab英文教程，不错的奥，值得看。(matlab)

- XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H. Dam, H.A. Abbass, C.J. Lokan, Evolutionary Online Data Mining – an Investigation in a Dynamic Environment. 2005, accepted for a book chapter in Springer Series on Studies in Computational Intelligence H.H. Dam, H.A. Abbass, C.J. Lokan, Be Real! XCS with Continuous-Valued Inputs. IWLCS 2005, (International Workshop on Learning Classifier Systems). Washington DC, June 2005.(- XCS for Continuous Dynamic Environments Test versions of XCS problem : real multiplexer Experiments : XCS is explored in dynamic environments with di fferent magnitudes of change to the underlying concepts. Reference papers : H. H. Dam, H. A. Abbass, C. J. Lokan. Evolutionary Online Data Mining-an Investiga tion in a Dynamic Environment. 2005. accepted for a book chapter in Springer Series o n Studies in Computational Intelligence H.H. D am, H. A. Abbass, C. J. Lokan. Be Real! XCS with Continuous- Valued Inputs. IW LCS 2005. (International Workshop on Learning Classifi er Systems). Washington DC, June 2005.)

PCA用于组成分分析，在labview下编程的，对于初学PCA有一定的帮助(PCA analysis labview)

简单的介绍什么是深度学习、深度学习的应用场景等基础知识，帮助我们快速入门该领域(Briefly introduce what is the basic knowledge of deep learning, deep learning application scenarios, and help us quickly get started in this field.)

This source code describes the minimum frequency seperation between two signals to be orthogonal with two cases for phase differences

Tranformasi wavelet merupakan perbaikan dari transformasi Fourier. Transformasi Fourier hanya dapat menangkap informasi apakahsuatu sinyal memiliki frekuensi tertentu ataukah tidak, tapi tidak dapat menangkap dimana frekuensi itu terjadi. Jika Transformasi Fourier hanya memberikan informasi tentang frekuensisuatu sinyal, maka transformasi wavelet memberikan informasi tentang kombinasi skala dan frekuensi