hierarchicalCentroid

Generating Random Number with Multi-dimensional

第7章 数值微分.zip。是从书中光盘里拷贝的代码，放在这里与大家共享，希望对大家有帮助。(Chapter 7, numerical differentiation)

对一个四阶系统用DMC算法进行控制仿真，可移植性强，只需改变系统模型即可(With a fourth-order DMC algorithm to control system simulation, portability, you can simply change the system model)

各向异性去噪，考虑到空间域的临近关系，同时考虑灰度的相似性，是相对比较经典的去噪模型(Anisotropic denoising, taking into account the close relationship between the spatial domain, taking into account the similarity of gray, is a relatively classical denoising model)

说明：  Matlab image inpainting using deep learning

自编四参数法生成多孔介质的matlab程序代码(Four-parameter method to generate self matlab code porous media)

常用数值算法 包括c++，c，MATLAB，等等(Numerical algorithm used includes c++, c, MATLAB, etc.)

编写的小波去噪程序，主要用于光纤捷联惯导系统中的惯性器件输出噪声滤除，为后续导航解算提供基础(The wavelet denoising program written mainly used in fiber SINS the inertial device output noise filtering, to provide a basis for subsequent navigation solution)

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

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