搜索资源列表
ICA_demo_text
- ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical
Ray_Fading_MED
- matlab实现的无线信道仿真，具体方法为正弦波叠加法的MED
SENSEgfactorcalculation
- 计算SENSE重建图像中的g-factor,这是并行磁共振成像SENSE算法的关键一步-G-factor is the metric to quantify the amplificaiton of noise power in reconstructing SENSE accelerated image. The detail was presented in Pruessmann s 1999 Magn. Reson. Med. paper. In theory, g-factor is t
Bio-med-_answerkey
- biomedical signal processing. model question paper and answer key
MED
- 最小熵翻卷积的源代码，此文摘自澳大利亚的学者。-Minimum entropy turn convolution of source code
voting-algorithm
- this a voting algorithm MATLAB codes for fault tolerant systems. file consist of five m-files that fours of them runs from testmaj m-file. inxmaj m-file is a function for inexact majority algorithm, inxplu is a function for inexact plurality algorith
Constrained-Engineering-Optimization
- 将离散约束优化问题转化为非负整数约束规划问题，开发求解该问题的离散差分进化算法。该算法采用基于混沌映射 的种群初始化、双版本变异和带随机扰动项的取整运算等新策略。针对非线性约束条件，给出惩罚基数的计算方法和连续映 射基函数的表达式，在此基础上设计处理非线性约束的自适应惩罚因子。提出一种刻画种群多样性的新测度——种群二次平 均基因距离及基于新测度的依概率混沌移民算子。将自适应罚函数法、依概率混沌移民操作与离散差分进化算法有机融合， 构造面向工程约束优化的混合离散差分进化算法
MED
- A Study of Bias Correction Methods for Enhancing Median Edge Detector Prediction-A Study of Bias Correction Methods for Enhancing Median Edge Detector Prediction
med
- 最小熵解卷积（MED），是一种自适应滤波器设计方法，可以提取冲击成分-Minimum entropy deconvolution (MED), is an adaptive filter design method that can extract the impact of component
med
- Image Capture Camera the imposition of noise median filter
omeda
- Non-iterative optimal solution for Minimum Entropy Deconvolution (MED) and convolution fix
med
- Calculate the coordinates of the point , rgb2gray , Convert the gray code sequence to decimal number = column number
MCKD
- med的升级版本，加入了自相关的概念，但是有一个缺点是需要知道特征频率，去噪效果相对更好-Med version of the upgrade, adding the concept of self-correlation, but there is a drawback is the need to know the characteristics of frequency, the noise is relatively better
1
- 将一个周期曲柄的转角如从0°到360°分成100个点，令dθ ω1dt；Medθ是转过 dθ角度等效力矩做的功，右边d()为动能的增量。编制相应的程序，即可求出每个位置对应的等效力矩Me，从而可求出驱动力矩M1-100 points, let dθ ω1dt Medθ is the work done by dθ angle equivalent moment, the right d () is the increment of kinetic energy. The preparati
MED算法
- Matlab编写的MED最小熵解卷积算法，可实现对故障特征的提取。(Matlab's MED minimum entropy deconvolution algorithm can be used to extract fault features)
deconvolution
- 时域解卷积的有关算法，med,mckd meda ,omeda,momeda等(The relevant algorithms for time domain deconvolution, Med, MCKD MEDA, omeda, momeda and so on)
MED.matrix
- matlab hi this is nonsense
AR_MED_filter
- 关于MED的程序源码，经本人验证，可以在matlab上运行(On the MED program source code, I verify, can run on matlab)
AR_MED_filter
- AR-MED 滤波，可用于轴承故障诊断，齿轮故障诊断(AR-MED filter for bearings fault diagnosis)