* acousticfeatures.m: Matlab script to generate training and testing files from event timeseries. * afm_mlpatterngen.m: Matlab script to extract feature information from acoustic event timeseries. * extractevents.m: Matlab script to extract event timeseries using the complete run timeseries and the ground truth/label information. * extractfeatures.m: Matlab script to extract feature information from all acoustic and seismic event timeseries for a given run and set of nodes. * sfm_mlpatterngen.m: Matlab script to extract feature information from esmic event timeseries. * ml_train1.m: Matlab script implementation of the Maximum Likelihood Training Module. ?ml_test1.m: Matlab script implementation of the Maximum Likelihood Testing Module. ?knn.m: Matlab script implementation of the k-Nearest Neighbor Classifier Module.
标签： acousticfeatures timeseries generate training
上传时间： 2013-12-26
上传用户：牛布牛
实现PET/SPECT 幻影图像regression的matlab源代码 algorithms for Poisson emission tomography PET/SPECT/ Poisson regression eml_ emission maximum likelihood eql_ emission quadratically penalized likelihood epl_ emission penalized likelihood
标签： Poisson SPECT regression algorithms
上传时间： 2014-01-07
上传用户：cuiyashuo
We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
标签： 传感器网络
上传时间： 2016-11-27
上传用户：xxmluo
％ [BestPop,Trace]=fmaxga(FUN,LB,UB,eranum,popsize,pcross,pmutation) ％ Finds a maximum of a function of several variables. ％ fmaxga solves problems of the form: ％ max F(X) subject to: LB <= X <= UB ％ BestPop--------最优的群体即为最优的染色体群 ％ Trace----------最佳染色体所对应的目标函数值 ％ FUN------------目标函数 ％ LB-------------自变量下限 ％ UB-------------自变量上限 ％ eranum---------种群的代数,取100--1000(默认1000) ％ popsize--------每一代种群的规模；此可取50--100(默认50) ％ pcross---------交叉的概率,此概率一般取0.5--0.85之间较好(默认0.8) ％ pmutation------变异的概率,该概率一般取0.05-0.2左右较好(默认0.1) ％ options--------1×2矩阵,options(1)=0二进制编码(默认0),option(1)~=0十进制编码,option(2)设定求解精度(默认1e-4)
标签： pmutation BestPop popsize maximum
上传时间： 2015-07-16
上传用户：Altman
Maximum Security (First Edition) 网络安全 英文版
标签： Security Maximum Edition First
上传时间： 2015-07-23
上传用户：c12228
Classify using the maximum-likelyhood algorithm
标签： maximum-likelyhood algorithm Classify using
上传时间： 2015-08-28
上传用户：日光微澜
by Jay Kadane。Input:a vector with floats.Output:the maximum submatrix.
标签： submatrix maximum Kadane Output
上传时间： 2015-10-13
上传用户：彭玖华
Maximum eigenvalue and the corresponding eigenvector.
标签： corresponding eigenvector eigenvalue Maximum
上传时间： 2015-10-30
上传用户：2525775
The computer program for the maximum entropy estimation of a wave distribution function
标签： distribution estimation computer function
上传时间： 2015-11-03
上传用户：lwwhust
Amis - A maximum entropy estimator 一个最大熵模型统计工具，采用特征进行模型构建
标签： estimator maximum entropy Amis
上传时间： 2013-12-16
上传用户：Zxcvbnm
