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ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
least_square_estimation_model_select
- 生成一组带有高斯噪声的样本,分别用一阶,二阶,三阶的最小二乘估计方法进行拟合,然后分别用AIC,MDL,FPE,CAT四种评测模型对其性能进行比较,得到最优的拟合模型.
deternum1
- AIC AND MDL 算法，输入为特征值
AIC_MDL_or
- estimate the number of source using AIC and MDL criterion.
MDLAIC
- 在MATLAB环境下开发的基于AIC和MDL准则的远场入射新号的数目估计，估计准确度都很高，仿真效果理想-Developed under the MATLAB environment, based on AIC and MDL criteria for the far-field incident estimated number of new numbers, it is estimated have a high accuracy, simulation results are satisf
xinyuanshumu
- 阵列信号的信源数目估计——AIC，MDL，HQ，EDC法得比较-Array signal source number estimation- AIC, MDL, HQ, EDC method comparatively
Source_No_AIC_MDL_HQ_Prob_vs_SNR_ULA
- <空间谱估计理论与算法> 信号源个数估计 AIC MDL HQ 算法-spatial spectrum estimation source number estimation AIC MDL HQ
ddbmusic
- 不同信噪比下，利用MUSIC算法实现AIC,MDL,HQ,EDC-Different signal to noise ratio, the use of MUSIC algorithm AIC, MDL, HQ, EDC
DOA_zhunze
- DOA信号源估计，包含利用AIC,MDL,EDC,HQ四种准则，对于DOA估计的编程相当有用！malab程序验证-
source-number-estimation
- 源信号数目估计MATLAB程序，包括IAIC,AIC,MDL,IMDL，MEVARC等5种算法，可得到5种算法在不同信噪比条件下的估计准确率性能曲线。-The number of source signals to estimate the MATLAB program, including five kinds of IAIC, AIC, MDL, IMDL, MEVARC algorithm available algorithms estimated accuracy in differe
estimate_object_number_e.tar
- 该程序基于2D特征点的移动轨迹,估计独立运动的对象数目.-Given 2D trajectories of feature points moving in the image frame, this program estimates the number of independent motions using model selection by the geometric AIC (default) or the geometric MDL (option) based
dsp
- 随机过程： ，其中 是均值为零、方差为1的白噪声， 、 是相互独立并在 上服从均匀分布的随机相位。采用AIC和MDL准则估计信号源个数，并且画出相应的MUSIC频率估计谱线。 要求：信号样本数为1000，估计的自相关矩阵为8阶。 -Stochastic process: where is zero mean and variance 1 white noise, are independent and uniformly distributed on a random phase. Es
MUSIC
- 负正弦加白噪声随机过程下使用MUSIC方法进行信号频率估计仿真，信号样本数去1000，估计的自相关矩阵为8阶，分别采用AIC和MDL准则估计信号源个数，并画出相应的MUSIC频率估计谱线。-Negative sine plus white noise random process method using MUSIC frequency estimation simulation, signal samples to 1000, the estimated autocorrelation mat
AICandMDL
- 经典的信息论准则估计信号源个数。 使用空间谱估计理论，模拟发射信号由天线阵列接受采样。经过AIC和MDL两种算法，估计出采样序列中信号的个数，所加噪声是白噪声。-Classical information theory for sources number estimation. It s spatial spectrum estimation theory. it analogs transmission signal from the antenna array . It uses tw
MUSIC
- （1）采用AIC和MDL准则估计信号源个数； （2）根据（1）中信源个数画出相应的MUSIC频率估计谱线。 -(1) using the AIC and MDL sources estimate the number of criteria (2) according to (1) the number of sources of CITIC MUSIC draw the corresponding frequency spectrum estimation.
AIC
- 1. 随机过程： ，其中 是均值为零、方差为1的白噪声， 、 是相互独立并在 上服从均匀分布的随机相位。采用AIC和MDL准则估计信号源个数，并且画出相应的MUSIC频率估计谱线。 要求：信号样本数为1000，估计的自相关矩阵为8阶。 分析：利用AIC准则和MDL准则算出信号源个数，然后根据算出的信号源个数计算出MUSIC谱。 -AIC criteria and guidelines for the use of MDL calculates the number of signal
Desktop
- AIC和MDL标准和使用来源的估计数从而得出相应的估计频谱MUSIC,使用信号频率估计仿真MUSIC方法- MUSIC method using the signal frequency estimation simulation: AIC and MDL criteria and using the estimated number of sources thus draw the corresponding estimate frequency spectrum MUSIC
AIC-MDL-GDE
- 用AIC MDL GDE等方法估计源信号个数，并进行性等分析在白噪声和色噪声环境下-estimate the number of source signal using AIC MDL GDE
AIC_MDL
- AIC & MDL The Akaike information criterion (AIC) is a measure of the relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other m
aic
- 基于信息论准则条件下的信源个数估计，AIC,MDL,HQ准则-this is used to estimate number of sources,AIC,MDL,HQ