[PDF] Top 20 Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach - Part 2: The Under-Sampled Case
Has 10000 "Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach - Part 2: The Under-Sampled Case" found on our website. Below are the top 20 most common "Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach - Part 2: The Under-Sampled Case".
Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach - Part 2: The Under-Sampled Case
... independent complex Gaussian random vector ...of the p.d.f. of the texture is seldom available, the usual way is to treat the textures as unknown deterministic quantities and to carry ... Voir le document complet
12
Regularized Covariance Matrix Estimation in Complex Elliptically Symmetric Distributions Using the Expected Likelihood Approach - Part 1: The Over-Sampled Case
... Maximum Likelihood Ratio—Part I: Application to Antenna Array Detec- tion-Estimation With Perfect Wavefront Coherence,” IEEE ...multivariate complex Gaussian distribution, that the ... Voir le document complet
13
On the Expected Likelihood Approach for Assessment of Regularization Covariance Matrix
... Albeit the two mechanisms for generating are different, from a likelihood point of view the two representations are equivalent, as far as only assessment of from is ...course, in the ... Voir le document complet
6
Robust Markowitz mean-variance portfolio selection under ambiguous covariance matrix *
... In the above cited papers, the continuous-time Markowitz problem was essentially stu- died in the framework of a Black-Scholes model, and abundant research has been conducted to extend ... Voir le document complet
34
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula
... detection In order to illustrate the consequences of our results we shall present two ...examples. In the first one we are given data distributed according to the spiked Wigner model ... Voir le document complet
14
Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions
... probability distributions. The Wasserstein distance, initially inspired by Monge [1] and later by Kan- torovich [2] in a transport theory analogy, provides a natural notion of dissimilarity ... Voir le document complet
7
Exact Maximum Likelihood estimation for the BL-GARCH model under elliptical distributed innovations
... variance in non-linear time series is a challenging modelling exercise, con- sidered among many others things by Tong ...(1990). In particular, the stylized fact that the volatility of ... Voir le document complet
30
Knowledge-aided covariance matrix estimation and adaptive detection in compound-Gaussian noise
... with covariance matrix R R and the R k ’s are positive ...process. In this scenario, the problem of estimating the covariance matrix is generally ...sample ... Voir le document complet
7
A moment matrix approach to computing symmetric cubatures
... divided in three parts. With the help of the last algorithm in the previous section, we first provide a way to determine the existence for a given measure of cubatures of a given ... Voir le document complet
140
Joint Estimation of Location and Scatter in Complex Elliptical Distributions: A robust semiparametric and computationally efficient R-estimator of the shape matrix
... campaigns, the (Real or Complex) Elliptically Symmetric (ES) model has been recently adopted to characterize the statistical data ...behavior. The RES and CES models in ... Voir le document complet
25
On the Cramer Rao bound and maximum likelihood in passive time delay estimation for complex signals
... tributed as (x 1 (t), x 2 (t)) t ∈[−T/2,T/2] and circular if s(t) is circular. For real-valued x j (t), a well known theorem of statistics [7, Sec. 6.4] asserts that these Fourier coefficients ... Voir le document complet
5
Large N expansion of the 2-matrix model, multicut case.
... appearing in 2-matrix models and the associated Riemann-Hilbert problem”, preprint CRM-2852 (2002), Saclay T02/097, ...“Random Matrix Models and Their Applications”, MSRI Research ... Voir le document complet
34
Beef cattle methane emission estimation using the eddy covariance technique in combination with geolocation
... for the Spring 2014 campaign with each point corresponding to a 30-minute 315 measurement ...interval. The different regression lines correspond to the reduced major axis method (RMA), the ... Voir le document complet
30
Maximum likelihood estimation for Gaussian processes under inequality constraints
... Also, in practice, computing the cMLE requires a discretization of the constraints, for instance using a piecewise affine interpolation as in Section 5 , or a finite set of constrained ... Voir le document complet
32
Nonparametric estimation of the expected discounted penalty function in the compound Poisson model
... if the model selection procedures (18) for the Laguerre deconvolution estimators lead to the same performance than the naive choice m = b5T 1/10 ...results in Tables 1, 2 and 3. ... Voir le document complet
37
Controlling light in complex media beyond the acoustic diffraction-limit using the acousto-optic transmission matrix
... measure the AOTM 6 . To compensate for any slow phase drifts of the reference arm, a flat-phase mask was displayed on the SLM before each input mode was injected, and the phase of the ... Voir le document complet
11
Improved Estimation of the Distance between Covariance Matrices
... Terms— Covariance distance, random matrix the- ory, Fisher information ...between covariance matrices are objects of inter- est for many engineering applications, among which machine learning ... Voir le document complet
6
The L^2 –Alexander torsion is symmetric
... fQs 1 ; : : : ; Qs b ; cg defines an Euler structure K.e/ for N , which only depends on e. Put differently, we defined a map KW Eul.N; @N / ! Eul.N / which is easily seen to be H 1 .N /–equivariant. Given e 2 ... Voir le document complet
14
Cross-validation estimation of covariance parameters under fixed-domain asymptotics
... exponential covariance function. Under fixed-domain asymptotics, we prove the strong consistency and asymptotic normality of a cross validation estimator of the microergodic covariance ... Voir le document complet
44
Performance analysis of beamformers using generalized loading of the covariance matrix in the presence of random steering vector errors
... of the robust beamformer (4) in the case where and both and are ...Therefore, the analysis does not apply directly to [10]–[12], where the loading level depends on the ... Voir le document complet
8
Sujets connexes