In this paper, a blind detection method is proposed to evaluate the information that can be drawn from the received phase shift keying (PSK) signals without channel knowledge at the receiver. First, we develop a method to determine the decision regions for detecting PSK symbols based on the maximum a posterior (MAP) criterion. Then, to reduce the numerical complexity, an approximated MAP criter...

Mean Squared Error (MSE) has been the most widely used tool to solve the linear filter estimation or system identification problem. However, MSE gives biased results when the input signals are noisy. This paper presents a novel Error Whitening Criterion (EWC) to tackle the problem of linear system identification in the presence of additive white disturbances. We will motivate the theory behind ...

This paper discusses two novel non-iterative design procedures based on eigenfilters for designing broadband beamformers with an arbitrary spatial directivity pattern for an arbitrary microphone configuration. In the conventional eigenfilter technique a reference frequency-angle point is required, whereas in the eigenfilter technique based on a TLS (Total Least Squares) error criterion, no refe...

Ridge regression and the lasso are regularized versions of least squares regression using L2 and L1 penalties respectively, on the coefficient vector. To make these regressions more robust we may replace least squares with Huber’s criterion which is a hybrid of squared error (for relatively small errors) and absolute error (for relatively large ones). A reversed version of Huber’s criterion can...

The performances of the seven different parameter estimation methods for the Gumbel distribution are compared with numerical simulations. Estimation methods used in this study are the method of moments (ME), the method of maximum likelihood (ML), the method of modified maximum likelihood (MML), the method of least squares (LS), the method of weighted least squares (WLS), the method of percentil...

Adaptive thinning algorithms are greedy point removal schemes for bivariate scattered data sets with corresponding function values, where the points are recursively removed according to some data-dependent criterion. Each subset of points, together with its function values, defines a linear spline over its Delaunay triangulation. The basic criterion for the removal of the next point is to minim...

This paper is devoted to the analysis of a “semi-blind” estimation framework in which the standard input-output (training sequence based) estimation is enhanced by using the statistical structure of the information sequence. More specifically, we consider the case of a general TDMA frame-based receiver equipped with multiple sensors, and restrict our attention to second-order based subspace met...

We have recently proposed a new maximum likelihood approach for separating multiple co-channel digital signals received at an antenna array. This approach exploits the-nite alphabet property of digital signals to simultaneously estimate the array response matrix A and symbol matrix S, given the data matrix X = AS. In 1, 2], we presented two eecient block algorithms for computing the estimates: ...

We investigate the predictive ability of the accumulated prediction error (APE) of Rissanen in an infinite-order autoregressive (AR(∞)) model. Since there are infinitely many parameters in the model, all finite-order AR models are misspecified. We first show that APE is asymptotically equivalent to Bayesian information criterion (BIC) and is not asymptotically efficient in the misspecified case...

Homogeneity analysis is a technique for making graphical representations of categorical multivariate data sets. Such data sets can also be represented by the adjacency matrix of a bipartite graph. Homogeneity analysis optimizes a weighted least-squares criterion and the optimal graph layout is computed by an alternating least squares algorithm. Heiser Comput. Statist. Data Anal. (1987) 337, loo...