In this paper we formulate a general class of problems for detecting subspace signals in subspace interference and broadband noise. We derive the generalized likelihood ratio (GLR) for each problem in the class. We then establish the invariances for the GLR and argue that these are the natural invariances for the problem. In each case, the GLR is a maximal invariant statistic, and the distribut...

To deal with the problem of sensitivity to noise in semi-supervised learning for biometrics, this paper proposes a robust Gaussian-Laplacian Regularized (GLR) framework based on maximum correntropy criterion (MCC), called GLR-MCC, along with its convergence analysis. The half quadratic (HQ) optimization technique is used to simplify the correntropy optimization problem to a standard semi-superv...

in this paper a new algorithm is presented for coherent radar detection of targets, when distribution of the interference (clutter and noise) is non-gaussian. the neyman-pearson criterion is used for optimal detection and several successive received samples from a radar range cell are used for detection in the same cell. on the basis of recent empirical evidences, the interference distribution ...

An extension of the well-known probabilistic neural network (PNN) to generalized locally recurrent PNN (GLR PNN) is introduced. The GLR PNN is derived from the original PNN by incorporating a fully connected recurrent layer between the pattern and output layers. This extension renders GLR PNN sensitive to the context in which events occur, and therefore, capable of identifying temporal and spat...

This paper addresses a target detection problem in radar imaging for which the covariance matrix of unknown Gaussian clutter has block diagonal structure. This block diagonal structure is the consequence of a target lying along a boundary between two statistically independent clutter regions. Here, we design adaptive detection algorithms using both the generalized likelihood ratio (GLR) and the...

Glycine (Gly) residues are particularly susceptible to hydrogen abstraction; which results in the formation of the capto-dative stabilized Cα-centered Gly radical (GLR) on the protein backbone. We examined the effect of GLR formation on the structure of the Trp cage; tryptophan zipper; and the villin headpiece; three fast-folding and stable miniproteins; using all-atom (OPLS-AA) molecular dynam...

The generalized likelihood ratio (GLR) test is a widely used method for detecting abrupt changes in linear systems and signals. In this paper the marginalized likelihood ratio (MLR) test is introduced for eliminating three shortcomings of GLR, while preserving its applicability and generality. Firstly, the need for a user-chosen threshold is eliminated in MLR. Secondly, the noise levels need no...

The code generator in a compiler attempts to match a subject tree against a collection of tree-shaped patterns for generating instructions. Tree-pattern matching may be considered as a generalization of string parsing. We propose a new generalized LR (GLR) parser, which extends the LR parser stack with a parser cactus. GLR explores all plausible parsing steps to find the least-cost matching. GL...

| The generalized likelihood ratio (GLR) test is a widely used method for detecting abrupt changes in linear systems and signals. In this paper the marginalized likelihood ratio (MLR) test is introduced for eliminating three shortcomings of GLR, while preserving its applicability and generality. Firstly, the need for a user-chosen threshold is eliminated in MLR. Secondly, the noise levels need ...