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A Unified Theory of Adaptive Subspace Detection. Part II: Numerical Examples
No full textThis paper is devoted to the performance analysis of the detectors proposed in the companion paper (Orlando et al., 2022) where a comprehensive design framework is presented for the adaptive detection of subspace signals. The framework addresses four variations on subspace detection: the subspace may be known or known only by its dimension; consecutive visits to the subspace may be unconstrained or they may be constrained by a prior probability distribution. In this paper, Monte Carlo simulations are used to compare the detectors derived in (Orlando et al., 2022) with estimate-and-plug (EP) approximations of the generalized likelihood ratio (GLR) detectors. Remarkably, some of the EP approximations appear here for the first time (at least to the best of the authors' knowledge). The numerical examples indicate that GLR detectors are effective for the detection of partially-known signals affected by inherent uncertainties due to the system or the operating environment. In particular, if the signal subspace is known, GLR detectors tend to ouperform EP detectors. If, instead, the signal subspace is known only by its dimension, the performance of GLR and EP detectors is very similar. Actually, there does not exist a general rule for recommending the first-order approach with respect to the second-order one and vice versa. Nevertheless, the analysis contains a specific case where the second-order detectors can outperform the first-order detectors
A Unified Theory of Adaptive Subspace Detection. Part I: Detector Designs
Get PDFThis paper addresses the problem of detecting multidimensional subspace
signals, which model range-spread targets, in noise of unknown covariance. It
is assumed that a primary channel of measurements, possibly consisting of
signal plus noise, is augmented with a secondary channel of measurements
containing only noise. The noises in these two channels share a common
covariance matrix, up to a scale, which may be known or unknown. The signal
model is a subspace model with variations: the subspace may be known or known
only by its dimension; consecutive visits to the subspace may be unconstrained
or they may be constrained by a prior distribution. As a consequence, there are
four general classes of detectors and, within each class, there is a detector
for the case where the scale between the primary and secondary channels is
known, and for the case where this scale is unknown. The generalized likelihood
ratio (GLR) based detectors derived in this paper, when organized with
previously published GLR detectors, comprise a unified theory of adaptive
subspace detection from primary and secondary channels of measurements
GLRT-Based Direction Detectors in Noise and Subspace Interference
No full textIn this paper we propose decision schemes to distinguish between the H 0 hypothesis that range cells under test contain disturbance only (i.e., noise plus interference) and the H 1 hypothesis that they also contain signal components along a direction which is a priori unknown, but constrained to belong to a given subspace 〈H〉 of the observables. The disturbance is modeled in terms of complex normal noise vectors plus deterministic interference assumed to belong to a known subspace 〈J〉 of the observables. At the design stage we resort to either the plain Generalized Likelihood Ratio Test (GLRT) or the two-step GLRT-based design procedure. Moreover, we assume that a set of noise only (secondary) data is available. A preliminary performance analysis, conducted by resorting to simulated data, shows that the one-step GLRT performs better than the two-step GLRT-based design procedure
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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