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mntabassm/SAEN-LARS: Zenodo
No full text<p>Package Repository | <em>SAEN-LARS</em> </p>
<ul>
<li><strong>Version</strong>: 1.0.0</li>
<li><strong>Title</strong>: Sequential Adaptive Elastic Net Approach for Single-snapshot Source Localization</li>
<li><strong>Short Title</strong>: <em>Sequential Adaptive Elastic Net</em></li>
<li><strong>Authors</strong>: Muhammad Naveed Tabassum and Esa Ollila</li>
<li><strong>Maintainer</strong>: Muhammad Naveed Tabassum</li>
<li><strong>Date</strong>: 19.03.2018</li>
</ul>
<p>Introduction</p>
<p>The MATLAB package <strong><em>SAEN-LARS</em></strong> provides an implementation of three algorithms proposed in our paper, titled: <em>"Sequential Adaptive Elastic Net Approach for Single-snapshot Source Localization"</em>.</p>
<p>In above paper and accordingly in this package, <em>sequential adaptive elastic net (SAEN)</em> approach applies the complex-valued pathwise method in the weighted elastic-net framework, named as <em>c-PW-WEN</em>, sequentially by decreasing the sparsity level (order) from 3K to K in three stages. SAEN utilizes smartly chosen adaptive (i.e., data dependent) weights that are based on solutions obtained in the previous stage. c-PW-WEN algorithm computes the WEN solution paths for different values of EN tuning parameter and then selects the best solution. To achieve this in a computationally efficient way, we develop a homotopy method that is a complex-valued extension of the least angle regression and shrinkage (LARS) algorithm for weighted Lasso problem, which we refer to as <em>c-LARS-WLasso</em>. It is numerically cost effective and avoids an exhaustive grid-search over candidate values of the regularization parameter.</p>
<p>NOTE: The c-PW-WEN algorithm contains</p>
<ul>
<li> both Lasso and EN as special cases for unity weights.</li>
<li> contains both adaptive Lasso and adaptive EN as special cases for data dependent weights.</li>
</ul>
<p>Demo | Example</p>
<p>The package contains a simple demo (Demo.mlx) that explains the usage of algorithms for direction-of-arrival (DoA) estimation with a uniform linear array (ULA) in compressed beamforming (CBF) application.<br>
Moreover, an example (Example.m) for set-up 4 in the paper is also included in the package. To have repeatable results, the pseudorandom number generator settings, in terms of seed and type, are provided along with scenario data in the package as 'seed_data.mat'.</p>
<p>Download | Usage</p>
<p>The <em>SAEN-LARS</em> package contains following files:</p>
<p><strong>README</strong>: This file.</p>
<p><strong>Functions</strong>: Function files for implementation of three algorithms proposed in the paper.</p>
<blockquote>
<ul>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/saen.m">saen.m</a></em>: The main function, sequential adaptive elastic net (SAEN) approach.</li>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/cpwwen.m">cpwwen.m</a></em>: Auxiliary function, called by the main function three times.</li>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/clarswlasso.m">clarswlasso.m</a></em>: Auxiliary function for finding knots and respective solutions at found knots.</li>
</ul>
</blockquote>
<p><strong>Usage</strong>: The files for the demo and an example.</p>
<blockquote>
<ul>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/Demo.mlx">Demo.mlx</a></em>: A live script demo.</li>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/Example.m">Example.m</a></em>: An example for DoA estimation with a ULA in CBF application.</li>
<li><em><a href="https://github.com/mntabassm/SAEN-LARS/blob/master/seed_data.mat">seed_data.mat</a></em>: Scenario data and pseudorandom number generator settings.</li>
</ul>
</blockquote>
<p>Download the package and extract the files into a folder with “full control” permission.<br>
Set the MATLAB home directory to the above folder. Thereafter, open either 'Demo.mlx' or 'Example.m' file in MATLAB and follow the steps.</p>
<ul>
</ul>
mntabassm/SAEN-LARS: Zenodo
No full textSequential adaptive elastic net (SAEN) approach, complex-valued LARS method in weighted Lasso/elastic-net framework, and sparsity (or model) order detection with an application to single-snapshot source localization
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Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
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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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