BU Open Access Articles
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The Boston University Open Access Articles collection contains scholarly publications written by Boston University faculty. This collection primarily consists of scholarly journal articles and published conference proceedings but open access book chapters, reviews, white papers, conference abstracts, and technical reports are also included. These publications are made available in OpenBU, Boston University’s Open Access Institutional Repository under the provisions of the Boston University Open Access Policy or by other arrangement. Note: Some works in this collection are not currently in open access, and are embargoed at the author's request.
Publications in Boston University’s Open Access collection are primarily one of three versions:
- First Author Draft. This is the author's manuscript prior to formal peer review.
- Accepted Manuscript. This is the version that exists after peer review, but before final copy editing and publisher formatting. Note: This is NOT publisher proofs.
- Published Version. This is the final version that appeared in a formal publication such as a peer-reviewed journal, book, or published conference proceeding.
Citations are always given to the final published version, which may differ from the version made available in the repository. Wherever possible, a link or DOI to the final version is provided.
For more information please see the FAQ about Open Access at BU or contact Digital Scholarship Services at disc@bu.edu.
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BU Open Access Articles [3934]
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Necessary and sufficient conditions for sparsity pattern recovery
(Institute of Electrical and Electronics Engineers (IEEE), 2009-12)The paper considers the problem of detecting the sparsity pattern of a k -sparse vector in \BBR n from m random noisy measurements. A new necessary condition on the number of measurements for asymptotically reliable detection ... -
Supply chain network structure and environmental information disclosure
(2019-07-18)Recognizing that supply network structure has implications for a focal firm’s ability to access environmental information embedded in its supply network, this paper draws on structural, environmental, and financial data ... -
Two places for causees in productive isiXhosa morphological causatives
(Wiley, 2021-03)Productive morphological causatives in isiXhosa exhibit a case alternation regarding the causee, which can be unmarked or instrumental. Much recent literature on similar alternations in causative constructions in other ... -
Macro-financial volatility under dispersed information
(2021-01)We provide a production-based asset pricing model with dispersed information and small deviations from full rational expectations. In the model, aggregate output and equity prices depend on the higher-order beliefs about ... -
On-off random access channels: a compressed sensing framework
(2009)This paper considers a simple on-off random multiple access channel, where n users communicate simultaneously to a single receiver over m degrees of freedom. Each user transmits with probability 𝛌, where typically 𝛌n < ... -
Time-resolved focused ion beam microscopy: modeling, estimation methods, and analyses
(2021)In a focused ion beam (FIB) microscope, source particles interact with a small volume of a sample to generate secondary electrons that are detected, pixel by pixel, to produce a micrograph. Randomness of the number of ... -
Differential effects of anesthetics on resting state functional connectivity in the mouse
(2020-04)Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard approach to examine resting state functional connectivity (RSFC), but fMRI in animal models is challenging. Recently, functional optical intrinsic ... -
Nonlinear digital post-processing to mitigate jitter in sampling
(2018)This paper describes several new algorithms for estimating the parameters of a periodic bandlimited signal from samples corrupted by jitter (timing noise) and additive noise. Both classical (non-random) and Bayesian ... -
SWAGGER: sparsity within and across groups for general estimation and recovery
(2020)Penalty functions or regularization terms that promote structured solutions to optimization problems are of great interest in many fields. Proposed in this work is a nonconvex structured sparsity penalty that promotes ...
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