Author
R. B. Nottingham
Bio: R. B. Nottingham is an academic researcher. The author has contributed to research in topics: Folded normal distribution & Chi distribution. The author has an hindex of 1, co-authored 1 publications receiving 344 citations.
Papers
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TL;DR: In this paper, the authors describe methods for estimating the mean and standard deviation of the normal distribution based on estimates of the estimated mean and the standard deviation determined from the folded normal.
Abstract: Measurements are frequently recorded without their algebraic sign. As a consequence, the underlying distribution of measurements is replaced by a distribution of absolute measurements. When the underlying distribution is normal, the resulting distribution is called the “folded normal distribution”. The authors describe methods for estimating the mean and standard deviation of the normal distribution based on estimates of the mean and standard deviation determined from the folded normal. Tables are provided to assist in the estimation procedure and an example included.
364 citations
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TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Abstract: Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as opposed to the usual m pixel samples. More specifically, suppose x has a sparse representation in some orthonormal basis (e.g., wavelet, Fourier) or tight frame (e.g., curvelet, Gabor)-so the coefficients belong to an lscrp ball for 0
18,609 citations
TL;DR: In this article, the authors survey and critically comment on some basic concepts and notions relevant to the methodology dealing with process capability indices (PCI's), focusing on distributional and inferential aspects.
Abstract: In this paper we survey and critically comment on some basic concepts and notions relevant to the methodology dealing with process capability indices (PCI's). The emphasis is on distributional and inferential aspects. The intent is to contribute to the ..
634 citations
01 Nov 2007
TL;DR: This paper considers an aggregated channel model which takes into account both path-loss and turbulence-induced log-normal fading in free-space optical systems operating in atmospheric turbulence channels and derived closed form expressions for outage probability of the relaying schemes under consideration.
Abstract: In this paper, we present relay-assisted transmission as a powerful fading mitigation tool for free-space optical systems operating in atmospheric turbulence channels. We study both serial (i.e., multi-hop transmission) and parallel (i.e., cooperative diversity) relaying encoupled with amplify-and-forward and decode-and-forward modes. We consider an aggregated channel model which takes into account both path-loss and turbulence-induced log-normal fading. Since fading variance is distance-dependent in free-space optical systems, relay-assisted transmission takes advantage of the resulting shorter hops and yields significant performance improvements. We derive outage probability of the relaying schemes under consideration which are further confirmed through Monte-Carlo simulations. Our outage probability analysis demonstrates that an impressive performance improvement of 18.5 dB is possible with the use of a single relay at a target outage probability of 10-6.
549 citations
TL;DR: The overlapping coefficient as discussed by the authors is defined as a measure of the agreement between two probability distributions, and its relationship to the dissimilarity index and its propertie are described in detail.
Abstract: The overlapping coefficient is defined as a measure of the agreement between two probability distributions. Its relationship to the dissimilarity index and its propertie are described. An extensive treatment of maximum-likelihood estimation of the overlap between two normal distributions is presented as an example of estimating the overlapping coefficient from sample data.
322 citations
TL;DR: In this article, an alternative closed-form general equilibrium model of the term structure within the Cox, Ingersoll, and Ross theoretical framework in which yields are nonlinear functions of the risk-free rate was derived.
251 citations