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Mathematical Analysis of Random Noise-Conclusion
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This article is published in Bell System Technical Journal.The article was published on 1945-01-01 and is currently open access. It has received 807 citations till now.read more
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Configurational and dynamic flexibility of polymer chains
M.G. Brereton,A. Rusli +1 more
TL;DR: The frequency of collisions between the end-groups of a polymer molecule is a useful measure of the dynamic flexibility of the molecule and an exact expression for this quantity is given in terms of the various distribution functions which characterize the polymer and the result compared with the experiments of Szwarc et al. as discussed by the authors on polymethylene chains in solution.
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A combined-alpha-shape-implicit-surface approach to generate 3D random concrete mesostructures via digital image processing, spectral representation, and point cloud
TL;DR: In this paper, the authors presented a numerical procedure for the stochastic characterization and representation of the aggregates and micro-cracks in concrete and the generation of virtual 3D random concrete mesostructures.
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Temporal phase correction of multiple echo T2 magnetic resonance images
TL;DR: In this paper, a temporal phase correction (TPC) algorithm was proposed to exploit the temporal noise information available in multiple echo T2 acquisitions to put the relevant decay information in the Real portion of the decay data and leave only noise in the Imaginary portion.
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Detecting gravitational waves from inspiraling binaries with a network of detectors: Coherent versus coincident strategies
H. Mukhopadhyay,Norichika Sago,Norichika Sago,Hideyuki Tagoshi,Sanjeev Dhurandhar,Hirotaka Takahashi,Nobuyuki Kanda +6 more
TL;DR: In this article, the authors compare two strategies of multidetector detection of compact binary inspiral signals, namely, the coincidence and the coherent, and conclude that the coherent strategy is superior to the coincidence strategy.
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Wave statistics in non-linear random sea
TL;DR: In this article, the sea elevation at a fixed point is modeled as a sum of a Gaussian process plus a quadratic random correction term, and the process can also be expressed as a vector-valued Gaussian Process with arbitrary mean.