M
Mark J. Beran
Researcher at University of Pennsylvania
Publications - 12
Citations - 315
Mark J. Beran is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Coherence (signal processing) & Fourier transform. The author has an hindex of 8, co-authored 12 publications receiving 313 citations.
Papers
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Journal ArticleDOI
Propagation of the Fourth-Order Coherence Function in a Random Medium (a Nonperturbative Formulation)*
Mark J. Beran,T. L. Ho +1 more
TL;DR: In this article, a perturbation solution for propagation of the fourth-order coherence function in a random medium was proposed and extended to treat the propagation problem when the field fluctuations need not be small.
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Propagation of the Mutual Coherence Function Through Random Media
TL;DR: In this paper, an approximate solution for the development of the ensemble-averaged mutual-coherence function {Γ(x1,x2,τ)} as it propagates through statistically homogeneous and isotropic random media is given.
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Effective Electrical, Thermal and Magnetic Properties of Fiber Reinforced Materials:
TL;DR: In this article, the effective conductivity of a fiber reinforced material in terms of volume fractions and a geometric factor has been analyzed, and the results are simple algebraic expressions, such as 4 2 4 2 and 4 4 2.
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Beam Spread of Laser Light Propagating in a Random Medium
Alan M. Whitman,Mark J. Beran +1 more
TL;DR: In this paper, the beam spread of laser light when it propagates in a random medium is analyzed in terms of the coherence function and it is shown that the irradiance pattern is always gaussian and that the characteristic beam diameter increases at a rate proportional to z32, where z is the propagation distance.
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Propagation of a Finite Beam in a Random Medium
TL;DR: In this paper, a determinate equation is derived for the propagation of a finite beam of radiation in a random medium, where the radiation is described by a mutual coherence function and the analysis is restricted to beam diameters that are large compared to the characteristic correlation lengths in the random medium.