109,871 research outputs found
Reference-less measurement of the transmission matrix of a highly scattering material using a DMD and phase retrieval techniques
This paper investigates experimental means of measuring the transmission
matrix (TM) of a highly scattering medium, with the simplest optical setup.
Spatial light modulation is performed by a digital micromirror device (DMD),
allowing high rates and high pixel counts but only binary amplitude modulation.
We used intensity measurement only, thus avoiding the need for a reference
beam. Therefore, the phase of the TM has to be estimated through signal
processing techniques of phase retrieval. Here, we compare four different phase
retrieval principles on noisy experimental data. We validate our estimations of
the TM on three criteria : quality of prediction, distribution of singular
values, and quality of focusing. Results indicate that Bayesian phase retrieval
algorithms with variational approaches provide a good tradeoff between the
computational complexity and the precision of the estimates
Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data
Mathematical and Physical Sciences: 3rd Place (The Ohio State University Edward F. Hayes Graduate Research Forum)In many applications, smooth processes generate data that is recorded under a variety of observation regimes, such as dense sampling and sparse or fragmented observations that are often contaminated with error. The statistical goal of registering and estimating the individual underlying functions from discrete observations has thus far been mainly approached sequentially without formal uncertainty propagation, or in an application-specific manner by pooling information across subjects. We propose a unified Bayesian framework for simultaneous registration and estimation, which is flexible enough to accommodate inference on individual functions under general observation regimes. Our ability to do this relies on the specification of strongly informative prior models over the amplitude component of function variability. We provide two strategies for this critical choice: a data-driven approach that defines an empirical basis for the amplitude subspace based on available training data, and a shape-restricted approach when the relative location and number of local extrema is well-understood. The proposed methods build on the elastic functional data analysis framework to separately model amplitude and phase variability inherent in functional data. We emphasize the importance of uncertainty quantification and visualization of these two components as they provide complementary information about the estimated functions. We validate the proposed framework using simulation studies, and real applications to estimation of fractional anisotropy profiles based on diffusion tensor imaging measurements, growth velocity functions and bone mineral density curves.No embarg
Sampling Distributions of Random Electromagnetic Fields in Mesoscopic or Dynamical Systems
We derive the sampling probability density function (pdf) of an ideal
localized random electromagnetic field, its amplitude and intensity in an
electromagnetic environment that is quasi-statically time-varying statistically
homogeneous or static statistically inhomogeneous. The results allow for the
estimation of field statistics and confidence intervals when a single spatial
or temporal stochastic process produces randomization of the field. Results for
both coherent and incoherent detection techniques are derived, for Cartesian,
planar and full-vectorial fields. We show that the functional form of the
sampling pdf depends on whether the random variable is dimensioned (e.g., the
sampled electric field proper) or is expressed in dimensionless standardized or
normalized form (e.g., the sampled electric field divided by its sampled
standard deviation). For dimensioned quantities, the electric field, its
amplitude and intensity exhibit different types of
Bessel sampling pdfs, which differ significantly from the asymptotic
Gauss normal and ensemble pdfs when is relatively
small. By contrast, for the corresponding standardized quantities, Student ,
Fisher-Snedecor and root- sampling pdfs are obtained that exhibit
heavier tails than comparable Bessel pdfs. Statistical uncertainties
obtained from classical small-sample theory for dimensionless quantities are
shown to be overestimated compared to dimensioned quantities. Differences in
the sampling pdfs arising from de-normalization versus de-standardization are
obtained.Comment: 12 pages, 15 figures, accepted for publication in Phys. Rev. E, minor
typos correcte
Introduction to Random Signals and Noise
Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals.\ud
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Key features:\ud
âą Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains.\ud
âą Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver.\ud
âą Examines optimal filtering methods and their consequences.\ud
âą Presents a detailed discussion of the topic of Poisson processed and shot noise.\u
Finite-size scaling properties of random transverse-field Ising chains : Comparison between canonical and microcanonical ensembles for the disorder
The Random Transverse Field Ising Chain is the simplest disordered model
presenting a quantum phase transition at T=0. We compare analytically its
finite-size scaling properties in two different ensembles for the disorder (i)
the canonical ensemble, where the disorder variables are independent (ii) the
microcanonical ensemble, where there exists a global constraint on the disorder
variables. The observables under study are the surface magnetization, the
correlation of the two surface magnetizations, the gap and the end-to-end
spin-spin correlation for a chain of length . At criticality, each
observable decays typically as in both ensembles, but the
probability distributions of the rescaled variable are different in the two
ensembles, in particular in their asymptotic behaviors. As a consequence, the
dependence in of averaged observables differ in the two ensembles. For
instance, the correlation decays algebraically as 1/L in the canonical
ensemble, but sub-exponentially as in the microcanonical
ensemble. Off criticality, probability distributions of rescaled variables are
governed by the critical exponent in both ensembles, but the following
observables are governed by the exponent in the microcanonical
ensemble, instead of the exponent in the canonical ensemble (a) in the
disordered phase : the averaged surface magnetization, the averaged correlation
of the two surface magnetizations and the averaged end-to-end spin-spin
correlation (b) in the ordered phase : the averaged gap. In conclusion, the
measure of the rare events that dominate various averaged observables can be
very sensitive to the microcanonical constraint.Comment: 24 page
Lower Bound on the Capacity of Continuous-Time Wiener Phase Noise Channels
A continuous-time Wiener phase noise channel with an integrate-and-dump
multi-sample receiver is studied.
A lower bound to the capacity with an average input power constraint is
derived, and a high signal-to-noise ratio (SNR) analysis is performed.
The capacity pre-log depends on the oversampling factor, and amplitude and
phase modulation do not equally contribute to capacity at high SNR.Comment: Extended version of a paper submitted to ISIT 2015. 9 pages and 1
figure. arXiv admin note: text overlap with arXiv:1411.039
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