34,432 research outputs found
Regularization of statistical inverse problems and the Bakushinskii veto
In the deterministic context Bakushinskii's theorem excludes the existence of
purely data driven convergent regularization for ill-posed problems. We will
prove in the present work that in the statistical setting we can either
construct a counter example or develop an equivalent formulation depending on
the considered class of probability distributions. Hence, Bakushinskii's
theorem does not generalize to the statistical context, although this has often
been assumed in the past. To arrive at this conclusion, we will deduce from the
classic theory new concepts for a general study of statistical inverse problems
and perform a systematic clarification of the key ideas of statistical
regularization.Comment: 20 page
Sampled signal reconstruction via H2 optimization
In this paper the sampled signal reconstruction problem is formulated and solved as the sampled-data H2 smoothing problem. Both infinite (non-causal reconstructor) and finite (reconstructor with relaxed causality) preview cases are considered. The optimal reconstructors are in the form of the cascade of a discrete-time smoother and a generalized hold (interpolator). In the particular case of reconstructing polynomial signals with infinite preview, the proposed procedure recovers the cardinal B-spline reconstructors
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Phase-space formulation of quantum mechanics and quantum state reconstruction for physical systems with Lie-group symmetries
We present a detailed discussion of a general theory of phase-space
distributions, introduced recently by the authors [J. Phys. A {\bf 31}, L9
(1998)]. This theory provides a unified phase-space formulation of quantum
mechanics for physical systems possessing Lie-group symmetries. The concept of
generalized coherent states and the method of harmonic analysis are used to
construct explicitly a family of phase-space functions which are postulated to
satisfy the Stratonovich-Weyl correspondence with a generalized traciality
condition. The symbol calculus for the phase-space functions is given by means
of the generalized twisted product. The phase-space formalism is used to study
the problem of the reconstruction of quantum states. In particular, we consider
the reconstruction method based on measurements of displaced projectors, which
comprises a number of recently proposed quantum-optical schemes and is also
related to the standard methods of signal processing. A general group-theoretic
description of this method is developed using the technique of harmonic
expansions on the phase space.Comment: REVTeX, 18 pages, no figure
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