787 research outputs found
Use of spatial information in 2D SEMG array decomposition
A new feature extraction/classification method for High Density surface ElectroMyoGraphy (HD sEMG) Motor Unit Aciton Potential (MUAP) decomposition using 2D shape and energy distribution features is presented and experimentally tested.\u
Odyssey Towards a Sirenic Thinking: An Attempt at a Self-Criticism of the Listening Paradigm Within Sound Studies
This text departs from a contradictory claim in deaf studies and sound studies: both disciplines describe a hierarchical regime of the sensible – visuocentrism and audiocentrism – which they try to counter with conceptualisations as “acoustemology” or “deaf gain.” However, as we argue, they both thereby erect what they claim to overcome: a sensual regime that privileges one sense over another and a restricted conception of subjectivity deriving from it. First, we draw a philosophical line in the critique of sensual regimes. Then we propose a figure for the transcendence of the separation of the sensible: in re-reading of the myth of Odysseus and the sirens, we engage various examples from literature, art, and acoustics to describe sirens as a mythological and technical archetype of the transcendence of the sensual regime, as well as reified subjectivity. The question, then, is not how to escape the sirens, but how they can be approached. It is necessary, we argue, for sound studies to develop a critical self-consciousness of its own restricted concepts in order to move from sonic thinking towards a sirenic thinking
Logarithmically-concave moment measures I
We discuss a certain Riemannian metric, related to the toric Kahler-Einstein
equation, that is associated in a linearly-invariant manner with a given
log-concave measure in R^n. We use this metric in order to bound the second
derivatives of the solution to the toric Kahler-Einstein equation, and in order
to obtain spectral-gap estimates similar to those of Payne and Weinberger.Comment: 27 page
Data-driven efficient score tests for deconvolution problems
We consider testing statistical hypotheses about densities of signals in
deconvolution models. A new approach to this problem is proposed. We
constructed score tests for the deconvolution with the known noise density and
efficient score tests for the case of unknown density. The tests are
incorporated with model selection rules to choose reasonable model dimensions
automatically by the data. Consistency of the tests is proved
Maximizing the Conditional Expected Reward for Reaching the Goal
The paper addresses the problem of computing maximal conditional expected
accumulated rewards until reaching a target state (briefly called maximal
conditional expectations) in finite-state Markov decision processes where the
condition is given as a reachability constraint. Conditional expectations of
this type can, e.g., stand for the maximal expected termination time of
probabilistic programs with non-determinism, under the condition that the
program eventually terminates, or for the worst-case expected penalty to be
paid, assuming that at least three deadlines are missed. The main results of
the paper are (i) a polynomial-time algorithm to check the finiteness of
maximal conditional expectations, (ii) PSPACE-completeness for the threshold
problem in acyclic Markov decision processes where the task is to check whether
the maximal conditional expectation exceeds a given threshold, (iii) a
pseudo-polynomial-time algorithm for the threshold problem in the general
(cyclic) case, and (iv) an exponential-time algorithm for computing the maximal
conditional expectation and an optimal scheduler.Comment: 103 pages, extended version with appendices of a paper accepted at
TACAS 201
Quantum Process Tomography: Resource Analysis of Different Strategies
Characterization of quantum dynamics is a fundamental problem in quantum
physics and quantum information science. Several methods are known which
achieve this goal, namely Standard Quantum Process Tomography (SQPT),
Ancilla-Assisted Process Tomography (AAPT), and the recently proposed scheme of
Direct Characterization of Quantum Dynamics (DCQD). Here, we review these
schemes and analyze them with respect to some of the physical resources they
require. Although a reliable figure-of-merit for process characterization is
not yet available, our analysis can provide a benchmark which is necessary for
choosing the scheme that is the most appropriate in a given situation, with
given resources. As a result, we conclude that for quantum systems where
two-body interactions are not naturally available, SQPT is the most efficient
scheme. However, for quantum systems with controllable two-body interactions,
the DCQD scheme is more efficient than other known QPT schemes in terms of the
total number of required elementary quantum operations.Comment: 15 pages, 5 figures, published versio
Percolation in invariant Poisson graphs with i.i.d. degrees
Let each point of a homogeneous Poisson process in R^d independently be
equipped with a random number of stubs (half-edges) according to a given
probability distribution mu on the positive integers. We consider
translation-invariant schemes for perfectly matching the stubs to obtain a
simple graph with degree distribution mu. Leaving aside degenerate cases, we
prove that for any mu there exist schemes that give only finite components as
well as schemes that give infinite components. For a particular matching scheme
that is a natural extension of Gale-Shapley stable marriage, we give sufficient
conditions on mu for the absence and presence of infinite components
Condensation in randomly perturbed zero-range processes
The zero-range process is a stochastic interacting particle system that
exhibits a condensation transition under certain conditions on the dynamics. It
has recently been found that a small perturbation of a generic class of jump
rates leads to a drastic change of the phase diagram and prevents condensation
in an extended parameter range. We complement this study with rigorous results
on a finite critical density and quenched free energy in the thermodynamic
limit, as well as quantitative heuristic results for small and large noise
which are supported by detailed simulation data. While our new results support
the initial findings, they also shed new light on the actual (limited)
relevance in large finite systems, which we discuss via fundamental diagrams
obtained from exact numerics for finite systems.Comment: 18 pages, 6 figure
New distance measures for classifying X-ray astronomy data into stellar classes
The classification of the X-ray sources into classes (such as extragalactic
sources, background stars, ...) is an essential task in astronomy. Typically,
one of the classes corresponds to extragalactic radiation, whose photon
emission behaviour is well characterized by a homogeneous Poisson process. We
propose to use normalized versions of the Wasserstein and Zolotarev distances
to quantify the deviation of the distribution of photon interarrival times from
the exponential class. Our main motivation is the analysis of a massive dataset
from X-ray astronomy obtained by the Chandra Orion Ultradeep Project (COUP).
This project yielded a large catalog of 1616 X-ray cosmic sources in the Orion
Nebula region, with their series of photon arrival times and associated
energies. We consider the plug-in estimators of these metrics, determine their
asymptotic distributions, and illustrate their finite-sample performance with a
Monte Carlo study. We estimate these metrics for each COUP source from three
different classes. We conclude that our proposal provides a striking amount of
information on the nature of the photon emitting sources. Further, these
variables have the ability to identify X-ray sources wrongly catalogued before.
As an appealing conclusion, we show that some sources, previously classified as
extragalactic emissions, have a much higher probability of being young stars in
Orion Nebula.Comment: 29 page
Cutting edges at random in large recursive trees
We comment on old and new results related to the destruction of a random
recursive tree (RRT), in which its edges are cut one after the other in a
uniform random order. In particular, we study the number of steps needed to
isolate or disconnect certain distinguished vertices when the size of the tree
tends to infinity. New probabilistic explanations are given in terms of the
so-called cut-tree and the tree of component sizes, which both encode different
aspects of the destruction process. Finally, we establish the connection to
Bernoulli bond percolation on large RRT's and present recent results on the
cluster sizes in the supercritical regime.Comment: 29 pages, 3 figure
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