2,204 research outputs found
Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes
A method is provided for designing and training noise-driven recurrent neural
networks as models of stochastic processes. The method unifies and generalizes
two known separate modeling approaches, Echo State Networks (ESN) and Linear
Inverse Modeling (LIM), under the common principle of relative entropy
minimization. The power of the new method is demonstrated on a stochastic
approximation of the El Nino phenomenon studied in climate research
Mechanical Unfolding of a Simple Model Protein Goes Beyond the Reach of One-Dimensional Descriptions
We study the mechanical unfolding of a simple model protein. The Langevin
dynamics results are analyzed using Markov-model methods which allow to
describe completely the configurational space of the system. Using transition
path theory we also provide a quantitative description of the unfolding
pathways followed by the system. Our study shows a complex dynamical scenario.
In particular, we see that the usual one-dimensional picture: free-energy vs
end-to-end distance representation, gives a misleading description of the
process. Unfolding can occur following different pathways and configurations
which seem to play a central role in one-dimensional pictures are not the
intermediate states of the unfolding dynamics.Comment: 10 pages, 6 figure
Poisson transition rates from time-domain measurements with finite bandwidth
In time-domain measurements of a Poisson two-level system, the observed
transition rates are always smaller than those of the actual system, a general
consequence of finite measurement bandwidth in an experiment. This
underestimation of the rates is significant even when the measurement and
detection apparatus is ten times faster than the process under study. We derive
here a quantitative form for this correction using a straightforward
state-transition model that includes the detection apparatus, and provide a
method for determining a system's actual transition rates from
bandwidth-limited measurements. We support our results with computer
simulations and experimental data from time-domain measurements of
quasiparticle tunneling in a single-Cooper-pair transistor.Comment: 4 pages, 5 figure
Action Recognition in Videos: from Motion Capture Labs to the Web
This paper presents a survey of human action recognition approaches based on
visual data recorded from a single video camera. We propose an organizing
framework which puts in evidence the evolution of the area, with techniques
moving from heavily constrained motion capture scenarios towards more
challenging, realistic, "in the wild" videos. The proposed organization is
based on the representation used as input for the recognition task, emphasizing
the hypothesis assumed and thus, the constraints imposed on the type of video
that each technique is able to address. Expliciting the hypothesis and
constraints makes the framework particularly useful to select a method, given
an application. Another advantage of the proposed organization is that it
allows categorizing newest approaches seamlessly with traditional ones, while
providing an insightful perspective of the evolution of the action recognition
task up to now. That perspective is the basis for the discussion in the end of
the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4
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Systematic comparison of BIC-based speaker segmentation systems
Unsupervised speaker change detection is addressed in this paper. Three speaker segmentation systems are examined. The first system investigates the AudioSpectrumCentroid and the AudioWaveformEnvelope features, implements a dynamic fusion scheme, and applies the Bayesian Information Criterion (BIC). The second system consists of three modules. In the first module, a second-order statistic-measure is extracted; the Euclidean distance and the T2 Hotelling statistic are applied sequentially in the second module; and BIC is utilized in the third module. The third system, first uses a metric-based approach, in order to detect potential speaker change points, and then the BIC criterion is applied to validate the previously detected change points. Experiments are carried out on a dataset, which is created by concatenating speakers from the TIMIT database. A systematic performance comparison among the three systems is carried out by means of one-way ANOVA method and post hoc Tukey’s method
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