13,375 research outputs found
A pseudo-matched filter for chaos
A matched filter maximizes the signal-to-noise ratio of a signal. In the
recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is
derived for the chaotic waveforms produced by a piecewise-linear system.
Motivated by these results, we describe a pseudo-matched filter, which removes
noise from the same chaotic signal. It consists of a notch filter followed by a
first-order, low-pass filter. We compare quantitatively the matched filter's
performance to that of our pseudo-matched filter using correlation functions in
a simulated radar application. On average, the pseudo-matched filter performs
with a correlation signal-to-noise ratio that is 2.0 dB below that of the
matched filter. Our pseudo-matched filter, though somewhat inferior in
comparison to the matched filter, is easily realizable at high speed (> 1 GHz)
for potential radar applications
Exploring multimodal data fusion through joint decompositions with flexible couplings
A Bayesian framework is proposed to define flexible coupling models for joint
tensor decompositions of multiple data sets. Under this framework, a natural
formulation of the data fusion problem is to cast it in terms of a joint
maximum a posteriori (MAP) estimator. Data driven scenarios of joint posterior
distributions are provided, including general Gaussian priors and non Gaussian
coupling priors. We present and discuss implementation issues of algorithms
used to obtain the joint MAP estimator. We also show how this framework can be
adapted to tackle the problem of joint decompositions of large datasets. In the
case of a conditional Gaussian coupling with a linear transformation, we give
theoretical bounds on the data fusion performance using the Bayesian Cramer-Rao
bound. Simulations are reported for hybrid coupling models ranging from simple
additive Gaussian models, to Gamma-type models with positive variables and to
the coupling of data sets which are inherently of different size due to
different resolution of the measurement devices.Comment: 15 pages, 7 figures, revised versio
Process operating mode monitoring : switching online the right controller
This paper presents a structure which deals with
process operating mode monitoring and allows the control law reconfiguration
by switching online the right controller. After a short
review of the advances in switching based control systems during
the last decade, we introduce our approach based on the definition
of operating modes of a plant. The control reconfiguration
strategy is achieved by online selection of an adequate controller,
in a case of active accommodation. The main contribution lies
in settling up the design steps of the multicontroller structure
and its accurate integration in the operating mode detection and
accommodation loop. Simulation results show the effectiveness
of the operating mode detection and accommodation (OMDA)
structure for which the design steps propose a method to study the
asymptotic stability, switching performances improvement, and
the tuning of the multimodel based detector
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