134,196 research outputs found
Optimal experiment design in a filtering context with application to sampled network data
We examine the problem of optimal design in the context of filtering multiple
random walks. Specifically, we define the steady state E-optimal design
criterion and show that the underlying optimization problem leads to a second
order cone program. The developed methodology is applied to tracking network
flow volumes using sampled data, where the design variable corresponds to
controlling the sampling rate. The optimal design is numerically compared to a
myopic and a naive strategy. Finally, we relate our work to the general problem
of steady state optimal design for state space models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS283 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Selection of sampling rate for digital control of aircrafts
The considerations in selecting the sample rates for digital control of aircrafts are identified and evaluated using the optimal discrete method. A high performance aircraft model which includes a bending mode and wind gusts was studied. The following factors which influence the selection of the sampling rates were identified: (1) the time and roughness response to control inputs; (2) the response to external disturbances; and (3) the sensitivity to variations of parameters. It was found that the time response to a control input and the response to external disturbances limit the selection of the sampling rate. The optimal discrete regulator, the steady state Kalman filter, and the mean response to external disturbances are calculated
Stochastic Digital Backpropagation with Residual Memory Compensation
Stochastic digital backpropagation (SDBP) is an extension of digital
backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP
takes into account noise from the optical amplifiers in addition to handling
deterministic linear and nonlinear impairments. The decisions in SDBP are taken
on a symbol-by-symbol (SBS) basis, ignoring any residual memory, which may be
present due to non-optimal processing in SDBP. In this paper, we extend SDBP to
account for memory between symbols. In particular, two different methods are
proposed: a Viterbi algorithm (VA) and a decision directed approach. Symbol
error rate (SER) for memory-based SDBP is significantly lower than the
previously proposed SBS-SDBP. For inline dispersion-managed links, the VA-SDBP
has up to 10 and 14 times lower SER than DBP for QPSK and 16-QAM, respectively.Comment: 7 pages, accepted to publication in 'Journal of Lightwave Technology
(JLT)
Information Loss and Anti-Aliasing Filters in Multirate Systems
This work investigates the information loss in a decimation system, i.e., in
a downsampler preceded by an anti-aliasing filter. It is shown that, without a
specific signal model in mind, the anti-aliasing filter cannot reduce
information loss, while, e.g., for a simple signal-plus-noise model it can. For
the Gaussian case, the optimal anti-aliasing filter is shown to coincide with
the one obtained from energetic considerations. For a non-Gaussian signal
corrupted by Gaussian noise, the Gaussian assumption yields an upper bound on
the information loss, justifying filter design principles based on second-order
statistics from an information-theoretic point-of-view.Comment: 12 pages; a shorter version of this paper was published at the 2014
International Zurich Seminar on Communication
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs
We introduce a dynamic mechanism for the solution of analytically-tractable
substructure in probabilistic programs, using conjugate priors and affine
transformations to reduce variance in Monte Carlo estimators. For inference
with Sequential Monte Carlo, this automatically yields improvements such as
locally-optimal proposals and Rao-Blackwellization. The mechanism maintains a
directed graph alongside the running program that evolves dynamically as
operations are triggered upon it. Nodes of the graph represent random
variables, edges the analytically-tractable relationships between them. Random
variables remain in the graph for as long as possible, to be sampled only when
they are used by the program in a way that cannot be resolved analytically. In
the meantime, they are conditioned on as many observations as possible. We
demonstrate the mechanism with a few pedagogical examples, as well as a
linear-nonlinear state-space model with simulated data, and an epidemiological
model with real data of a dengue outbreak in Micronesia. In all cases one or
more variables are automatically marginalized out to significantly reduce
variance in estimates of the marginal likelihood, in the final case
facilitating a random-weight or pseudo-marginal-type importance sampler for
parameter estimation. We have implemented the approach in Anglican and a new
probabilistic programming language called Birch.Comment: 13 pages, 4 figure
Multipath Multiplexing for Capacity Enhancement in SIMO Wireless Systems
This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN)
data transmission and detection approach for a single input multiple output
(SIMO) system. It is assumed that the signal having a bandwidth is
transmitted through a wireless channel with multipath components. Under
this assumption, the current paper provides a novel and simple OFTN
transmission and symbol-by-symbol detection approach that exploits the
multiplexing gain obtained by the multipath characteristic of wideband wireless
channels. It is shown that the proposed design can achieve a higher
transmission rate than the existing one (i.e., orthogonal frequency division
multiplexing (OFDM)). Furthermore, the achievable rate gap between the proposed
approach and that of the OFDM increases as the number of receiver antennas
increases for a fixed value of . This implies that the performance gain of
the proposed approach can be very significant for a large-scale multi-antenna
wireless system. The superiority of the proposed approach is shown
theoretically and confirmed via numerical simulations. {Specifically, we have
found {upper-bound average} rates of 15 bps/Hz and 28 bps/Hz with the OFDM and
proposed approaches, respectively, in a Rayleigh fading channel with 32 receive
antennas and signal to noise ratio (SNR) of 15.3 dB. The extension of the
proposed approach for different system setups and associated research problems
is also discussed.Comment: IEEE Transactions on Wireless Communication
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