23,025 research outputs found
Approximate Methods for State-Space Models
State-space models provide an important body of techniques for analyzing
time-series, but their use requires estimating unobserved states. The optimal
estimate of the state is its conditional expectation given the observation
histories, and computing this expectation is hard when there are
nonlinearities. Existing filtering methods, including sequential Monte Carlo,
tend to be either inaccurate or slow. In this paper, we study a nonlinear
filter for nonlinear/non-Gaussian state-space models, which uses Laplace's
method, an asymptotic series expansion, to approximate the state's conditional
mean and variance, together with a Gaussian conditional distribution. This {\em
Laplace-Gaussian filter} (LGF) gives fast, recursive, deterministic state
estimates, with an error which is set by the stochastic characteristics of the
model and is, we show, stable over time. We illustrate the estimation ability
of the LGF by applying it to the problem of neural decoding and compare it to
sequential Monte Carlo both in simulations and with real data. We find that the
LGF can deliver superior results in a small fraction of the computing time.Comment: 31 pages, 4 figures. Different pagination from journal version due to
incompatible style files but same content; the supplemental file for the
journal appears here as appendices B--E
Convolutional coding techniques for data protection Quarterly progress report, 16 May - 15 Aug. 1969
General inverses for linear sequential circuits and continuous dynamical system
Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm
Iterative information processing, either based on heuristics or analytical
frameworks, has been shown to be a very powerful tool for the design of
efficient, yet feasible, wireless receiver architectures. Within this context,
algorithms performing message-passing on a probabilistic graph, such as the
sum-product (SP) and variational message passing (VMP) algorithms, have become
increasingly popular.
In this contribution, we apply a combined VMP-SP message-passing technique to
the design of receivers for MIMO-ODFM systems. The message-passing equations of
the combined scheme can be obtained from the equations of the stationary points
of a constrained region-based free energy approximation. When applied to a
MIMO-OFDM probabilistic model, we obtain a generic receiver architecture
performing iterative channel weight and noise precision estimation,
equalization and data decoding. We show that this generic scheme can be
particularized to a variety of different receiver structures, ranging from
high-performance iterative structures to low complexity receivers. This allows
for a flexible design of the signal processing specially tailored for the
requirements of each specific application. The numerical assessment of our
solutions, based on Monte Carlo simulations, corroborates the high performance
of the proposed algorithms and their superiority to heuristic approaches
Study of application of practical performance criteria for the implementation of efficient error-reduction coding Final report
Criteria for implementation of efficient error reduction codin
Performance of convolutional codes on fading channels typical of planetary entry missions
The performance of convolutional codes in fading channels typical of the planetary entry channel is examined in detail. The signal fading is due primarily to turbulent atmospheric scattering of the RF signal transmitted from an entry probe through a planetary atmosphere. Short constraint length convolutional codes are considered in conjunction with binary phase-shift keyed modulation and Viterbi maximum likelihood decoding, and for longer constraint length codes sequential decoding utilizing both the Fano and Zigangirov-Jelinek (ZJ) algorithms are considered. Careful consideration is given to the modeling of the channel in terms of a few meaningful parameters which can be correlated closely with theoretical propagation studies. For short constraint length codes the bit error probability performance was investigated as a function of E sub b/N sub o parameterized by the fading channel parameters. For longer constraint length codes the effect was examined of the fading channel parameters on the computational requirements of both the Fano and ZJ algorithms. The effects of simple block interleaving in combatting the memory of the channel is explored, using the analytic approach or digital computer simulation
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