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kalman.rar
... case with
fading must, however, allow for amplitude as well as phase variations of
the MD.
We assume a state-variable model for the MD and generally obtain a
nonlinear estimation problem with additional randomly-varying system
parameters such as ...
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OnsequentialMonteCarlosamplingmethodsforBayesianfi
... method which uses Rao-Blackwellisation in order to take advantage of
the analytic structure present in some important classes of state-space models. In a final section we
develop algorithms for prediction, smoothing and evaluation of the likelihood in ...
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ParticleFilterTrackerwithIsomap.rar
... Isomap. The particle filter works on the low-dimensional embedding of training images. It indexes into the Isomap with its state variables to find the closest template for each particle. The most weighted particle approximates the location of head. We ...
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LogicalParticleFiltering.rar
... . The
algorithm updates the formulae as new observations are received. Since
a single particle tracks many states, this filter can be more accurate
than a traditional particle filter in high dimensional state spaces, as we
demonstrate in experiments.
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AMODIFIEDRAO-BLACKWELLISEDPARTICLEFILTER.rar
... Particle Filters (RBPFs) are a class of Particle
Filters (PFs) that exploit conditional dependencies between
parts of the state to estimate. By doing so, RBPFs can
improve the estimation quality while also reducing the overall
computational load in ...
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BuildingRobustSimulation-basedFiltersforEvolvingDa
... , there has been renewed interest in simulation-based techniques. The basic idea behind
these techniques is that the current state of knowledge is encapsulated in a representative
sample from the appropriate posterior distribution. As time goes on, the ...
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Savege.zip
save form state with structured storage!
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hybridSIREKF.rar
To estimate the input-output mapping with inputs x
％ and outputs y generated by the following nonlinear,
％ nonstationary state space model:
％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)]
％ + 8cos(1.2t) + process noise
％ y(t) = x(t)^(2) / 20 + 6 ...
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bpmpd.rar
bpmpd是用fortran77语言编写的一个state-of-the-art求解大规模线性规划程序，使用不可行原-对偶内点法（infeasible primal-dual interior point method）求解
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State_space_reconstruction_parameters_in_the_analy
State_space_reconstruction_parameters_in_the_analysis_of_chaotic_time_series_-_the_role_of_the_time_window_length.
It is used for reconstruction of state space in chaotic time series, and also how to determine time window.
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