7,248 research outputs found
Optimization of Planck/LFI on--board data handling
To asses stability against 1/f noise, the Low Frequency Instrument (LFI)
onboard the Planck mission will acquire data at a rate much higher than the
data rate allowed by its telemetry bandwith of 35.5 kbps. The data are
processed by an onboard pipeline, followed onground by a reversing step. This
paper illustrates the LFI scientific onboard processing to fit the allowed
datarate. This is a lossy process tuned by using a set of 5 parameters Naver,
r1, r2, q, O for each of the 44 LFI detectors. The paper quantifies the level
of distortion introduced by the onboard processing, EpsilonQ, as a function of
these parameters. It describes the method of optimizing the onboard processing
chain. The tuning procedure is based on a optimization algorithm applied to
unprocessed and uncompressed raw data provided either by simulations, prelaunch
tests or data taken from LFI operating in diagnostic mode. All the needed
optimization steps are performed by an automated tool, OCA2, which ends with
optimized parameters and produces a set of statistical indicators, among them
the compression rate Cr and EpsilonQ. For Planck/LFI the requirements are Cr =
2.4 and EpsilonQ <= 10% of the rms of the instrumental white noise. To speedup
the process an analytical model is developed that is able to extract most of
the relevant information on EpsilonQ and Cr as a function of the signal
statistics and the processing parameters. This model will be of interest for
the instrument data analysis. The method was applied during ground tests when
the instrument was operating in conditions representative of flight. Optimized
parameters were obtained and the performance has been verified, the required
data rate of 35.5 Kbps has been achieved while keeping EpsilonQ at a level of
3.8% of white noise rms well within the requirements.Comment: 51 pages, 13 fig.s, 3 tables, pdflatex, needs JINST.csl, graphicx,
txfonts, rotating; Issue 1.0 10 nov 2009; Sub. to JINST 23Jun09, Accepted
10Nov09, Pub.: 29Dec09; This is a preprint, not the final versio
New scenario for transition to slow 3D turbulence
Analytical non-perturbative study of the three-dimensional nonlinear
stochastic partial differential equation with additive thermal noise, analogous
to that proposed by V.N. Nikolaevskii [1]-[5]to describe longitudinal seismic
waves, is presented. The equation has a threshold of short-wave instability and
symmetry, providing long wave dynamics. New mechanism of quantum chaos
generating in nonlinear dynamical systems with infinite number of degrees of
freedom is proposed. The hypothesis is said, that physical turbulence could be
identified with quantum chaos of considered type. It is shown that the additive
thermal noise destabilizes dramatically the ground state of the Nikolaevskii
system thus causing it to make a direct transition from a spatially uniform to
a turbulent state.Comment: 23page
Efficient use of bit planes in the generation of motion stimuli
The production of animated motion sequences on computer-controlled display systems presents a technical problem because large images cannot be transferred from disk storage to image memory at conventional frame rates. A technique is described in which a single base image can be used to generate a broad class of motion stimuli without the need for such memory transfers. This technique was applied to the generation of drifting sine-wave gratings (and by extension, sine wave plaids). For each drifting grating, sine and cosine spatial phase components are first reduced to 1 bit/pixel using a digital halftoning technique. The resulting pairs of 1-bit images are then loaded into pairs of bit planes of the display memory. To animate the patterns, the display hardware's color lookup table is modified on a frame-by-frame basis; for each frame the lookup table is set to display a weighted sum of the spatial sine and cosine phase components. Because the contrasts and temporal frequencies of the various components are mutually independent in each frame, the sine and cosine components can be counterphase modulated in temporal quadrature, yielding a single drifting grating. Using additional bit planes, multiple drifting gratings can be combined to form sine-wave plaid patterns. A large number of resultant plaid motions can be produced from a single image file because the temporal frequencies of all the components can be varied independently. For a graphics device having 8 bits/pixel, up to four drifting gratings may be combined, each having independently variable contrast and speed
Quantization of Prior Probabilities for Hypothesis Testing
Bayesian hypothesis testing is investigated when the prior probabilities of
the hypotheses, taken as a random vector, are quantized. Nearest neighbor and
centroid conditions are derived using mean Bayes risk error as a distortion
measure for quantization. A high-resolution approximation to the
distortion-rate function is also obtained. Human decision making in segregated
populations is studied assuming Bayesian hypothesis testing with quantized
priors
Nonparametric estimation of the dynamic range of music signals
The dynamic range is an important parameter which measures the spread of
sound power, and for music signals it is a measure of recording quality. There
are various descriptive measures of sound power, none of which has strong
statistical foundations. We start from a nonparametric model for sound waves
where an additive stochastic term has the role to catch transient energy. This
component is recovered by a simple rate-optimal kernel estimator that requires
a single data-driven tuning. The distribution of its variance is approximated
by a consistent random subsampling method that is able to cope with the massive
size of the typical dataset. Based on the latter, we propose a statistic, and
an estimation method that is able to represent the dynamic range concept
consistently. The behavior of the statistic is assessed based on a large
numerical experiment where we simulate dynamic compression on a selection of
real music signals. Application of the method to real data also shows how the
proposed method can predict subjective experts' opinions about the hifi quality
of a recording
Optimal Image Reconstruction in Radio Interferometry
We introduce a method for analyzing radio interferometry data which produces
maps which are optimal in the Bayesian sense of maximum posterior probability
density, given certain prior assumptions. It is similar to maximum entropy
techniques, but with an exact accounting of the multiplicity instead of the
usual approximation involving Stirling's formula. It also incorporates an Occam
factor, automatically limiting the effective amount of detail in the map to
that justified by the data. We use Gibbs sampling to determine, to any desired
degree of accuracy, the multi-dimensional posterior density distribution. From
this we can construct a mean posterior map and other measures of the posterior
density, including confidence limits on any well-defined function of the
posterior map.Comment: 41 pages, 11 figures. High resolution figures 8 and 9 available at
http://www.astro.uiuc.edu/~bwandelt/SuttonWandelt200
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