Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty

The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference in the presence of unknown parameters within the framework of information field theory. We develop a generic parameter uncertainty renormalized estimation (PURE) technique and address the problem of reconstructing Gaussian signals with unknown power-spectrum with five different approaches: (i) separate maximum-a-posteriori power spectrum measurement and subsequent reconstruction, (ii) maximum-a-posteriori power reconstruction with marginalized power-spectrum, (iii) maximizing the joint posterior of signal and spectrum, (iv) guessing the spectrum from the variance in the Wiener filter map, and (v) renormalization flow analysis of the field theoretical problem providing the PURE filter. In all cases, the reconstruction can be described or approximated as Wiener filter operations with assumed signal spectra derived from the data according to the same recipe, but with differing coefficients. All of these filters, except the renormalized one, exhibit a perception threshold in case of a Jeffreys prior for the unknown spectrum. Data modes, with variance below this threshold do not affect the signal reconstruction at all. Filter (iv) seems to be similar to the so called Karhune-Loeve and Feldman-Kaiser-Peacock estimators for galaxy power spectra used in cosmology, which therefore should also exhibit a marginal perception threshold if correctly implemented. We present statistical performance tests and show that the PURE filter is superior to the others.Comment: 21 pages, 5 figures, accepted by PR

A power filter for the detection of burst sources of gravitational radiation in interferometric detectors

We present a filter for detecting gravitational wave signals from burst sources. This filter requires only minimal advance knowledge of the expected signal: i.e. the signal's frequency band and time duration. It consists of a threshold on the total power in the data stream in the specified signal band during the specified time. This filter is optimal (in the Neyman-Pearson sense) for signal searches where only this minimal information is available.Comment: 3 pages, RevTeX, GWDAW '99 proceedings contribution, submitted to Int. J. Modern Phys.

Medical image enhancement using threshold decomposition driven adaptive morphological filter

One of the most common degradations in medical images is their poor contrast quality. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image. In this paper, a new edge detected morphological filter is proposed to sharpen digital medical images. This is done by detecting the positions of the edges and then applying a class of morphological filtering. Motivated by the success of threshold decomposition, gradientbased operators are used to detect the locations of the edges. A morphological filter is used to sharpen these detected edges. Experimental results demonstrate that the detected edge deblurring filter improved the visibility and perceptibility of various embedded structures in digital medical images. Moreover, the performance of the proposed filter is superior to that of other sharpener-type filters

Stable ac phase and amplitude comparator

Stable ac phase and amplitude comparator detects excessive vehicle maneuvering or vibration. It has phase demodulation, low-pass filter, and multiple threshold-setting capability designed specifically for low drifts over a wide range of temperatures

Length summation in noise

To investigate the effect of background noise on visual summation, we measured the contrast detection thresholds for targets with or without a white noise mask in luminance contrast. The targets were Gabor patterns placed at 3° eccentricity to either the left or right of the fixation and elongated along an arc of the same radius to ensure equidistance from fixation for every point along the long axis. The task was a spatial two-alternative forced-choice (2AFC) paradigm in which the observer had to indicate whether the target was on the left or the right of the fixation. The threshold was measured at 75% accuracy with a staircase procedure. The detection threshold decreased with target length with slope −1/2 on log-log coordinates for target lengths between 30′ and 300′ half-height full-width (HHFW), defining a range of ideal matched-filter summation extending up to about 200′ (or about 16× the center width of the Gabor targets). The summation curves for different noise contrasts were shifted copies of each other. For the threshold versus mask contrast (TvN) functions, the target threshold was constant for noise levels up to about −22 dB, then increased with noise contrast to a linear asymptote on log-log coordinates. Since the “elbow” of the target threshold versus noise function is an index of the level of the equivalent noise experienced by the visual system during target detection, our results suggest that the signal-to-noise ratio was invariant with target length. We further show that a linear-nonlinear-linear gain-control model can fully account for these results with far fewer parameters than a matched-filter model

All fiber, low threshold, widely tunable single-frequency, erbium-doped fiber ring laser with a tandem fiber Fabry–Perot filter

An all fiber, widely tunable, single-frequency, erbium-doped fiber ring laser was constructed with a threshold pump power as low as 10 mW. Tuning over more than 30 nm was obtained by applying 0 to 17 dc V to an intracavity fiber Fabry–Perot filter. Threshold pump power versus wavelength data showed low variation over the tuning range. Mode hopping suppression with a tandem fiber Fabry–Perot filter is proposed and demonstrated. Stable single-frequency operation was demonstrated with side mode suppression higher than 35 dB

Quasi-SLCA based Keyword Query Processing over Probabilistic XML Data

The probabilistic threshold query is one of the most common queries in uncertain databases, where a result satisfying the query must be also with probability meeting the threshold requirement. In this paper, we investigate probabilistic threshold keyword queries (PrTKQ) over XML data, which is not studied before. We first introduce the notion of quasi-SLCA and use it to represent results for a PrTKQ with the consideration of possible world semantics. Then we design a probabilistic inverted (PI) index that can be used to quickly return the qualified answers and filter out the unqualified ones based on our proposed lower/upper bounds. After that, we propose two efficient and comparable algorithms: Baseline Algorithm and PI index-based Algorithm. To accelerate the performance of algorithms, we also utilize probability density function. An empirical study using real and synthetic data sets has verified the effectiveness and the efficiency of our approaches

Apparatus and method for congestion control in high speed networks

An adjustable bit rate (ABR) feedback control scheme is provided where the effects of multiloop delays and high priority traffic transmission are built into the control model. The data traffic is filtered by a low pass filter. Then, the low frequency bandwidth of the filtered traffic is measured and compared to a predetermined threshold. If the measured value exceeds the threshold, the ABR traffic flow is reduced. If the measured value is less than the threshold, the ABR traffic flow is increased. In addition, a General Prediction Control (GPC) method may be applied to the control model for optimal performance. An object of the invention is to minimize the unused link capacity subject to no congestion, where the ABR traffic is adapted to the low frequency variation of high priority traffic flow for high efficiency.Board of Regents, University of Texas Syste