222 research outputs found
Fisher-information condition for enhanced signal detection via stochastic resonance
Various situations where a signal is enhanced by noise through stochastic resonance are now known. This paper contributes to determining general conditions under which improvement by noise can be a priori decided as feasible or not. We focus on the detection of a known signal in additive white noise. Under the assumptions of a weak signal and a sufficiently large sample size, it is proved, with an inequality based on the Fisher information, that improvement by adding noise is never possible, generically, in these conditions. However, under less restrictive conditions, an example of signal detection is shown with favorable action of adding noise.Fabing Duan, François Chapeau-Blondeau, Derek Abbot
Tsallis entropy measure of noise-aided information transmission in a binary channel
Noise-aided information transmission via stochastic resonance is shown and analyzed in a binary channel by means of information measures based on the Tsallis entropy. The analysis extends the classic reference of binary information transmission based on the Shannon entropy, and also parallels a recent study based on the Rényi entropy. The conditions for a maximally pronounced stochastic resonance identify optimal Tsallis measures. The study involves a correspondence between Tsallis and Rényi information measures, specially relevant to the characterization of stochastic resonance, and establishing that for such effects identical properties are shared in common by both Tsallis and Rényi measures
Exploiting the speckle noise for compressive imaging
An optical setup is proposed for the implementation of compressive sensing with coherent images. This setup specifically exploits the natural multiplicative action of speckle noise occurring with coherent light, in order to optically realize the essential step in compressive sensing which is the multiplication with known random patterns of the image to be acquired. In the test of the implementation, we specifically examine the impact of several departures, that exist in practice, from the ideal conditions of a pure multiplicative action of the speckle. In such practical realistic conditions, we assess the feasibility, performance and robustness of the optical scheme of compressive sensing. (C) 2011 Elsevier B.V. All rights reserved
Fisher information and Shannon entropy for on-line detection of transient signal high-values in laser Doppler flowmetry signals of healthy subjects
Laser Doppler flowmetry (LDF) is an easy-to-use method for the assessment of microcirculatory blood flow in tissues. However, LDF recordings very often present TRAnsient Signal High-values (TRASH), generally of a few seconds. These TRASH can come from tissue motions, optical fibre movements, movements of the probe head relative to the tissue, etc. They often lead to difficulties in signal global interpretations. In order to test the possibility of detecting automatically these TRASH for their removal, we process noisy and noiseless LDF signals with two indices from information theory, namely Fisher information and Shannon entropy. For this purpose, LDF signals from 13 healthy subjects are recorded at rest, during vascular occlusion of 3 min, and during post-occlusive hyperaemia. Computation of Fisher information and Shannon entropy values shows that, when calibrated, these two indices can be complementary to detect TRASH and be insensitive to the rapid increases of blood flow induced by post-occlusive hyperaemia. Moreover, the real-time algorithm has the advantage of being easy to implement and does not require any frequency analysis. This study opens new fields of application for Fisher information and Shannon entropy: LDF \u27denoising\u27
Multifractal analysis of laser Doppler flowmetry signals: partition function and generalized dimensions of data recorded before and after local heating
Enumerative and asymptotic analysis of a moduli space
We focus on combinatorial aspects of the Hilbert series of the cohomology
ring of the moduli space of stable pointed curves of genus zero. We show its
graded Hilbert series satisfies an integral operator identity. This is used to
give asymptotic behavior, and in some cases, exact values, of the coefficients
themselves. We then study the total dimension, that is, the sum of the
coefficients of the Hilbert series. Its asymptotic behavior involves the
Lambert W function, which has applications to classical tree enumeration,
signal processing and fluid mechanics.Comment: 14 page
Study of time reversibility/irreversibility of cardiovascular data: theoretical results and application to laser Doppler flowmetry and heart rate variability signals
Time irreversibility can be qualitatively defined as the degree of a signal for temporal asymmetry. Recently, a time irreversibility characterization method based on entropies of positive and negative increments has been proposed for experimental signals and applied to heart rate variability (HRV) data (central cardiovascular system (CVS)). The results led to interesting information as a time asymmetry index was found different for young subjects and elderly people or heart disease patients. Nevertheless, similar analyses have not yet been conducted on laser Doppler flowmetry (LDF) signals (peripheral CVS). We first propose to further investigate the above-mentioned characterization method. Then, LDF signals, LDF signals reduced to samples acquired during ECG R peaks (LDF_RECG signals) and HRV recorded simultaneously in healthy subjects are processed. Entropies of positive and negative increments for LDF signals show a nonmonotonic pattern: oscillations—more or less pronounced, depending on subjects—are found with a period matching the one of cardiac activity. However, such oscillations are not found with LDF_RECG nor with HRV. Moreover, the asymmetry index for LDF is markedly different from the ones of LDF_RECG and HRV. The cardiac activity may therefore play a dominant role in the time irreversibility properties of LDF signals
Localization of transient signal high-values in laser Doppler flowmetry signals with an empirical mode decomposition
The laser Doppler flowmetry (LDF) technique provides the monitoring of microvascular blood flow perfusion. However, LDF monitors based on fiber-optic transducers have the serious drawback of generating TRAnsient Signal High-values (TRASH) in signals. These TRASH correspond to artifacts for clinicians as they prevent interpretations of the signal when they are numerous. Moreover, TRASH exclude the possibility of direct signal processing and analyses. Therefore, in clinical routines, a human visual inspection of LDF signals is necessary to detect TRASH and to process the signals accordingly. This may be very time consuming. An algorithm able to localize TRASH automatically for their removal is therefore of interest. However, the development of such an algorithm is not an easy task as TRASH amplitude can be lower, higher, or in the same amplitude range as responses to stimuli such as post-occlusive hyperemia. The recently introduced empirical mode decomposition (EMD) has the advantage of splitting any kind of signal into fast and slow oscillations. Relying on these properties, the authors evaluate the possibility for EMD to localize TRASH automatically. For this purpose, LDF signals from 28 men of different ages are recorded at rest, during a vascular occlusion of 3 min , followed by a post-occlusive hyperemia. For each signal containing TRASH, the first intrinsic mode function obtained with the EMD is processed with a running window-based analysis in which a thresholding of the local maxima is carried out for the localization of TRASH. From the data, the use of a window width of 25 s is suggested. The results show effective and potential usefulness of this algorithm for an automatic localization of TRASH. Moreover, the method proposed has the advantage of being insensitive to the rapid increases of blood flow induced by post-occlusive hyperemia, which is of interest for clinicians. Because it is both local and fully data adaptive, EMD appears as an appealing processing technique for overcoming some of the limitations of the LDF
Multiscale Analysis of Microvascular Blood Flow: A Multiscale Entropy Study of Laser Doppler Flowmetry Time Series
Processes regulating the cardiovascular system (CVS) are numerous. Each possesses several temporal scales. Their interactions lead to interdependences across multiple scales. For the CVS analysis, different multiscale studies have been proposed, mostly performed on heart rate variability signals (HRV) reflecting the central CVS; only few were dedicated to data from the peripheral CVS, such as laser Doppler flowmetry (LDF) signals. Very recently, a study implemented the first computation of multiscale entropy for LDF signals. A nonmonotonic evolution of multiscale entropy with two distinctive scales was reported, leading to a markedly different behavior from the one of HRV. Our goal herein is to confirm these results and to go forward in the investigations on origins of this behavior. For this purpose, 12 LDF signals recorded simultaneously on the two forearms of six healthy subjects are processed. This is performed before and after application of physiological scales-based filters aiming at isolating previously found frequency bands linked to physiological activities. The results obtained with signals recorded simultaneously on two different sites of each subject show a probable central origin for the nonmonotonic behavior. The filtering results lead to the suggestion that origins of the distinctive scales could be dominated by the cardiac activity
Computer-Assisted Generation of Patterns and Virtual Reality Techniques for Fashion Design
We present a methodology for the design of aesthetic patterns and their visualization on virtual clothes. Generated patterns are directly mapped on the dress of a virtual mannequin. Furthermore, patterns sets may be interactively mapped on the virtual dress using a specific 3D interaction technique called Back-and-Forth. Pattern generation involves different mathematical approaches such as iterated function systems (IFS) and nonlinear trajectory models. Both model parameters and color space exploration is performed through a simple user interface. This work contributes to promote both computer assistance in the context of mass customization for fashion design
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