Using a dispersive source signal to generate a dispersive field in a nondispersive medium

2008 ◽  
Vol 123 (5) ◽  
pp. 3596-3596
Author(s):  
Shane C. Walker ◽  
William A. Kuperman
Keyword(s):  
Source Signal ◽  
Nondispersive Medium

scholarly journals Sensitivity of Ultrasonic Coda Wave Interferometry to Material Damage—Observations from a Virtual Concrete Lab

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4033
Author(s):  
Claudia Finger ◽  
Leslie Saydak ◽  
Giao Vu ◽  
Jithender J. Timothy ◽  
Günther Meschke ◽  
...  
Keyword(s):  
Elastic Moduli ◽  
Concrete Specimen ◽  
Coda Wave ◽  
Velocity Change ◽  
Damage Scenarios ◽  
Different Types ◽  
Source Signal ◽  
The Impact ◽  
Structural Scale ◽  
Coda Wave Interferometry

Ultrasonic measurements are used in civil engineering for structural health monitoring of concrete infrastructures. The late portion of the ultrasonic wavefield, the coda, is sensitive to small changes in the elastic moduli of the material. Coda Wave Interferometry (CWI) correlates these small changes in the coda with the wavefield recorded in intact, or unperturbed, concrete specimen to reveal the amount of velocity change that occurred. CWI has the potential to detect localized damages and global velocity reductions alike. In this study, the sensitivity of CWI to different types of concrete mesostructures and their damage levels is investigated numerically. Realistic numerical concrete models of concrete specimen are generated, and damage evolution is simulated using the discrete element method. In the virtual concrete lab, the simulated ultrasonic wavefield is propagated from one transducer using a realistic source signal and recorded at a second transducer. Different damage scenarios reveal a different slope in the decorrelation of waveforms with the observed reduction in velocities in the material. Finally, the impact and possible generalizations of the findings are discussed, and recommendations are given for a potential application of CWI in concrete at structural scale.

Research on Blind Signal Extraction Based on Normalized Kurtosis

2014 ◽  
Vol 989-994 ◽  
pp. 3609-3612
Author(s):  
Yong Jian Zhao
Keyword(s):  
Biomedical Applications ◽  
Prior Information ◽  
Signal Extraction ◽  
Promising Technique ◽  
Blind Source Extraction ◽  
Blind Signal ◽  
Source Signal ◽  
Blind Signal Extraction ◽  
Source Signals ◽  
Source Extraction

Blind source extraction (BSE) is a promising technique to solve signal mixture problems while only one or a few source signals are desired. In biomedical applications, one often knows certain prior information about a desired source signal in advance. In this paper, we explore specific prior information as a constrained condition so as to develop a flexible BSE algorithm. One can extract a desired source signal while its normalized kurtosis range is known in advance. Computer simulations on biomedical signals confirm the validity of the proposed algorithm.

Biomedical and Forensic Applications of Combined Catalytic Hydrogenation-Stable Isotope Ratio Analysis

2007 ◽  
Vol 2 ◽  
pp. 117739010700200 ◽  
Author(s):  
Mark A. Sephton ◽  
Will Meredith ◽  
Cheng-Gong Sun ◽  
Colin E. Snape
Keyword(s):  
Carbon Source ◽  
Isotope Ratio ◽  
Stable Carbon Isotope ◽  
Carbon Isotope Ratio ◽  
Precise Determination ◽  
Stable Isotope Ratio ◽  
Laboratory Equipment ◽  
Natural Form ◽  
Source Signal ◽  
Molecular Indicators

Studies of biological molecules such as fatty acids and the steroid hormones have the potential to benefit enormously from stable carbon isotope ratio measurements of individual molecules. In their natural form, however, the body's molecules interact too readily with laboratory equipment designed to separate them for accurate measurements to be made. Some methods overcome this problem by adding carbon to the target molecule, but this can irreversibly overprint the carbon source ‘signal’. Hydropyrolysis is a newly-applied catalytic technique that delicately strips molecules of their functional groups but retains their carbon skeletons and stereochemistries intact, allowing precise determination of the carbon source. By solving analytical problems, the new technique is increasing the ability of scientists to pinpoint molecular indicators of disease, elucidate metabolic pathways and recognise administered substances in forensic investigations.

Using Supervised Machine Learning to Improve Active Source Signal Retrieval

2018 ◽  
Vol 89 (3) ◽  
pp. 1023-1029 ◽  
Author(s):  
Gerrit Olivier ◽  
Julien Chaput ◽  
Brian Borchers
Keyword(s):  
Machine Learning ◽  
Supervised Machine Learning ◽  
Active Source ◽  
Source Signal

A fresh isotopic look at Greenland kimberlites: Cratonic mantle lithosphere imprint on deep source signal

2011 ◽  
Vol 305 (1-2) ◽  
pp. 235-248 ◽  
Author(s):  
Sebastian Tappe ◽  
D. Graham Pearson ◽  
Geoff Nowell ◽  
Troels Nielsen ◽  
Phil Milstead ◽  
...  
Keyword(s):  
Mantle Lithosphere ◽  
Source Signal ◽  
Cratonic Mantle ◽  
Deep Source

An ICA Algorithm Based on Symmetric and Asymmetric Generalized Gaussian Model

2011 ◽  
Vol 204-210 ◽  
pp. 470-475
Author(s):  
Feng Zhao ◽  
Yun Jie Zhang ◽  
Min Cai
Keyword(s):  
Independent Component Analysis ◽  
Gradient Method ◽  
Gaussian Model ◽  
Component Analysis ◽  
Independent Component ◽  
Blind Signal Separation ◽  
Natural Gradient ◽  
Analysis Model ◽  
Practical Applications ◽  
Source Signal

Maximum likelihood estimation is a very popular method to estimate the independent component analysis model because of good performance. Independent component analysis algorithm (the natural gradient method) based on this method is widely used in the field of blind signal separation. It potentially assumes that the source signal was symmetrical distribution, in fact in practical applications, source signals may be asymmetric. This article by distinguishing that the source signal is symmetrical or asymmetrical, proposes an improved natural gradient method based on symmetric generalized Gaussian model (People usually call generalized Gaussian model) and asymmetric generalized Gaussian model. The random mixed-signal simulation results show that the improved algorithm is better than the natural gradient separation method.

Physiology and its Impact on the Performance of Singing

2015 ◽  
pp. 66-84
Author(s):  
Filipa M. B. Lã ◽  
Brian P. Gill
Keyword(s):  
Vocal Tract ◽  
Teaching Method ◽  
Vocal Technique ◽  
Voice Source ◽  
Advantages And Disadvantages ◽  
Physiological Processes ◽  
Subglottal Pressure ◽  
Source Signal ◽  
Frequency Components ◽  
Singing Performance

Singing performance is highly competitive; thus, finding strategies to accelerate the acquisition of knowledge that results in an efficient and effective vocal technique is of the utmost importance. There are many ways in which a singer may acquire an efficient and effective vocal technique, which can be based on the physiological processes of voice production. This chapter explores these processes within the context of singing performance. The authors examine three major aspects of singing: 1) efficient control of breathing, such that optimal airflow and subglottal pressure are available as needed, for a given frequency and intensity; 2) maximized laryngeal coordination, so that the voice source signal contains all the necessary frequency components for the desired tone; and 3) the modulation of the source signal by subtle shaping of the vocal tract. The advantages and disadvantages of various pedagogical methods are discussed, including breath management, known as appoggio, and different resonant strategies. The authors advocate for a scientifically-grounded teaching method, which allows for physiological differences between individuals, genders, and voice classifications.

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