The Experts below are selected from a list of 62034 Experts worldwide ranked by ideXlab platform
Wenjing Liao - One of the best experts on this subject based on the ideXlab platform.
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music for single snapshot spectral estimation stability and super resolution
Applied and Computational Harmonic Analysis, 2016Co-Authors: Wenjing Liao, Albert FannjiangAbstract:Abstract This paper studies the problem of line spectral estimation in the continuum of a bounded interval with one snapshot of Array Measurement. The single-snapshot Measurement data are turned into a Hankel data matrix which admits the Vandermonde decomposition and is suitable for the MUSIC algorithm. The MUSIC algorithm amounts to finding the null space (the noise space) of the adjoint of the Hankel matrix, forming the noise-space correlation function and identifying the s smallest local minima of the noise-space correlation as the frequency set. In the noise-free case exact reconstruction is guaranteed for any arbitrary set of frequencies as long as the number of Measurement data is at least twice the number of distinct frequencies to be recovered. In the presence of noise the stability analysis shows that the perturbation of the noise-space correlation is proportional to the spectral norm of the noise matrix as long as the latter is smaller than the smallest (nonzero) singular value of the noiseless Hankel data matrix. Under the assumption that the true frequencies are separated by at least twice the Rayleigh Length (RL), the stability of the noise-space correlation is proved by means of novel discrete Ingham inequalities which provide bounds on the largest and smallest nonzero singular values of the noiseless Hankel data matrix. The numerical performance of MUSIC is tested in comparison with other algorithms such as BLO-OMP and SDP (TV-min). While BLO-OMP is the stablest algorithm for frequencies separated above 4 RL, MUSIC becomes the best performing one for frequencies separated between 2 RL and 3 RL. Also, MUSIC is more efficient than other methods. MUSIC truly shines when the frequency separation drops to 1 RL or below when all other methods fail. Indeed, the resolution length of MUSIC decreases to zero as noise decreases to zero as a power law with an exponent smaller than an upper bound established by Donoho.
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music for single snapshot spectral estimation stability and super resolution
arXiv: Information Theory, 2014Co-Authors: Wenjing Liao, Albert FannjiangAbstract:This paper studies the problem of line spectral estimation in the continuum of a bounded interval with one snapshot of Array Measurement. The single-snapshot Measurement data is turned into a Hankel data matrix which admits the Vandermonde decomposition and is suitable for the MUSIC algorithm. The MUSIC algorithm amounts to finding the null space (the noise space) of the Hankel matrix, forming the noise-space correlation function and identifying the s smallest local minima of the noise-space correlation as the frequency set. In the noise-free case exact reconstruction is guaranteed for any arbitrary set of frequencies as long as the number of Measurements is at least twice the number of distinct frequencies to be recovered. In the presence of noise the stability analysis shows that the perturbation of the noise-space correlation is proportional to the spectral norm of the noise matrix as long as the latter is smaller than the smallest (nonzero) singular value of the noiseless Hankel data matrix. Under the assumption that frequencies are separated by at least twice the Rayleigh Length (RL), the stability of the noise-space correlation is proved by means of novel discrete Ingham inequalities which provide bounds on nonzero singular values of the noiseless Hankel data matrix. The numerical performance of MUSIC is tested in comparison with other algorithms such as BLO-OMP and SDP (TV-min). While BLO-OMP is the stablest algorithm for frequencies separated above 4 RL, MUSIC becomes the best performing one for frequencies separated between 2 RL and 3 RL. Also, MUSIC is more efficient than other methods. MUSIC truly shines when the frequency separation drops to 1 RL or below when all other methods fail. Indeed, the resolution length of MUSIC decreases to zero as noise decreases to zero as a power law with an exponent much smaller than an upper bound established by Donoho.
Albert Fannjiang - One of the best experts on this subject based on the ideXlab platform.
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music for single snapshot spectral estimation stability and super resolution
Applied and Computational Harmonic Analysis, 2016Co-Authors: Wenjing Liao, Albert FannjiangAbstract:Abstract This paper studies the problem of line spectral estimation in the continuum of a bounded interval with one snapshot of Array Measurement. The single-snapshot Measurement data are turned into a Hankel data matrix which admits the Vandermonde decomposition and is suitable for the MUSIC algorithm. The MUSIC algorithm amounts to finding the null space (the noise space) of the adjoint of the Hankel matrix, forming the noise-space correlation function and identifying the s smallest local minima of the noise-space correlation as the frequency set. In the noise-free case exact reconstruction is guaranteed for any arbitrary set of frequencies as long as the number of Measurement data is at least twice the number of distinct frequencies to be recovered. In the presence of noise the stability analysis shows that the perturbation of the noise-space correlation is proportional to the spectral norm of the noise matrix as long as the latter is smaller than the smallest (nonzero) singular value of the noiseless Hankel data matrix. Under the assumption that the true frequencies are separated by at least twice the Rayleigh Length (RL), the stability of the noise-space correlation is proved by means of novel discrete Ingham inequalities which provide bounds on the largest and smallest nonzero singular values of the noiseless Hankel data matrix. The numerical performance of MUSIC is tested in comparison with other algorithms such as BLO-OMP and SDP (TV-min). While BLO-OMP is the stablest algorithm for frequencies separated above 4 RL, MUSIC becomes the best performing one for frequencies separated between 2 RL and 3 RL. Also, MUSIC is more efficient than other methods. MUSIC truly shines when the frequency separation drops to 1 RL or below when all other methods fail. Indeed, the resolution length of MUSIC decreases to zero as noise decreases to zero as a power law with an exponent smaller than an upper bound established by Donoho.
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music for single snapshot spectral estimation stability and super resolution
arXiv: Information Theory, 2014Co-Authors: Wenjing Liao, Albert FannjiangAbstract:This paper studies the problem of line spectral estimation in the continuum of a bounded interval with one snapshot of Array Measurement. The single-snapshot Measurement data is turned into a Hankel data matrix which admits the Vandermonde decomposition and is suitable for the MUSIC algorithm. The MUSIC algorithm amounts to finding the null space (the noise space) of the Hankel matrix, forming the noise-space correlation function and identifying the s smallest local minima of the noise-space correlation as the frequency set. In the noise-free case exact reconstruction is guaranteed for any arbitrary set of frequencies as long as the number of Measurements is at least twice the number of distinct frequencies to be recovered. In the presence of noise the stability analysis shows that the perturbation of the noise-space correlation is proportional to the spectral norm of the noise matrix as long as the latter is smaller than the smallest (nonzero) singular value of the noiseless Hankel data matrix. Under the assumption that frequencies are separated by at least twice the Rayleigh Length (RL), the stability of the noise-space correlation is proved by means of novel discrete Ingham inequalities which provide bounds on nonzero singular values of the noiseless Hankel data matrix. The numerical performance of MUSIC is tested in comparison with other algorithms such as BLO-OMP and SDP (TV-min). While BLO-OMP is the stablest algorithm for frequencies separated above 4 RL, MUSIC becomes the best performing one for frequencies separated between 2 RL and 3 RL. Also, MUSIC is more efficient than other methods. MUSIC truly shines when the frequency separation drops to 1 RL or below when all other methods fail. Indeed, the resolution length of MUSIC decreases to zero as noise decreases to zero as a power law with an exponent much smaller than an upper bound established by Donoho.
Ennes Sarradj - One of the best experts on this subject based on the ideXlab platform.
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trailing edge noise of partially porous airfoils
AIAA CEAS Aeroacoustics Conference, 2014Co-Authors: Thomas Geyer, Ennes SarradjAbstract:The use of porous trailing edges is one possible approach to reduce airfoil trailing edge noise. Past experiments on fully porous airfoil models showed that a noticeable noise reduction can be achieved. However, this reduction is accompanied by a loss in aerodynamic performance. To combine the acoustic advantages of the porous trailing edge with the aerodynamic advantages of a non-porous airfoil, the generation of trailing edge noise of airfoil models that only have a porous trailing edge is investigated. To this end, initial experiments were performed on a set of airfoils with porous trailing edges of varying chordwise extent in an open jet wind tunnel, using microphone Array Measurement technique and a deconvolution beamforming algorithm. The lift forces and drag forces were measured simultaneously to the acoustic Measurements. Additionally, hot-wire Measurements were performed to allow conclusions on the underlying mechanisms that enable the noise reduction. It could be demonstrated that, depending on the porous material, airfoils that are non-porous except for their trailing edge can still lead to a noticeable trailing edge noise reduction, while providing a better aerodynamic performance.
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experimental assessment of the noise generated at the leading edge of porous airfoils using microphone Array techniques
AIAA CEAS Aeroacoustics Conference, 2011Co-Authors: Thomas F Geyer, Ennes Sarradj, Jens Giesler, Marcus HobrachtAbstract:ow{permeable materials is a known method for the reduction of airfoil aeroacoustic noise. Detailed acoustic Measurements on the noise generation at the leading edge of porous airfoil models were performed in an open jet wind tunnel using microphone Array Measurement techniques and three{dimensional beamforming algorithms. A set of three dierent grids provided the required inow turbulence. Measurement results are presented for the noise generated at the leading edge of porous airfoils, which are characterized by their air ow resistivity, compared to a non{porous reference airfoil. The comparison of the leading edge noise spectra measured for the reference airfoil with theory yields good agreement. The results of the acoustic Measurements show that porous airfoils with low air ow resistivities lead to a noticeable noise reduction, which is assumed to be caused by the larger pores of these materials compared to porous airfoils with a higher air ow resistivity.
Leo Brown - One of the best experts on this subject based on the ideXlab platform.
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comparison of phase velocities from Array Measurements of rayleigh waves associated with microtremor and results calculated from borehole shear wave velocity profiles
Bulletin of the Seismological Society of America, 2000Co-Authors: Hsiping Liu, David M Boore, William B Joyner, David H Oppenheimer, Richard E Warrick, Wenbo Zhang, John C Hamilton, Leo BrownAbstract:Shear-wave velocities (VS) are widely used for earthquake ground- motion site characterization. VS data are now largely obtained using borehole meth- ods. Drilling holes, however, is expensive. Nonintrusive surface methods are inex- pensive for obtaining VS information, but not many comparisons with direct borehole Measurements have been published. Because different assumptions are used in data interpretation of each surface method and public safety is involved in site character- ization for engineering structures, it is important to validate the surface methods by additional comparisons with borehole Measurements. We compare results obtained from a particular surface method (Array Measurement of surface waves associated with microtremor) with results obtained from borehole methods. Using a 10-element nested-triangular Array of 100-m aperture, we measured surface-wave phase veloci- ties at two California sites, Garner Valley near Hemet and Hollister Municipal Air- port. The Garner Valley site is located at an ancient lake bed where water-saturated sediment overlies decomposed granite on top of granite bedrock. Our Array was deployed at a location where seismic velocities had been determined to a depth of 500 m by borehole methods. At Hollister, where the near-surface sediment consists of clay, sand, and gravel, we determined phase velocities using an Array located close to a 60-m deep borehole where downhole velocity logs already exist. Because we want to assess the Measurements uncomplicated by uncertainties introduced by the inversion process, we compare our phase-velocity results with the borehole VS depth profile by calculating fundamental-mode Rayleigh-wave phase velocities from an earth model constructed from the borehole data. For wavelengths less than 2 times of the Array aperture at Garner Valley, phase-velocity results from Array measure- ments agree with the calculated Rayleigh-wave velocities to better than 11%. Mea- surement errors become larger for wavelengths 2 times greater than the Array aper- ture. At Hollister, the measured phase velocity at 3.9 Hz (near the upper edge of the microtremor frequency band) is within 20% of the calculated Rayleigh-wave veloc- ity. Because shear-wave velocity is the predominant factor controlling Rayleigh- wave phase velocities, the comparisons suggest that this nonintrusive method can provide VS information adequate for ground-motion estimation.
Urs Frey - One of the best experts on this subject based on the ideXlab platform.
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revealing neuronal function through microelectrode Array recordings
Frontiers in Neuroscience, 2015Co-Authors: Marie Engelene J Obien, Urs Frey, Kosmas Deligkaris, Torsten Bullmann, Douglas J BakkumAbstract:Microelectrode Arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around the sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode Array Measurement methods facilitate the understanding of single neurons as well as network function.