Effect of signal-processing parameters on phase velocity uncertainty

2002 ◽  
Author(s):  
M.C. Renken ◽  
C.M. Fortunko ◽  
C.T. Mullis
Keyword(s):  
Signal Processing ◽  
Phase Velocity ◽  
Processing Parameters

scholarly journals The use of self-report measures to examine changes in perception in response to fittings using different signal processing parameters

2018 ◽  
Vol 57 (11) ◽  
pp. 809-815 ◽  
Author(s):  
Melinda Anderson ◽  
Varsha Rallapalli ◽  
Tim Schoof ◽  
Pamela Souza ◽  
Kathryn Arehart
Keyword(s):  
Signal Processing ◽  
Processing Parameters ◽  
Self Report ◽  
Use Of Self

Signal Processing Parameters for Estimation of the Diesel Engine Combustion Signature

2011 ◽  
Vol 4 (2) ◽  
pp. 1201-1215 ◽  
Author(s):  
Andrew J. Morello ◽  
Jason R. Blough ◽  
Jeffrey Naber ◽  
Libin Jia
Keyword(s):  
Signal Processing ◽  
Diesel Engine ◽  
Processing Parameters ◽  
Engine Combustion

scholarly journals Interpolator: a two-dimensional graphical interpolation system for the simultaneous control of digital signal processing parameters

2001 ◽  
Vol 6 (2) ◽  
pp. 147-151 ◽  
Author(s):  
Martin Spain ◽  
Richard Polfreman
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Processing Parameters ◽  
Digital Audio ◽  
Two Dimensional ◽  
Current Position ◽  
Control Space ◽  
Simultaneous Control ◽  
Parameter Values

The musical use of realtime digital audio tools implies the need for simultaneous control of a large number of parameters to achieve the desired sonic results. Often it is also necessary to be able to navigate between certain parameter configurations in an easy and intuitive way, rather than to precisely define the evolution of the values for each parameter. Graphical interpolation systems (GIS) provide this level of control by allocating objects within a visual control space to sets of parameters that are to be controlled, and using a moving cursor to change the parameter values according to its current position within the control space. This paper describes Interpolator, a two-dimensional interpolation system for controlling digital signal processing (DSP) parameters in real time.

scholarly journals Instantaneous local wave vector estimation from multi-spacecraft measurements using few spatial points

2004 ◽  
Vol 22 (7) ◽  
pp. 2633-2641 ◽  
Author(s):  
T. D. Carozzi ◽  
A. M. Buckley ◽  
M. P. Gough
Keyword(s):  
Signal Processing ◽  
Phase Velocity ◽  
Wave Vector ◽  
Direct Determination ◽  
Space Mission ◽  
3 Dimensional ◽  
Local Wave ◽  
Local Properties ◽  
Vector Estimation

Abstract. We introduce a technique to determine instantaneous local properties of waves based on discrete-time sampled, real-valued measurements from 4 or more spatial points. The technique is a generalisation to the spatial domain of the notion of instantaneous frequency used in signal processing. The quantities derived by our technique are closely related to those used in geometrical optics, namely the local wave vector and instantaneous phase velocity. Thus, this experimental technique complements ray-tracing. We provide example applications of the technique to electric field and potential data from the EFW instrument on Cluster. Cluster is the first space mission for which direct determination of the full 3-dimensional local wave vector is possible, as described here.

Laser Doppler anemometry applied to airborne acoustics: Influence of the signal processing parameters

1999 ◽  
Vol 105 (2) ◽  
pp. 1292-1292
Author(s):  
Sylvain Poggi ◽  
Bruno Gazengel ◽  
Jean‐Christophe Valière ◽  
Anne‐Marie Bruneau
Keyword(s):  
Signal Processing ◽  
Laser Doppler Anemometry ◽  
Processing Parameters ◽  
Laser Doppler

COMPARISON OF LINEAR AND ORTHOGONAL BEAMFORMER PERFORMANCE FOR THE 1993 MATCHED FIELD PROCESSING BENCHMARKS

1994 ◽  
Vol 02 (03) ◽  
pp. 187-197 ◽  
Author(s):  
JOHN M. OZARD ◽  
PETER BROUWER ◽  
TIM SCHEUER
Keyword(s):  
Signal Processing ◽  
Parabolic Equation ◽  
Acoustic Signal ◽  
Processing Parameters ◽  
Minimum Variance ◽  
Source Detection ◽  
Source Position ◽  
Matched Field Processing ◽  
Detection And Localization ◽  
Gradient Models

Results are presented for the Matched Field Processing (MFP) analysis of synthetic benchmark cases, performed by a comprehensive Acoustic Signal Processing (ASP) code used in a turnkey manner. The performance of the Generalized Bartlett Beamformer (GBB), Minimum Variance (MV), and Modified Reduced Minimum Variance (MRMV) processors incorporated in the ASP code were evaluated. Matches for replicas generated using normal mode and Parabolic Equation (PE) models produced virtually identical results. However, the choice of layered versus gradient models was shown to be a cause of sufficient mismatch and to alter the source position by several increments in range and depth if sufficiently fine layering was not employed. GBB and MRMV exhibit similar levels of robustness to mismatch, while MV showed its well-known sensitivity to mismatch. Our turnkey approach indicated that MFP techniques are relatively robust with respect to source detection and localization even when suboptimal modeling and processing parameters are used.

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