# Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt Acoustics Research Group

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Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric Equalizer. Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt Acoustics Research Group Department of Physics and Astronomy Brigham Young University - PowerPoint PPT PresentationTRANSCRIPT

Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric EqualizerMicah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.SommerfeldtAcoustics Research GroupDepartment of Physics and AstronomyBrigham Young University148th Meeting of the Acoustical Society of America18 November 2004Background and Traditional TechniqueBackgroundSound fields in rooms do not have ideal responsesSound field equalization compensates for room effects using filtersTraditional techniquesExcite room using pink noiseMeasure pressure response at one locationCut and boost in nth octave bands using graphic equalizer to produce desired responseBetter control using parametric equalizersVariable frequencyVariable QProblemsSpatial variance of sound fieldMicrophone at nodesLimited frequency and gain adjustmentNeed for a better approachSearch for an Improved TechniqueMeasure transfer function between source and receiver in 1-D sound fieldThree casesSingle point mean-squared pressureSpatially averaged mean-squared pressure (potential energy density)Single point total energy densityUse normalized inverses of the responses as equalization filtersExperimental SetupEnergy DensityPressure gradient method Estimate particle velocity using pressure gradientEnergy Density is then2 microphone transfer function method Developed by Chung and Blaser Solve for incident and reflected pressure and reflection coefficients at microphone positionsDerive particle velocity and energy density from resultDifference in ED EstimationsUnequalized FieldMean-Squared Pressure FieldEnergy Density FieldIdeal Inverse Filters From Measured FieldIdeal Equalized Pressure FieldsMean-Squared Pressure EQEnergy Density EQComparison of Ideal Energy DensityFilter and Parametric EQ FilterEqualized Pressure FieldsParametric ED EQIdeal ED EQSpatially Averaged Pressure Responses: Ideal and ParametricConclusionsEnergy density equalization approximates spatially averaged pressure equalization in a 1-D sound fieldA discrete ED measurement can be used to equalize a 1-D sound field better than a discrete pressure measurementParametric equalizers can be used to approximate ideal ED filters, but with notable errorsFuture workConduct more general tests in a 1-D field with variable side-branch source positionsTest energy density equalization methods in 3-D sound fieldsTest energy density equalization methods using multiple sourcesDevelop adaptive filtering techniquesThank you

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