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Acoustical Impulse Response Functions of Music Performance Halls [Minkštas viršelis]

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Acoustical Impulse Response Functions of Music Performance HallsDidesnis paveikslėlis
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Pastovi nuoroda: https://www.kriso.lt/db/9781627051873.html
Digital measurement of the analog acoustical parameters of a music performance hall is difficult. The aim of such work is to create a digital acoustical derivation that is an accurate numerical representation of the complex analog characteristics of the hall. The present study describes the exponential sine sweep (ESS) measurement process in the derivation of an acoustical impulse response function (AIRF) of three music performance halls in Canada. It examines specific difficulties of the process, such as preventing the external effects of the measurement transducers from corrupting the derivation, and provides solutions, such as the use of filtering techniques in order to remove such unwanted effects. In addition, the book presents a novel method of numerical verification through mean-squared error (MSE) analysis in order to determine how accurately the derived AIRF represents the acoustical behavior of the actual hall.
Preface xiii
Acknowledgments xv
List of Symbols, Abbreviations, and Nomenclature
xvii
1 Introduction
1(4)
1.1 Acoustic Measurement of Music Performance Halls in Canada
1(1)
1.2 Geometrical Acoustics
2(1)
1.3 The Importance of Measurement Accuracy
2(3)
1.3.1 Software Issues in Developing an Accurate Representation
3(1)
1.3.2 Verification of the Representation
3(2)
2 A Review of Acoustic Measurement Techniques
5(12)
2.1 The Exponential Sine Sweep (ESS) Technique
6(7)
2.1.1 Advantages of the ESS Technique
9(2)
2.1.2 Performance of Electro-acoustic Transducers
11(2)
2.2 Software Limitations in Measurement Processing Accuracy
13(1)
2.3 Remarks
14(3)
3 The Loudspeaker as a Measurement Sweep Generator
17(20)
3.1 The Measurement Loudspeaker
19(1)
3.2 Classifications of Loudspeakers
20(6)
3.2.1 Direct-Radiator Loudspeakers
20(4)
3.2.2 Horn Loudspeakers
24(2)
3.3 Harmonic Distortion in Loudspeakers
26(2)
3.4 Measurement Loudspeakers used in the Work
28(1)
3.4.1 The Meyer MTS-4 HF Horn Loudspeaker System
28(1)
3.4.2 The Dynaudioacoustics AIR 15 HF Tweeter Near-field Monitor
29(1)
3.5 Performance Comparison of the Measurement Loudspeakers
29(4)
3.5.1 Frequency Response
29(1)
3.5.2 Efficiency, Directivity, and Measurement SNR
30(3)
3.6 Anechoic Simulations of the MTS-4 Measurement Loudspeaker
33(1)
3.7 Remarks
34(3)
4 Convolution and Filtering
37(20)
4.1 Discrete-time Processing of Continuous-time Signals
37(7)
4.1.1 Finite-length Sequences
39(1)
4.1.2 Frequency-domain Representation
39(1)
4.1.3 Computational Requirements of Convolution
40(1)
4.1.4 Circular Convolution Versus Linear Convolution
41(3)
4.2 Convolution Algorithms
44(5)
4.2.1 The Overlap-Save Method
45(1)
4.2.2 Algorithm Optimization
46(3)
4.3 The Problem of Deconvolution
49(5)
4.3.1 Defining the Problem
49(1)
4.3.2 Inverse Filters
49(3)
4.3.3 The Wiener Filter
52(2)
4.3.4 Difficulties with Deconvolution
54(1)
4.4 Remarks
54(3)
5 Experimental Method for the Derivation of an AIRF of a Music Performance Hall
57(12)
5.1 General Technical Specifications
57(1)
5.2 Measurement Recording Configurations
58(2)
5.3 Filtering and Removal of the Effects of the Transducers on the AIRF
60(4)
5.3.1 Loudspeaker Equalization Prefilter
60(1)
5.3.2 Transducer Impulse Response and Inverse Filter
60(4)
5.4 Verification of the AIRF Representation
64(2)
5.5 Remarks
66(3)
6 Evaluation of Results
69(14)
6.1 The Edited AIRF Derivations of the Three Music Performance Halls
71(2)
6.2 Spectral Verification of the AIRF Derivation
73(5)
6.2.1 Numerical Quantification of Spectral Differences
77(1)
6.3 Remarks
78(5)
7 Conclusion
83(2)
7.1 Concluding Remarks
83(1)
7.2 Future Work
84(1)
References 85(4)
Authors' Biographies 89
Douglas FreyUniversity of CalgaryVictor CoelhoBoston UniversityRangaraj M. RangayyanUniversity of Calgary