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Driver Filter Design for Software-Implemented Loudspeaker Crossovers

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A hybrid method is presented for the integration of low-, mid-, and high-frequency driver filters in loud- speaker crossovers. The Pascal matrix is exploited to calculate denominators; the locations of minimum values in frequency magnitude responses are associated with the forms of numerators; the maximum values are used to compute gain factors. The forms of the resulting filters are based on the physical meanings of low-pass, band-pass, and high-pass filters, an intuitive idea which is easy to be understood. Moreover, each coefficient is believed to be simply calculated, an advantage which keeps the software- implemented crossover running smoothly even if crossover frequencies are being changed in real time. This characteristic allows users to efficiently adjust the bandwidths of the driver filters by subjective listening tests if objective measurements of loudspeaker parameters are unavailable. Instead of designing separate structures for a low-, mid-, and high-frequency driver filter, by using the proposed techniques we can implement one structure which merges three types of digital filters. Not only does the integra- tion architecture operate with low computational cost, but its size is also compact. Design examples are included to illustrate the effectiveness of the presented methodology.
Rocznik
Strony
591--597
Opis fizyczny
Bibliogr. 8 poz., rys., tab., wykr.
Twórcy
autor
  • School of Electronic, Electrical and Computer Engineering, University of Birminghamg Edgbaston, Birmingham, B15 2TT, UK
Bibliografia
  • 1. Konopacki J. (2005), The frequency transformation by matrix operation and its application in IIR filters design, IEEE Signal Processing Letters, 12, 1, 5–8.
  • 2. Kulka Z. (2011), Advances in digitization of microphones and loudspeakers, Archives of Acoustics, 36, 2, 419–436.
  • 3. Oppenheim A.V., Schafer R.W. (1999), Discrete-time signal processing, Prentice Hall, New Jersey.
  • 4. Pradabpet C., Yimman S., Hinjit W., Chivapreecha S., Dejhan K. (2003), Design and implementation of biquad digital filter, Proceedings of the IEEE Asia-Pacific Conference on Communications, 1138–1142.
  • 5. Proakis J.G., Manolakis D.G. (1996), Digital Signal Processing, Prentice Hall, New Jersey.
  • 6. Psenicka B., Garcia-Ugalde F., Herrera-Camacho A. (2002), The bilinear Z transform by Pascal matrix and its application in the design of digital filters, IEEE Signal Processing Letters, 9, 11, 368–370.
  • 7. Waterschoot V.T., Moonen M. (2007), Pole-zero placement technique for designing second-order IIR parametric equalizer filters, IEEE Trans. Audio Speech Lang. Process., 15, 8, 2561–2565.
  • 8. Yao S.N., Collins T., Jančovič P. (2012), Hybrid method for designing digital Butterworth filters, Computers & Electrical Engineering, 38, 4, 811–818.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a4fa881a-5604-4289-81cd-fab54e86d6d5
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