Reduced-Complexity Modeling of High-Order Nonlinear Audio Systems Using Swept-Sine and Principal Component Analysis

Cauduro Dias de Paiva R, Pakarinen J, Välimäki V. Reduced-Complexity Modeling of High-Order Nonlinear Audio Systems Using Swept-Sine and Principal Component Analysis. In: AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio. Audio Engineering Society; 2012. Paper 5-4. Available from: https://aes.org/publications/elibrary-page/?id=16200

@inproceedings{CauduroDiasdePaiva2012_16200,
  author = {Cauduro Dias de Paiva, Rafael and Pakarinen, Jyri and Välimäki, Vesa},
  title = {{Reduced-Complexity Modeling of High-Order Nonlinear Audio Systems Using Swept-Sine and Principal Component Analysis}},
  booktitle = {AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio},
  note = {Paper 5-4},
  year = {2012},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16200}
}

TY  - CPAPER
TI  - Reduced-Complexity Modeling of High-Order Nonlinear Audio Systems Using Swept-Sine and Principal Component Analysis
AU  - Cauduro Dias de Paiva, Rafael
AU  - Pakarinen, Jyri
AU  - Välimäki, Vesa
T2  - AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio
M1  - Paper 5-4
PY  - 2012
DA  - 2012/03/06
UR  - https://aes.org/publications/elibrary-page/?id=16200
PB  - Audio Engineering Society
LA  - en
AB  - Modeling high-order nonlinear systems is an important issue in audio signal processing. It may be employed in real-time emulation of analog nonlinear systems, such as guitar distortion and amplifiers or other vintage electronic audio systems. This paper proposes a new method for obtaining an economical black-box model of nonlinear systems using the swept-sine technique, which extracts the harmonic distortion at each frequency by separating them in time. In the proposed model the swept-sine technique is used to obtain the time-frequency representation of a nonlinear system, and the principal component analysis is used to reduce the complexity of the model. It is shown that the proposed method reduces the computational cost by 66% when compared to traditional swept-sine models.
ER  -