F. Eichas, and U. Zölzer, "Gray-Box Modeling of Guitar Amplifiers," J. Audio Eng. Soc., vol. 66, no. 12, pp. 1006-1015, (2018 December.). doi: https://doi.org/10.17743/jaes.2018.0052
F. Eichas, and U. Zölzer, "Gray-Box Modeling of Guitar Amplifiers," J. Audio Eng. Soc., vol. 66 Issue 12 pp. 1006-1015, (2018 December.). doi: https://doi.org/10.17743/jaes.2018.0052
Abstract: Musical distortion circuits, especially guitar amplifiers, have been the subject of virtual analog modeling for years. There exists two main modeling approaches: white-box modeling, where the internal properties are fully known, and gray-box modeling, where only the input and output are available. This work proposes a gray-box modeling approach for analog guitar amplifiers using iterative optimization to adjust the parameters of a block-based model. The only assumption made about the reference system is its basic structure. The digital model is an extended Wiener–Hammerstein model consisting of a linear time-invariant (LTI) block, a nonlinear block with a nonlinear mapping function, and another LTI block connected in series. The model is adapted in two steps: first the filters are measured, and then the parameters for the nonlinear part of the digital model are optimized with the Levenberg–Marquardt method to minimize a cost-function describing the error between the digital model and the analog reference system. A small number of guitar amplifiers were modeled, the adapted model was evaluated with objective scores, and a listening test was performed to rate its quality.
@article{eichas2018gray-box,
author={eichas, felix and zölzer, udo},
journal={journal of the audio engineering society},
title={gray-box modeling of guitar amplifiers},
year={2018},
volume={66},
number={12},
pages={1006-1015},
doi={https://doi.org/10.17743/jaes.2018.0052},
month={december},}
@article{eichas2018gray-box,
author={eichas, felix and zölzer, udo},
journal={journal of the audio engineering society},
title={gray-box modeling of guitar amplifiers},
year={2018},
volume={66},
number={12},
pages={1006-1015},
doi={https://doi.org/10.17743/jaes.2018.0052},
month={december},
abstract={musical distortion circuits, especially guitar amplifiers, have been the subject of virtual analog modeling for years. there exists two main modeling approaches: white-box modeling, where the internal properties are fully known, and gray-box modeling, where only the input and output are available. this work proposes a gray-box modeling approach for analog guitar amplifiers using iterative optimization to adjust the parameters of a block-based model. the only assumption made about the reference system is its basic structure. the digital model is an extended wiener–hammerstein model consisting of a linear time-invariant (lti) block, a nonlinear block with a nonlinear mapping function, and another lti block connected in series. the model is adapted in two steps: first the filters are measured, and then the parameters for the nonlinear part of the digital model are optimized with the levenberg–marquardt method to minimize a cost-function describing the error between the digital model and the analog reference system. a small number of guitar amplifiers were modeled, the adapted model was evaluated with objective scores, and a listening test was performed to rate its quality.},}
TY - paper
TI - Gray-Box Modeling of Guitar Amplifiers
SP - 1006
EP - 1015
AU - Eichas, Felix
AU - Zölzer, Udo
PY - 2018
JO - Journal of the Audio Engineering Society
IS - 12
VO - 66
VL - 66
Y1 - December 2018
TY - paper
TI - Gray-Box Modeling of Guitar Amplifiers
SP - 1006
EP - 1015
AU - Eichas, Felix
AU - Zölzer, Udo
PY - 2018
JO - Journal of the Audio Engineering Society
IS - 12
VO - 66
VL - 66
Y1 - December 2018
AB - Musical distortion circuits, especially guitar amplifiers, have been the subject of virtual analog modeling for years. There exists two main modeling approaches: white-box modeling, where the internal properties are fully known, and gray-box modeling, where only the input and output are available. This work proposes a gray-box modeling approach for analog guitar amplifiers using iterative optimization to adjust the parameters of a block-based model. The only assumption made about the reference system is its basic structure. The digital model is an extended Wiener–Hammerstein model consisting of a linear time-invariant (LTI) block, a nonlinear block with a nonlinear mapping function, and another LTI block connected in series. The model is adapted in two steps: first the filters are measured, and then the parameters for the nonlinear part of the digital model are optimized with the Levenberg–Marquardt method to minimize a cost-function describing the error between the digital model and the analog reference system. A small number of guitar amplifiers were modeled, the adapted model was evaluated with objective scores, and a listening test was performed to rate its quality.
Musical distortion circuits, especially guitar amplifiers, have been the subject of virtual analog modeling for years. There exists two main modeling approaches: white-box modeling, where the internal properties are fully known, and gray-box modeling, where only the input and output are available. This work proposes a gray-box modeling approach for analog guitar amplifiers using iterative optimization to adjust the parameters of a block-based model. The only assumption made about the reference system is its basic structure. The digital model is an extended Wiener–Hammerstein model consisting of a linear time-invariant (LTI) block, a nonlinear block with a nonlinear mapping function, and another LTI block connected in series. The model is adapted in two steps: first the filters are measured, and then the parameters for the nonlinear part of the digital model are optimized with the Levenberg–Marquardt method to minimize a cost-function describing the error between the digital model and the analog reference system. A small number of guitar amplifiers were modeled, the adapted model was evaluated with objective scores, and a listening test was performed to rate its quality.
