A Swept-Sine-Type Single Measurement to Estimate Intermodulation Distortion in a Dynamic Range of Audio Signal Amplitudes

In the world of real audio systems, it is extremely important to model and identify their nonlinear behavior, especially in the case of professional audio devices. In this context, it is useful to have a quantitative estimation of the nonlinearity degree of the device, which can be obtained by exploiting an efficient and rapid measurement methodology. In this article, we propose an original estimation technique targeting the third-order intermodulation distortion (IMD) and based on a single detection. The proposed technique can be implemented both on devices operating in baseband and in bandpass. Starting from the same single detection, the technique allows to give either an estimate of the third-order IMD for the signal level actually used and to extrapolate the estimate of the IMD to signal levels different from the one actually used. Experimental verifications on real audio devices have allowed to validate the procedure in operational situations, thus confirming the validity of the proposed approach.

[1]  Susanna Spinsante,et al.  A Swept-Sine Pulse Compression Procedure for an Effective Measurement of Intermodulation Distortion , 2020, IEEE Transactions on Instrumentation and Measurement.

[2]  Jyri Tapani Pakarinen,et al.  A Review of Digital Techniques for Modeling Vacuum-Tube Guitar Amplifiers , 2009, Computer Music Journal.

[3]  Danilo Comminiello,et al.  Comparison of Hammerstein and Wiener systems for nonlinear acoustic echo cancelers in reverberant environments , 2011, 2011 17th International Conference on Digital Signal Processing (DSP).

[4]  Simone Orcioni,et al.  Identification of Volterra Models of Tube Audio Devices using Multiple-Variance Method , 2018, Journal of the Audio Engineering Society.

[5]  Francesco Piazza,et al.  Adaptive Identification of Nonlinear Models Using Orthogonal Nonlinear Functions , 2012 .

[6]  Kurt James Werner,et al.  The Fender Bassman 5F6-A Family of Preamplifier Circuits—A Wave Digital Filter Case Study , 2016 .

[7]  Udo Zölzer,et al.  Virtual Analog Modeling of a UREI 1176LN Dynamic Range Control System , 2017 .

[8]  Leon O. Chua,et al.  Fading memory and the problem of approximating nonlinear operators with volterra series , 1985 .

[9]  Matti Karjalainen,et al.  Wave Digital Simulation of a Vacuum-Tube Amplifier , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[10]  Marco Ricci,et al.  Accuracy Analysis of Harmonic Distortion Estimation Through Exponential Chirp Pulse Compression , 2019, 2019 International Conference on Control, Automation and Diagnosis (ICCAD).

[11]  Jonathan S. Abel,et al.  SIMULATION OF THE DIODE LIMITER IN GUITAR DISTORTION CIRCUI TS BY NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS , 2007 .

[12]  A. Terenzi,et al.  A Multiband Structure based on Hammerstein Model for Nonlinear Audio System Identification , 2019, 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA).

[13]  Wolfgang Klippel Active Compensation of Transducer Nonlinearities , 2003 .

[14]  Marc Rébillat,et al.  Identification of cascade of Hammerstein models for the description of nonlinearities in vibrating devices , 2011 .

[15]  Angelo Farina,et al.  Not-Linear Convolution: A New Approach For The Auralization Of Distorting Systems , 2001 .

[16]  Martin Holters,et al.  A Digital Emulation of the Boss SD-1 Super Overdrive Pedal Based on Physical Modeling , 2011 .

[17]  Delphine Bard Horn loudspeakers nonlinearity comparison and linearization using volterra series , 2008 .

[18]  Francesco Piazza,et al.  System Identification based on Hammerstein Models using Cubic Splines , 2013 .

[19]  Udo Zölzer,et al.  BLOCK-ORIENTED GRAY BOXMODELING OF GUITAR AMPLIFIERS , 2017 .

[20]  Joshua D. Reiss,et al.  Modeling Nonlinear Audio Effects with End-to-end Deep Neural Networks , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[21]  Angelo Farina,et al.  Simultaneous Measurement of Impulse Response and Distortion with a Swept-Sine Technique , 2000 .

[22]  J. Embrechts,et al.  Hammerstein Kernels Identification by Means of a Sine Sweep Technique Applied to Nonlinear Audio Devices Emulation , 2017 .

[23]  Yong Soo Cho,et al.  An adaptive nonlinear prefilter for compensation of distortion in nonlinear systems , 1998, IEEE Trans. Signal Process..

[24]  Pierrick Lotton,et al.  Nonlinear System Identification Using Exponential Swept-Sine Signal , 2010, IEEE Transactions on Instrumentation and Measurement.

[25]  Pierrick Lotton,et al.  Nonparametric Identification of Nonlinear Systems in Series , 2014, IEEE Transactions on Instrumentation and Measurement.

[26]  John Vanderkooy,et al.  Harmonic Distortion Measurement for Nonlinear System Identification , 2016 .

[27]  Lauri Juvela,et al.  Real-Time Modeling of Audio Distortion Circuits with Deep Learning , 2019 .

[28]  Udo Zölzer,et al.  Virtual Analog Modeling of Dynamic Range Compression Systems , 2017 .

[29]  Francesco Piazza,et al.  Identification of Hammerstein model using cubic splines and FIR filtering , 2013, 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).

[30]  T. I. Karimov,et al.  Computer simulation of audio circuits with vacuum tubes , 2016, 2016 XIX IEEE International Conference on Soft Computing and Measurements (SCM).