I. Introduction
Research in physics-based acoustic modeling obtained remarkable results in understanding and developing models for complex acoustic phenomena such as spatial sound diffusion, plate and membrane vibration, or string excitation, just to name a few. When the physical models are transformed in the discrete-time domain, numerical algorithms can be designed to simulate an acoustic phenomenon to the extent of obtaining a perceptually accurate rendition of a real-world sound. To obtain such a goal, a part of the effort must be devoted to the estimation of the model parameters. The more the model departs from its physical behavior, the more it gets harder to estimate the parameters, because they cannot be measured or inferred from physical properties. This is often the case with those techniques where some simplifying hypotheses are assumed to reduce the computational cost or the model complexity, such as Digital Waveguide modeling (DWG) [1]. Similarly, the more the model gets accurate, e.g. introducing secondary physical effects, the more the parameters increase.