In this paper we propose new models for the plucking interaction of the player with the string for use with digital waveguide simulation of guitar. Unlike the previously presented models, the new models are based on structurally passive scattering junctions, which have the main advantage of being properly scaled for use in fixed-point waveguide implementations and of guaranteeing stability independently of the plucking excitation. In a first model we start from the Cuzzucoli-Lombardo equations [1], within the Evangelista-Eckerholm [2] propagation formulation, in order to derive the passive scattering junction by means of bilinear transformation. In a second model we start from equations properly modeling the finger compliance by means of a spring. In a third model we formalize the interaction in terms of driving impedances. The model is also extended using nonlinear (feathering) compliance models.

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In quasi-bandlimited classical waveform oscillators, the aliasing distortion present in a trivially sampled waveform can be reduced in the digital domain by applying a tabulated correction function. This paper presents an approach that applies the correction function in the differentiated domain by synthesizing a bandlimited impulse train (BLIT) that is integrated to obtain the desired bandlimited waveform. The ideal correction function of the BLIT method is infinitely long and in practice needs to be windowed. In order to obtain a good alias-reduction performance, long tables are typically required. It is shown that when a short look-up table is used, a windowed ideal correction function does not provide the best performance in terms of minimizing aliasing audibility. Instead, audibly improved alias-reduction performance can be obtained using a look-up table that has a parametric control over the low-order generations of aliasing. Some practical parametric look-up table designs are discussed in this paper, and their use and alias-reduction performance are exemplified. The look-up table designs discussed in this paper providing the best alias-reduction performance are parametric window functions and least-squares optimized multiband FIR filter designs.

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