Download Graphic Equalizers Based on Limited Action Networks
Several classic graphic equalizers, such as the Altec 9062A and the “Motown EQ,” have stepped gain controls and “proportional bandwidth” and used passive, constant-resistance, RLC circuit designs based on “limited-action networks.” These are related to bridged-T-network EQs, with several differences that cause important practical improvements, also affecting their sound. We study these networks, giving their circuit topologies, design principles, and design equations, which appear not to have been published before. We make a Wave Digital Filter which can model either device or an idealized “Exact” version, to which we can add various new extensions and features.
Download Real-Time Guitar Synthesis
The synthesis of guitar tones was one of the first uses of physical modeling synthesis, and many approaches (notably digital waveguides) have been employed. The dynamics of the string under playing conditions is complex, and includes nonlinearities, both inherent to the string itself, and due to various collisions with the fretboard, frets and a stopping finger. All lead to important perceptual effects, including pitch glides, rattling against frets, and the ability to play on the harmonics. Numerical simulation of these simultaneous strong nonlinearities is challenging, but recent advances in algorithm design due to invariant energy quadratisation and scalar auxiliary variable methods allow for very efficient and provably numerically stable simulation. A new design is presented here that does not employ costly iterative methods such as the Newton-Raphson method, and for which required linear system solutions are small. As such, this method is suitable for real-time implementation. Simulation and timing results are presented.
Download RIR2FDN: An Improved Room Impulse Response Analysis and Synthesis
This paper seeks to improve the state-of-the-art in delay-networkbased analysis-synthesis of measured room impulse responses (RIRs). We propose an informed method incorporating improved energy decay estimation and synthesis with an optimized feedback delay network. The performance of the presented method is compared against an end-to-end deep-learning approach. A formal listening test was conducted where participants assessed the similarity of reverberated material across seven distinct RIRs and three different sound sources. The results reveal that the performance of these methods is influenced by both the excitation sounds and the reverberation conditions. Nonetheless, the proposed method consistently demonstrates higher similarity ratings compared to the end-to-end approach across most conditions. However, achieving an indistinguishable synthesis of measured RIRs remains a persistent challenge, underscoring the complexity of this problem. Overall, this work helps improve the sound quality of analysis-based artificial reverberation.