Download Analysis and Emulation of Early Digitally-Controlled Oscillators Based on the Walsh-Hadamard Transform Early analog synthesizer designs are very popular nowadays, and the discrete-time emulation of voltage-controlled oscillator (VCO) circuits is covered by a large number of virtual analog (VA) textbooks, papers and tutorials. One of the issues of well-known VCOs is their tuning instability and sensitivity to environmental conditions. For this reason, digitally-controlled oscillators were later introduced to provide stable tuning. Up to now, such designs have gained much less attention in the music processing literature. In this paper, we examine one of such designs, which is based on the Walsh-Hadamard transform. The concept was employed in the ARP Pro Soloist and in the Welson Syntex, among others. Some historical background is provided, along with a discussion on the principle, the actual implementation and a band-limited virtual analog derivation.
Download Equalizing Loudspeakers in Reverberant Environments Using Deep Convolutive Dereverberation Loudspeaker equalization is an established topic in the literature, and currently many techniques are available to address most practical use cases. However, most of these rely on accurate measurements of the loudspeaker in an anechoic environment, which in some occurrences is not feasible. This is the case, e.g. of custom digital organs, which have a set of loudspeakers that are built into a large and geometrically-complex piece of furniture, which may be too heavy and large to be transported to a measurement room, or may require a big one, making traditional impulse response measurements impractical for most users. In this work we propose a method to find the inverse of the sound emission system in a reverberant environment, based on a Deep Learning dereverberation algorithm. The method is agnostic of the room characteristics and can be, thus, conducted in an automated fashion in any environment. A real use case is discussed and results are provided, showing the effectiveness of the approach in designing filters that match closely the magnitude response of the ideal inverting filters.
Download PolyADAA: Improving Aliasing Reduction in Memoryless Nonlinearities Using Lagrange Interpolation and Polynomial Approximation Reducing the aliasing of nonlinear functions is an important problem in digital signal processing. The introduction of the Antiderivative Antialiasing (ADAA) method brought many benefits and is an active area of research. The current bottleneck in terms of aliasing reduction is the initial conversion from discrete- to continuous-time, which was previously done by linear interpolation. In this paper we derive PolyADAA, a method for computing the ADAA output when this conversion is done using higher order Lagrange interpolation. To obtain a viable solution, the nonlinear function is approximated using Chebyshev polynomials, which enable the ADAA integral to be computed. The paper provides numerical examples to show the effectiveness of the approach and discusses the advantages of the method.