Real time tube guitar amplifier simulation using WebAudio

This paper presents a tube guitar amplifier simulation made with the WebAudio API, that reproduces the main parts of the Marshall JCM 800 amplifier schematics. Each stage of the real amp has been recreated (preamp, tone stack, reverb, power amp and speaker simulation, and we added an extra multiband EQ). The “classic rock” amp simulation we built has been used in real gigs and can be compared with some native amp simulation both in terms of latency, sound quality, dynamics and comfort of the guitar play. Unfortunately, as of today, low latency can be achieved only with certain configurations, due to audio driver limitations of current browsers on certain operating systems. The paper discusses the latency problems encountered with WebAudio, common traps, current limitations, and proposes some solutions. The final web based simulation has been compared with native recreations of the same amp model (including commercial products such as GuitarRig, the JCM800 amp included in GarageBand or the open source Guitarix amp sim that runs on Linux), and with a real amp: the Yamaha THR10 that comes with a model of a Marshall amp. We conducted both quantitative evaluations (measure of the “guitar-to-speaker” latency, group delay, frequency response analysis) and qualitative evaluations with real guitar players who compared, guitar in hands, the different simulations in terms of sound quality and dynamics, and more generally “how they feel playing guitar with these simulations”. The amp is open source1 and can be tested online2, even without a guitar (it comes with an audio player, dry guitar samples and a wave generator that can be used at input). The Web page contains links to the source code repository, tutorial videos and a complete report of the measures we made, with different configurations (various soundcard, operating system, browsers), that is summarized in this paper. Figure 1 shows the current GUI (with optional frequency analyzers and oscilloscopes we used to probe the signal at different stages of the simulation). Our initial goal was to evaluate the limits of the WebAudio API and see if it was possible to design a web based guitar amp simulator that could compete with native simulations

Gröbner bases and wavelet design

AbstractIn this paper, we detail the use of symbolic methods in order to solve some advanced design problems arising in signal processing. Our interest lies especially in the construction of wavelet filters for which the usual spectral factorization approach (used for example to construct the well-known Daubechies filters) is not applicable. In these problems, we show how the design equations can be written as multivariate polynomial systems of equations and accordingly how Gröbner algorithms offer an effective way to obtain solutions in some of these cases

Balanced Multiwavelets Theory and Design

This paper deals with multiwavelets which are a recent generalization of wavelets in the context of multirate filter banks and with their applications to signal processing and especially compression. By their inherent structure, multiwavelets are fit for processing multi-channel signals. First, we will recall some general results on multifilters by looking at them as time-varying filters. Then, we will link this to multiwavelets, looking closely at the convergence of the iterated matrix product leading to them and the typical properties we can expect. Then, we will define under what conditions we can apply systems based on multiwavelets to one-dimensional signals in a simple way. That means we will give some natural and simple conditions that should help in the design of new multiwavelets for signal processing. Finally, we will provide some tools in order to construct multiwavelets with the required properties, the so-called `balanced multiwavelets'

High-order balanced multiwavelets: theory, factorization, and design

This correspondence deals with multiwavelets, which are a recent generalization of wavelets in the context of time-varying filter banks and with their applications to signal processing and especially com- pression. By their inherent structure, multiwavelets are fit for processing multichannel signals. This is the main issue in which we will be interested here. The outline of the correspondence is as follows. First, we will review material on multiwavelets and their links with multifilter banks and, especially, time-varying filter banks. Then, we will have a close look at the problems encountered when using multiwavelets in applications, and we will propose new solutions for the design of multiwavelets filter banks by introducing the so-called balanced multiwavelets

Evidence for horizontal transfer of a secondary metabolite gene cluster between fungi

Background Filamentous fungi synthesize many secondary metabolites and are rich in genes encoding proteins involved in their biosynthesis. Genes from the same pathway are often clustered and co-expressed in particular conditions. Such secondary metabolism gene clusters evolve rapidly through multiple rearrangements, duplications and losses. It has long been suspected that clusters can be transferred horizontally between species, but few concrete examples have been described so far. Results In the rice blast fungus Magnaporthe grisea, the avirulence gene ACE1 that codes for a hybrid polyketide synthase-nonribosomal peptide synthetase (PKS-NRPS) belongs to a cluster of 15 genes involved in secondary metabolism. Additional related clusters were detected in the ascomycetes Chaetomium globosum, Stagonospora nodorum and Aspergillus clavatus. Gene-by-gene phylogenetic analysis showed that in C. globosum and M. grisea, the evolution of these ACE1-like clusters is characterized by successive complex duplication events including tandem duplication within the M. grisea cluster. The phylogenetic trees also present evidence that at least five of the six genes in the homologous ACE1 gene cluster in A. clavatus originated by horizontal transfer from a donor closely related to M. grisea. Conclusion The ACE1 cluster originally identified in M. grisea is shared by only few fungal species. Its sporadic distribution within euascomycetes is mainly explained by multiple events of duplication and losses. However, because A. clavatus contains an ACE1 cluster of only six genes, we propose that horizontal transfer from a relative of M. grisea into an ancestor of A. clavatus provides a much simpler explanation of the observed data than the alternative of multiple events of duplication and losses of parts of the cluster