Month: November 2018

Monitoring embedded space quality for classification

November 27, 2018 Matt No Comments Manifold learning, Deep Learning, Python
This entry is part 2 of 2 in the series Deep adventures

A few weeks ago, on StackOverflow, a user asked for an accuracy measure on the embedded space for an autoencoder. This was with Keras, but I thought it would be a nice exercise for Tensorflow as well.

The idea in this case is to add a few layers to the embedded space to create a classifier and measure its accuracy while we optimize the autoencoder.

We will train the autoencoder in alternation with the classifier. When one is updated, the other will be frozen, and then we can measure classification accuracy and reconstruction loss concurrently in Tensorboard.

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From netlist to code: strategies to implement schematics modelling

November 20, 2018 Matt 2 Comments Electronic, Music, Digital filters, SPICE, Python, C++
This entry is part 8 of 13 in the series Analog modelling

Today, I’m presenting at the ADC my work on analog modelling for the past year.

I will make a more detailed post later this year, but I’d like to put some teasers here. SPICE net lists are an efficient way of representing electronics circuits and there are several very good free and paying simulators. Unfortunately, they are not easy to integrate in a VST plugin.

Audio ToolKit now has a sister project around this topic. The lite version is also licensed under the BSD and can generate a dynamic filter of a net list. The full project is now also capable of generating static filter, with a source file (and compiling it in memory) that can be manually tuned.

Future work on this project will include different solvers for the static filter, as well as a tuner that will be able to drop entries in the Jacobian (full entries or component contributions for a given pin) in the Newton Raphson solver.

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