Combination of adaptive filters


My Master's topic involves studying combinations of adaptive filters from a formal viewpoint to try and answer questions such as: "What exactly is a combination of adaptive filters? How can we formally define it?", "What is the best way to combine a set of adaptive filters?", "How does each type of combination compare to each other?"... In summary, this project has 3 goals: (i) setting forth a taxonomy to classify existing combinations based on an extensive literature review; (ii) proposing a more general definition of combination, under which new combinations can be put forward and/or improvements can be made on the existing ones; and (iii) building an analysis framework based on this definition.



The development and test of adaptive filters relies heavily on Monte Carlo simulations in MATLAB in order to assess their performance and tune their designs. However, these ensemble average experiments can rapidly become time consuming, especially when thorough parametric tests are necessary. The AFTBX provides an intuitive interface to vectorized adaptive algorithms that are up to 10 times faster than commonly used implementations. These adaptive filters include LMS, NLMS, LMF, RLS, convex supervisor, affine supervisor... Moreover, a comprehensive data modeling function is provided to ease the prototyping in different environments.


Aircraft cabin simulator


The drop in airfares has made air passenger traffic grow fast in the last few decades. This increase in competition has made aircraft carriers and manufacturers aware of the need to find new ways to attract customers, inevitably turning to the comfort factor. Although studies on automotive comfort are abundant, those on aircraft environments are still scarce, partly due to the difficulties in running experiments (costs, risks...). In order to address these issues, a real-size aircraft cabin simulator was built at the University of São Paulo with capability of controlling variables such as sound, vibration, temperature, air flow, pressure, and lighting. This project involved the Brazilian aeronautic industry and several other universities, running more than 60 simulated flights with over 1000 people.

Underwater probe


Underwater sensing is an intricate problem from a probe engineering point of view, even more so in oceanographic applications where salinity, temperature variations, and high pressure are fundamental components of the environment. This project puts forward a new concept in underwater probe, engineered from scratch to address the main issues found in these instruments. Impermeability, submerged data transfer, charging... all important aspects of the system have been designed to improve performance and provide ease of use and reliability during measurements. Furthermore, a low budget constraint was imposed on the project so that it could be used not only for research, but also for educational purposes. In 2012, the wireless power subsystem of the probe was awarded an IEEE SEC grant.