Andrea Ridolfi

Biography

I am a professor of Signal Processing and Communication Technologies at Bern University of Applied Sciences.

Since 2004 I hold a lecturer position at EPFL, teaching “Mathematical Principles of Signal Processing” (Doctoral School, 2004 – 2011), “Statistical Signal and Data Processing through Applications” (Master Program, (2004 – ongoing), and Signal Processing and Machine Learning for Digital Humanities (Master, 2017 – 2019, co-taught with Mathieu Salzmann).

Previously, I have been working as Project Manager and R&D Engineer at EPFL (2011-2014), coordinating the LCAV activities within the NSF – Nanotera project Opensense, and as Project Manager and R&D Engineer with the biomedical signal processing group at CSEM (2006-2011).

Official source

https://people.epfl.ch/andrea.ridolfi

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Experiences with Reproducible Research in Various Facets of Signal Processing Research

Guillermo Barrenetxea Kobas, Ivana Jovanovic, Andrea Ridolfi, Patrick Vandewalle, Martin Vetterli

How often have you been able to implement an algorithm as it is described in a paper? And when you did, were you confident that you had exactly the same parameter values and results as the authors of the paper? All too often, articles do not describe all the details of an algorithm and thus prohibit an implementation by someone else. In this paper, we describe our experience with reproducible research, a paradigm to allow other people to reproduce with minimal effort the results we have obtained. We discuss both the reproducibility of data and algorithms, and give examples for each of them. The effort required to make research reproducible is compensated by a higher visibility and impact of the results.

2007

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In this paper, we model a spatially varying channel where a source is moving along a random trajectory with respect to a fixed re- ceiver. The aim is to compute the power spectral density corre- sponding to the channel impulse response as a function of tempo- ral and spatial frequencies. The trajectory of the source follows an autoregressive model where the poles of the system control the smoothness of the path. Theoretical results are presented for the AR2 case and generalized to any ARn systems. Simulations results are shown and compared to the presented theory. The stochas- tic plenacoustic function analyzed in this paper also models time- varying channels governed by the wave equation, like they appear in acoustic echo cancellation or ultra wide band communication channels.

2006

Ultrawide Bandwidth Signals as Shot-Noise: a Unifying Approach

Andrea Ridolfi

We present a shot noise based model for a large family of ultrawide bandwidth (UWB) signals. These include time-hopping and direct-sequence signaling with pulse position, interval, and amplitude modulations. Each specific signal is constructed by adding features to a basic model in a modular, simple, and tractable way. Our work unifies the contributions scattered in the literature and provides a general approach that allows various extensions of previous works as well as new results. The exact power spectrum is then evaluated using shot noise spectral theory, which provides a simpler, systematic, and rigorous approach to the spectra evaluation of complicated UWB signals. The strength of our methodology is that different features of the signal model contribute clearly and separately to the resulting spectral expressions.

Institute of Electrical and Electronics Engineers2006