A survey of uncertainty principles and some signal processing applications
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The theme of this thesis revolves around three important manifestations of light, namely its corpuscular, wave and electromagnetic nature. Our goal is to exploit these principles to analyze, design and build imaging modalities by developing new signal proc ...
Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...
This article aims to study crowd dynamics in small teams. In particular we are specifically interested to internal crowdsourcing as a venue for innovation and new ideas production, questioning the difference with regard to other cooperative models based, e ...
Signal processing tools are presented from an intuitive geometric point of view which is at the heart of all modern signal processing techniques. The student will develop the mathematical depth and rigour needed for the study of advanced topics in signal p ...
Effective representation methods and proper signal priors are crucial in most signal processing applications. In this thesis we focus on different structured models and we design appropriate schemes that allow the discovery of low dimensional latent struct ...
A Python package for room acoustics. This package would allow us to simulate sound propagation in a closed room allowing us to predict a situation, compare it with experimental results or apply calculations for various signal processing applications. ...
Wikipedia has become a widely-used resource on signal processing. However, the freelance-editing model of Wikipedia makes it challenging to maintain a high content quality. We develop techniques to monitor the network structure and content quality of Signa ...
Wikipedia has become a widely-used resource on signal processing. However, the freelance-editing model of Wikipedia makes it challenging to maintain a high content quality. We develop techniques to monitor the network structure and content quality of Signa ...
There are a wide variety of applications that are able to tolerate small errors in the values of the outputs, provided they are within the application-specific thresholds. For such applications, there have been many efforts to study the tradeoff involved i ...
Sparsity has been one of the major drives in signal processing in the last decade. Structured sparsity has also lately emerged as a way to enrich signal priors towards more meaningful and accurate representations. In this paper we propose a new structured ...