[ABE-L] Seminário - Captura e processamento eficiente de sinais

[Hugo Carvalho]

Olá, pessoal. Escrevo para atualizar que a apresentação do Felipe
Pagginelli será no dia 07/03, presencial, na sala C-116 do Instituto de
Matemática da UFRJ.

Abraços!

Em sex., 3 de mar. de 2023 às 17:22, Hugo Carvalho <hugo em dme.ufrj.br>
escreveu:

> Prezados,
>
> Gostaria de lhes convidar para assistir a um seminário com um tema super
> interessante e atual, ministrado pelo Felipe Pagginelli. Com muito orgulho
> e satisfação, apresento meu primeiro aluno de Iniciação Científica
> (estudando Filtro de Kalman) e de Mestrado (dissertação
> <http://objdig.ufrj.br/11/teses/926242.pdf> sobre o Lema de
> Johnson-Lindenstrauss), hoje doutorando na Universidade Técnica de Munique
> sendo orientado por Felix Krahmer (TUM) e Ayush Bhandari (Imperial College
> London). Ele voou longe após a conclusão do Mestrado, está passando umas
> semanas no Brasil, e gostaria de nos trazer as novidades de sua pesquisa
> por lá. Portanto, segue abaixo informações sobre a apresentação.
>
> Abraços, e nos vemos lá!
>
> --
>
> *DATA:* 07/03/2023 (terça-feira)
>
> *LOCAL:* Presencial, no Instituto de Matemática da UFRJ (Sala C-116 ou
> C-119, informação a confirmar na segunda-feira)
>
> *HORÁRIO:* 14h
>
> *PALESTRANTE:* Felipe Pagginelli
>
> *TÍTULO:* Next generation digital acquisition using modulo nonlinearities
>
> *RESUMO: *One of the flagships of the Third Industrial — so-called
> "Digital" — Revolution is a mathematical result called Nyquist-Shannon's
> Theorem that allows for the perfect recovery of a bandlimited analog
> time-signal from a digital representation of it via sampling and
> quantization when samples are taken with at least with a minimum sampling
> rate (Nyquist's rate).
>
> Despite not being a requirement of that result, the electrical circuits —
> called analog-to-digital converters (ADCs) — that are used to implement it
> in real life are limited in the range of amplitudes — called Dynamic Range
> (DR) — of the signals that they can acquire. That is a major bottleneck in
> the area of Signal Processing, since Dynamic Range limitations yield
> information loss since the very acquisition of the input.
>
> The state-of-art methods can be summarized by the "acquired now, process
> process later" procedure, that are either: purely algorithmic-based, by
> "guessing" or combining various acquisitions of the same signal made by
> ADCs calibrated in different ranges; or purely hardware-based, by designing
> ADC with wider ranges. Nevertheless, both of those procedures are based on
> calibration techniques and lack theoretical recovery guarantees, since the
> ground-truth is unavoidably unknown.
>
> In contrast, the Unlimited Sampling Framework (USF) was recently proposed
> as the first paradigm that connects the hardware and algorithm parts to
> overcome the information loss. Namely, on the hardware side, the use of an
> ADC that folds the input signal inside its Dynamic Range (Self-reset ADC)
> via a (nonlinear) modulo operation is proposed; on the algorithmic side,
> they deal with the problem of unfolding those modulo samples.
>
> On their pioneering work, the authors were able to: provide a sufficient
> guarantee and an algorithm for perfect recovery in the noiseless setting by
> leveraging on oversampling — i.e., sampling above the Nyquist's sampling
> rate — and on the bandlimitedness and smoothness of the input signal. Also,
> that novel approach is single-shot — that is, requires just one acquisition
> of the input signal and admits inputs of unlimited amplitude.
>
> In our talk, we intend to discuss how that first algorithm behaves in the
> noisy setting, the theoretical reasons for that, and also to provide a
> sensibility analysis for it. Finally, we intend to share further approaches
> to that problem and to invite for future contributions.
>
> *ORIENTADORES:* Felix Krahmer (TUM), Ayush Bhandari (Imperial College
> London)
> *BOLSA:* JADS-IGSSE
>
> --
> Hugo Tremonte de Carvalho
>
> • Assistant Professor @
>  - Federal University of Rio de Janeiro (*UFRJ <https://ufrj.br/>*)
>  - Institute of Mathematics (*IM <http://www.im.ufrj.br/>*)
>  - Department of Statistical Methods (*DME <http://www2.dme.ufrj.br/>*)
>
> • Member of the MusMat Research Group <https://musmat.org/>
>
> • Coordinator of the Specialization in Data Science
> <http://www.im.ufrj.br/index.php/pt/ensino/pos-graduacao/pos-graduacao-do-im/cursos-lato-sensu/ciencia-de-dados>
>
> Personal website:
> *im.ufrj.br/~hugocarvalho/ <http://im.ufrj.br/~hugocarvalho/>*
>


-- 
Hugo Tremonte de Carvalho

• Assistant Professor @
 - Federal University of Rio de Janeiro (*UFRJ <https://ufrj.br/>*)
 - Institute of Mathematics (*IM <http://www.im.ufrj.br/>*)
 - Department of Statistical Methods (*DME <http://www2.dme.ufrj.br/>*)

• Member of the MusMat Research Group <https://musmat.org/>

• Coordinator of the Specialization in Data Science
<http://www.im.ufrj.br/index.php/pt/ensino/pos-graduacao/pos-graduacao-do-im/cursos-lato-sensu/ciencia-de-dados>

Personal website:
*im.ufrj.br/~hugocarvalho/ <http://im.ufrj.br/~hugocarvalho/>*
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