Publication

A survey of uncertainty principles and some signal processing applications

Related publications (33)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Compressive Sampling Strategies for Multichannel Signals

Mohammad Golbabaee

Over the past decade researches in applied mathematics, signal processing and communications have introduced compressive sampling (CS) as an alternative to the Shannon sampling theorem. The two key observations making CS theory widely applicable to numerou ...

EPFL2012

Filtered Variation method for denoising and sparse signal processing

Volkan Cevher

We propose a new framework, called Filtered Variation (FV), for denoising and sparse signal processing applications. These problems are inherently ill-posed. Hence, we provide regularization to overcome this challenge by using discrete time filters that ar ...

2012

Trends in Bioimaging and Signal Processing

Michaël Unser

This is the second in a series of three columns summarizing the "Trends" expert sessions organized by the Signal Processing Society Technical Committees during ICASSP 2011 in Prague, Czech Republic. Readers have an opportunity to access these Trends sessio ...

IEEE2011

Sparse spectral factorization: Unicity and Reconstruction Algorithms

Martin Vetterli, Yue Lu

Spectral factorization is a classical tool in signal processing and communications. It also plays a critical role in X-ray crystallography, in the context of phase retrieval. In this work, we study the problem of sparse spectral factorization, aiming to re ...

2011

Distributed Detection Over Adaptive Networks Using Diffusion Adaptation

Ali H. Sayed

We study the problem of distributed detection, where a set of nodes is required to decide between two hypotheses based on available measurements. We seek fully distributed and adaptive implementations, where all nodes make individual real-time decisions by ...

IEEE2011

Frame Domain Signal Processing: Framework and Applications

Martin Vetterli, Amina Chebira

Besides basis expansions, frames representations play a key role in signal processing. We thus consider the problem of frame domain signal processing, which is more complex and challenging than transform domain processing. Examples of such processing aboun ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Multimodal Signal Processing: Methods and Techniques to Build Multimodal Interactive Systems

Jean-Philippe Thiran, Hervé Bourlard, Ferran Marqués

Multimodal signal processing is an important new field that processes signals from a variety of modalities - speech, vision, language, text- derived from one source, which aids human-computer and human-human interaction. The overarching theme of this book ...

Academic Press2009

Reproducible Research in Signal Processing - What, why, and how

Martin Vetterli, Patrick Vandewalle

Have you ever tried to reproduce the results presented in a research paper? For many of our current publications, this would unfortunately be a challenging task. For a computational algorithm, details such as the exact data set, initialization or terminati ...

Institute of Electrical and Electronics Engineers2009

Signal Processing for Communications

Martin Vetterli, Paolo Prandoni

With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The threatment is therefore less focused on the mathematics and more on the conceptual aspects, the ...

EPFL Press, CRC2008

Dataflow/Actor-Oriented language for the design of complex signal processing systems

Marco Mattavelli, Christophe Lucarz, Ghislain Roquier

Signal processing algorithms become more and more complex and the algorithm architecture adaptation and design processes cannot any longer rely only on the intuition of the designers to build efficient systems. Specific tools and methods are needed to cope ...

2008