Publication

Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

Mohammad Amin Shokrollahi, Seyed Armin Tajalli, Harm Cronie
2012
Patents

Résumé

In bus communications methods and apparatus, a first set of physical signals representing the information to be conveyed over the bus is provided, and mapped to a codeword of a sparse signaling code, wherein a codeword is representable as a vector of a plurality of components, some of which are quiescent components and some of which are non-quiescent components, wherein the number of quiescent components and non-quiescent components meet a sparseness requirement.

Source officielle

https://infoscience.epfl.ch/entities/publication/65d1aad6-887d-4f8f-8ac1-9f58ddd40afa

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Mohammad Amin Shokrollahi, Seyed Armin Tajalli, Harm Cronie
2012
Patents

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/65d1aad6-887d-4f8f-8ac1-9f58ddd40afa

À propos de ce résultat

Concepts associés (28)

Sparse dictionary learning

Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims at finding a sparse representation of the input data in the form of a linear combination of basic elements as well as those basic elements themselves. These elements are called atoms and they compose a dictionary. Atoms in the dictionary are not required to be orthogonal, and they may be an over-complete spanning set. This problem setup also allows the dimensionality of the signals being represented to be higher than the one of the signals being observed.

Amplificateur opérationnel

thumb|300px|Différents modèles d'amplificateurs opérationnels. thumb|300px|La représentation schématique d'un amplificateur opérationnel varie suivant les normes ANSI/IEEE et IEC 60617-13. Un amplificateur opérationnel (aussi dénommé ampli-op ou ampli op, AO, AOP, ALI ou AIL) est un amplificateur différentiel à grand gain : c'est un amplificateur électronique qui amplifie fortement une différence de potentiel électrique présente à ses entrées.

Sparse approximation

Sparse approximation (also known as sparse representation) theory deals with sparse solutions for systems of linear equations. Techniques for finding these solutions and exploiting them in applications have found wide use in , signal processing, machine learning, medical imaging, and more. Consider a linear system of equations , where is an underdetermined matrix and . The matrix (typically assumed to be full-rank) is referred to as the dictionary, and is a signal of interest.

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