Concept

Downsampling (signal processing)

Related publications (62)

Pump-linewidth-tolerant wavelength multicasting using soliton Kerr frequency combs

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Lin Zhang, Amirhossein Mohajerin Ariaei

We experimentally demonstrate pump-linewidth-tolerant wavelength multicasting using microresonator-based soliton Kerr frequency combs. When Kerr comb lines serve as coherent pumps in a periodically poled lithium niobate waveguide, the linewidth of the mult ...

Optical Soc Amer2017

Introduction to the IEEE Journal on Selected Topics in Signal Processing and IEEE Transactions on Signal and Information Processing Over Networks Joint Special Issue on Graph Signal Processing

Pascal Frossard, Pier Luigi Dragotti

The papers in this special issue are intended to address some of the main research challenges in Graph Signal Processing by presenting a collection of the latest advances in the domain. These papers examine key representation, learning and processing aspec ...

2017

Multipliers-Driven Perturbation of Coefficients for Low-Power Operation in Reconfigurable FIR Filters

Andreas Peter Burg, Adam Shmuel Teman, Andrea Bonetti

Reconfigurable finite-impulse response (FIR) filters are one of the most widely implemented components in Internet of Things systems that require flexibility to support several target applications while consuming the minimum amount of power to comply with ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Learning Laplacian Matrix in Smooth Graph Signal Representations

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful graph is not alwa ...

Institute of Electrical and Electronics Engineers2016

A Multiscale Pyramid Transform for Graph Signals

Pierre Vandergheynst, David Shuman, Mohammadjavad Faraji

Multiscale transforms designed to process analog and discrete-time signals and images cannot be directly applied to analyze high-dimensional data residing on the vertices of a weighted graph, as they do not capture the intrinsic topology of the graph data ...

Institute of Electrical and Electronics Engineers2016

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the first

k

eigenvectors of the similarity matrix' Laplacian, whose computati ...

Ieee2016

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Design optimization of polyphase digital down converters for extremely high frequency wireless communications

Yusuf Leblebici, Gain Kim, Raffaele Capoccia

In this paper, an area-optimized polyphase digital down converter (DDC) architecture is introduced, where the mixers can be completely merged into the polyphase decimation filter under certain conditions. We also introduce an interface architecture, called ...

2015

Sub-Nyquist artifacts and sampling moiré effects, Part 2: Spectral-domain analysis

Isaac Amidror

Sampling moiré effects occur due to aliasing (foldover) when a continuous periodic signal g(x) is sampled using a sampling frequency that does not respect the Nyquist condition. However, visible beating artifacts may also occur when g(x) is sampled using s ...

2015

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Isaac Amidror

Sampling moiré effects are well known in signal processing. They occur when a continuous periodic signal g(x) is sampled using a sampling frequency fs that does not respect the Nyquist condition, and the signal frequency f folds-over and gives a new, false ...

The Royal Society Publishing2015

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Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the first

k

eigenvectors of the similarity matrix' Laplacian, whose computati ...

Ieee2016