Efficient Distributed Multiresolution Processing for Data Gathering in Sensor Networks

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Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated with the signal of interest. The acquired data is then wirelessly transmitted ...

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In multichannel sampling, several sets of sub-Nyquist sampled signal values are acquired. The offsets between the sets are unknown, and have to be resolved, just like the parameters of the signal itself. This problem is nonlinear in the offsets, but linear ...

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Information transfer plays a central role in the biology of most organisms, particularly social species [1, 2]. Although the neurophysiological processes by which signals are produced, conducted, perceived, and interpreted are well understood, the conditio ...

Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This par ...

In the general context of complex data processing, this paper reviews a recent practical approach to the continuous wavelet formalism on the sphere. This formalism notably yields a correspondence principle which relates wavelets on the plane and on the sph ...

With the price of wireless sensor technologies diminishing rapidly we can expect large numbers of autonomous sensor networks being deployed in the near future. These sensor networks will typically not remain isolated but the need of interconnecting them on ...

Site-specific radiation damage on anomalously scattering sites can be used to generate additional phase information in standard single- or multi-wavelength anomalous diffraction (SAD or MAD) experiments. In this approach the data are kept unmerged, down to ...

The transceivers of a wireless sensor network (WSN) have to fulfill the low-power and low-voltage constraints. The WiseNET project has already proven that it is possible to design a receiver working at 1V and consuming less than 2mW. However this transceiv ...

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In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the A/D converter, etc. A low-pass filter is then often applied before the sampling operation to avoid aliasing. However ...

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This thesis explores the application of ensemble methods to sequential learning tasks. The focus is on the development and the critical examination of new methods or novel applications of existing methods, with emphasis on supervised and reinforcement lear ...

We discuss variance estimation by resampling in surveys in which data are missing. We derive a formula for jackknife linearization in the case of calibrated estimation with deterministic regression imputation, and compare the resulting variance estimates w ...

We present a general framework and an efficient algorithm for tracking relevant video structures. The structures to be tracked are implicitly defined by a Matching Pursuit procedure that extracts and ranks the most important image contours. Based on the ra ...

Recent advances in wireless communications and computing technology are enabling the emergence of low-cost devices that incorporate sensing, processing, and communication functionalities. A large number of these devices are deployed in the field to create ...

We aim at developing autonomous micro-flyers capable of navigating within houses or small indoor environments using vision as principal source of information. Due to severe weight and energy constraints, inspiration is taken from the fly for the selection ...

We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds whi ...

Efficient Distributed Multiresolution Processing for Data Gathering in Sensor Networks

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Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime

The Collective Memory of Amnesic Processes

Groebner Basis Methods for Multichannel Sampling with Unknown Offsets

Distributed Media Rate Allocation in Multipath Networks

Evolutionary Conditions for the Emergence of Communication in Robots

Learning Multi-Modal Dictionaries

Complex data processing: fast wavelet analysis on the sphere

Infrastructure for data processing in large-scale interconnected sensor networks

Modelling and refining site-specific radiation damage in SAD/MAD phasing

Low-power and low-voltage delta-sigma analog-to-digital converters for digital radio in standard CMOS technology

Experiences with Reproducible Research in Various Facets of Signal Processing Research

On the modelling of multi-modal data using redundant dictionaries

Super-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods

A profiling framework for high level design space exploration for memory and system architectures

Ensembles for sequence learning

Resamping variance estimation in surveys with missing data

Tracking Atoms with Particles for Audio-visual Source Localization

Distributed routing algorithms for sensor networks

Fly-inspired Visual Steering of an Ultralight Indoor Aircraft

Power-Efficient Sensor Placement and Transmission Structure for Data Gathering under Distortion Constraints