A Chronology of Interpolation: From Ancient Astronomy to Modern Signal and Image Processing

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We developed an extended reciprocity theorem approach to model neuron signals which handles heterogeneous dielectric environments and arbitrary electrode shapes, and use it to study analytically the single fiber action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model evoked compound action potential (eCAP) signals from multi-fascicular nerves populated with heterogeneous fiber populations. For validation, model predictions w

A search for heavy neutral leptons (HNLs) with the CMS experiment in final states with tau leptons is set up and optimized. The targeted final states contain 3 prompt leptons, of which at least one is a hadronic tau. The analysed channels are eµτ , eττ and µττ. The search is performed using simulated event samples with HNL masses ranging from 100 GeV to 900 GeV and is the first search in this mass range. The signal is extracted from a combined fit to different kinematic observables in the various three-lept

This goal of this paper is the characterisation of surface roughness of 3D object scanned via micro CT. The idea is to extract the fractal dimension D of a 3D cloud of points. This project follows the work of a previous student project: Characterisation of the surface roughness of 3D objects from micro CT. Two methods were compared the box counting method and extraction of the power spectrum of the signal formed by the fragment profile.

In this thesis, we explore 3 main topics: non-uniform (in time) sub-sampling, QRS detection in an event-based sub-sampled ECG (electrocardiogram) and implementation on a low-power MCU (Micro Controller Unit). The main idea behind this work is to reduce the energy consumption of a QRS detection algorithm by adapting the sampling frequency using the local frequency of the signal while maintaining the overall performance on the QRS detection without degradation. In particular, we will focus on the compréhensio

The ability of human auditory systems to focus on one signal and ignore other signals in an auditory scene where several auditory events are taking place, often referred to as cocktail-party effect, is a key to localization of sound sources. This ability is partly made possible by interaural cues – Interaural Time Differences (ITDs) and Interaural Level Differences (ILDs) – between the input ear signals that assist the estimation of source azimuth angles, and separation of the signal of the desired directio

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 recover a one-dimensional sparse signal from its autocorrelation. We present a sufficient condition for the recovery to be unique, and propose an iterative algorithm that can obtain the original signal (up to a sign change, time-shift and time-reversal). Num

In this work package (WP), we investigate the possibility of discovering structure within dictionary learning. This could range from exploring groups of atoms that appear in clusters - a form of molecule learning - to learning graphical dependencies across the dictionary elements. In modeling a signal as a sparse combination of atoms, ties between atoms can be enforced. For example harmonic models Gabor dictionaries can be seen as this type of model. Here we aim to explore the "molecule-learning" problem -

We consider the problem of signal design for transmission over an interference channel, along the lines of the recently proposed strategy of Interference Alignment. In the framework of interference alignment, each receiver maintains an interference subspace. The transmitters shape their transmissions such that all the interference seen at a particular receiver falls into its interference subspace, hence allowing the remaining receiver space to be used for reception of the useful signal. In contrast to previ

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 idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vei

Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are much shorter than typical room impulse responses. We present a feature extraction technique based on modeling temporal envelopes of the speech signal in narrow sub-bands using Frequency Domain Linear Prediction (FDLP). FDLP provides an all-pole approximatio

The aim of this project is the analysis of different approaches for curve and surface reconstruction and the development of a related MATLAB library. We initially study the Lagrange polynomial interpolation, then the Bezier, the B-splines and the NURBS curves and finally we introduce the NURBS surfaces. At each step we list the useful properties of the different approaches, the details of the mathematical representation and the evolution from simpler to more complicated representations.

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 ranking, the contours are automatically selected to initialize a Particle Filtering tracker. The proposed algorithm deals with salient video entities whose behavior has an intuitive meaning, related to the physics of the signal. Moreover, as the interactions

We have used electrically detected magnetic resonance (EDMR) to study the spin dependent processes on the operation of diodes based on poly(2-metoxy-5-(2'-etil-hexiloxy)-1,4-phenylene vinylene) (MEH-PPV) and on tris-8-hydroxyquinoline-aluminum (Alq3). In MEH-PPV based diodes, the EDMR signal is found to be composed of two lines, a Lorentzian with ΔHpp=5 G and a Gaussian with ΔHpp=24 G. The g-factor of both components is about 2.0022. The signal is quenching, typi

The Karhunen-Loeve transform (KLT) is a key element of many signal processing tasks, including approximation, compression, and classification. Many recent applications involve {\em distributed} signal processing where it is not generally possible to apply the KLT to the signal; rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approximations to the KLT. First, we present explicit solutions to special cases, including a partial KLT (where only a subset of

Basics of the theory of direct chaotic communications is presented. We introduce the notion of chaotic radio pulse and consider the signal structures and modulation methods applicable in direct chaotic schemes. Signal processing in noncoherent and coherent receivers is discussed. The efficiency of direct chaotic communications is investigated by means of numerical simulation. Potential application areas are analyzed, including multiple access systems.

In recent years, wavelet-based algorithms have been successful in different signal processing tasks. The wavelet trans- form is a powerful tool because it manages to represent both tran- sient and stationary behaviors of a signal with few transform coeffi- cients. Discontinuities often carry relevant signal information, and therefore, they represent a critical part to analyze. In this paper, we study the dependency across scales of the wavelet coefficients generated by discontinuities. We start by showing t

This article describes a method of constructing parametric models out of captured motion and skeleton data. Casting the problem as scattered data interpolation, our work is based on a multi-step approximation for the interpolation function with motion data compressed by principal component analysis. This leads to smaller storage and faster computation than those of previous approaches based on classical methods of exact interpolation. As a result, motion models can be constructed out of a rich set of exampl

We have modified the popular Mbone tool vic (VIdeo Conferencing) to use Arequipa (Application REQuested IP over ATM). The latter enables applications and in particular vic, to request a direct ATM connection for its exclusive use and to directly control the traffic parameters of this connection. We have also implemented ATM Forums UNI4.0 signaling and ITU-Ts connection modification recommendation Q.2963.1, on end-systems as well as on switches. This implementation, coupled with the Arequipa mechanism, all

Our goal in this paper is to set a theoretical basis for the comparison of re-sampling and interpolation methods. We consider the general problem of the approximation of an arbitrary continuously-defined function f(x)—not necessarily bandlimited—when we vary the sampling step T. We present an accurate

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computation of the induced approximation error as a function of T for a general class of linear approximation operators including interpolation and other kinds of projectors. This new quantitative

This paper deals with multiwavelets which are a recent generalization of wavelets in the context of multirate filter banks and with their applications to signal processing and especially compression. By their inherent structure, multiwavelets are fit for processing multi-channel signals. First, we will recall some general results on multifilters by looking at them as time-varying filters. Then, we will link this to multiwavelets, looking closely at the convergence of the iterated matrix product leading to t

A Chronology of Interpolation: From Ancient Astronomy to Modern Signal and Image Processing

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Simulation insights on the compound action potential in multifascicular nerves

A search for heavy neutral leptons in tau lepton final states with the CMS Experiment

On the Characterisation of the Surface Roughness of 3d Object Scanned with Micro CT

Pattern Recognition in Non-uniformly sampled electrocardiogram signal for wearable sensors

Implementing a Cocktail-party Processor via Time-frequency Masking

Sparse spectral factorization: Unicity and Reconstruction Algorithms

Deliverable 3.2: Report on Discovering Structure within Dictionary Learning

An Iterative Algorithm for Joint Signal and Interference Alignment

Signal Processing for Communications

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Geometrical reconstruction of curves and surfaces using NURBS

Tracking Atoms with Particles

Electrically detected magnetic resonance of organic and polymeric light emitting diodes

The distributed Karhunen-Loeve transform

Introduction in direct chaotic communications

Wavelet Footprints: Theory, Algorithms and Applications

Construction of animation models out of captured data

Using Quality of Service can be simple: Arequipa with Renegotiable ATM connections

Quantitative $ L ^{ 2 } $ Error Analysis for Interpolation Methods and Wavelet Expansions

Balanced MultiWavelets - Theory and Design