Search results for "Signal"
showing 10 items of 6924 documents
Advanced nonlinear signal processing in silicon-based waveguides
2015
This talk presents recent progress in optical signal processing based on compact waveguides fabricated mainly using silicon germanium alloys. Applications include supercontinuum generation, wavelength conversion and signal regeneration.
Flip angle considerations in (3)helium-MRI.
2000
3Helium-MRI ((3)He-MRI) can be used for analysis of lung function, e. g. dynamic imaging of ventilation and gas diffusion within the lung, assessment of intrapulmonary oxygen concentrations and their time course. During imaging, the irreversible signal loss due to depolarizing radio frequency excitations can be described using the flip angle (FA) alpha. This parameter has to be quantified in order to account for it during quantitative assessment of the (3)helium signal intensity and its temporal development. This technical report reviews two different methods to determine alpha. Limitations and possible error sources of each method are discussed.
Compact-like pulse signals in a new nonlinear electrical transmission line
2013
International audience; A nonlinear electrical transmission line with an intersite circuit element acting as a nonlinear resistance is introduced and investigated. In the continuum limit, the dynamics of localized signals is described by a nonlinear evolution equation belonging to the family of nonlinear diffusive Burgers' equations. This equation admits compact pulse solutions and shares some symmetry properties with the Rosenau-Hyman K(2,2) equation. An exact discrete compactly- supported signal voltage is found for the network and the dissipative effects on the pulse motion analytically studied. Numerical simulations confirm the validity of analytical results and the robustness of these …
Special Issue on Signal Processing and Machine Learning for Biomedical Data
2021
This Special Issue is focused on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems. Biomedical data play a fundamental role in many fields of research and clinical practice. Very often the complexity of these data and their large volume makes it necessary to develop advanced analysis techniques and systems. Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging, requires new signal processing and machine learning methods. The recent progress in machine learning techniques, and in particular deep learning, revolutionized various f…
Continuous Refocusing for Integral Microscopy with Fourier Plane Recording
2018
Integral or light field imaging is an attractive approach in microscopy, as it allows to capture 3D samples in just one shot and explore them later through changing the focus on particular depth planes of interest. However, it requires a compromise between spatial and angular resolution on the 2D sensor recording the microscopic images. A particular setting called Fourier Integral Microscope (FIMic) allows maximizing the spatial resolution for the cost of reducing the angular one. In this work, we propose a technique, which aims at reconstructing the continuous light field from sparse FIMic measurements, thus providing the functionality of continuous refocus on any arbitrary depth plane. Ou…
Signal processing and frequency-dependent associative memory based on nanoswitches
2008
A signal processing concept based on nanoscale switches whose conductance can be tuned by an external stimulus between two (ON and OFF) states is proposed and analyzed theoretically. The building block of the system is formed by a metal nanoparticle linked to two electrodes by an organic ligand and a molecular switch. When we apply an alternating potential to the system of the same frequency as the periodic variation between the ON and OFF states induced on the switch, the net charge delivered by the system exhibits a sharp resonance. This resonance can be used to process an external signal by selectively extracting the weight of the different harmonics. In addition, a frequency-dependent a…
Introduction to Digital Signal Processing
2018
Signal processing deals with the representation, transformation, and manipulation of signals and the information they contain. Typical examples include extracting the pure signals from a mixture observation (a field commonly known as deconvolution) or particular signal (frequency) components from noisy observations (generally known as filtering). This chapter outlines the basics of signal processing and then introduces the more advanced concepts of time‐frequency and time‐scale representations, as well as emerging fields of compressed sensing and multidimensional signal processing. When moving to multidimensional signal processing, a modern approach is taken from the point of view of statis…
Proceedings of MLSP2012 [front matter]
2012
Inquiry-based environments for bio-signal processing training in engineering education
2021
Active student engagement, teaching via experience in real-life settings and learning by doing, are pedagogical strategies appropriate to improve student-reasoning skills. By building models, performing investigations, examining and explaining experimental results, using theoretical and computational thinking, constructing representations, undergraduates can acquire a deeper understanding of fundamental disciplinary concepts while reinforcing transversal abilities. In this framework, Engineering courses should be designed with the final objective to develop practical skills, focusing on hands-on activities. This contribution presents two different inquiry-based learning environments recent…