Verfahren zur direkten Implementierung von Algorithmen auf Gatterebene

Bit serial, processing, digital signal processing, transmission, time division, linear programming, linear optimization

Estudi sobre equalització electrònica per a sistemes de comunicació per fibra òptica

Estudi realitzat a partir d’una estada a Bell Labs (Lucent Technologies), New Jersey (Estats Units), entre el 15 de setembre de 2005 i el 15 de gener de 2006. Els sistemes de transmissió per fibra òptica fonamenten les principals xarxes de comunicacions. A mesura que la demanda d’ample de banda per usuari creixi, seran necessaris nous sistemes que siguin capaços de cobrir les necessitats a curt i llarg termini. La tecnologia dels sistemes òptics limita fortament la complexitat dels sistemes de transmissió / recepció en comparació, per exemple, als sistemes d’ones de ràdio. La tendència és la de dissenyar sistemes avançats amb detecció directa i mirar d’aplicar tècniques bàsiques de processat del senyal. Una d’aquestes tècniques és l’equalització electrònica, és a dir, fer ús de les tècniques de processament del senyal per tal de compensar la distorsió introduïda pel canal, deguda per una o diverses degradacions típiques: dispersió cromàtica, efectes no lineals, dispersió del mode de polarització (PMD) ... Dins d’un entorn comercial d’empresa, s’ha avaluat el funcionament dels sistemes d’equalització FFE-DFE aixi com MLSE en presència de dispersió cromàtica i/o dispersió del mode de polarització (PMD) en transmissions NRZ/RZ.

Coronary magnetic resonance angiography for assessment of the stent lumen: a phantom study.

PURPOSE: To evaluate the feasibility of visualizing the stent lumen using coronary magnetic resonance angiography in vitro. MATERIAL AND METHODS: Nineteen different coronary stents were implanted in plastic tubes with an inner diameter of 3 mm. The tubes were positioned in a plastic container filled with gel and included in a closed flow circuit (constant flow 18 cm/sec). The magnetic resonance images were obtained with a dual inversion fast spin-echo sequence. For intraluminal stent imaging, subtraction images were calculated from scans with and without flow. Subsequently, intraluminal signal properties were objectively assessed and compared. RESULTS: As a function of the stent type, various degrees of in-stent signal attenuation were observed. Tantalum stents demonstrated minimal intraluminal signal attenuation. For nitinol stents, the stent lumen could be identified, but the intraluminal signal was markedly reduced. Steel stents resulted in the most pronounced intraluminal signal voids. CONCLUSIONS: With the present technique, radiofrequency penetration into the stents is strongly influenced by the stent material. Thesefindings may have important implicationsforfuture stent design and stent imaging strategies.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Experimentació amb un receptor software GPS-Galileo d'alta sensibilitat per a entorns interiors

Este proyecto se centra en el análisis de señales GPS, utilizando un receptor software desarrollado con Matlab en un proyecto de investigación para la Agencia Espacial Europea (ESA), llevado a cabo por parte del departamento de Telecomunicaciones e Ingeniería de Sistemas de la ETSE. Este software utiliza técnicas de procesado de señal de alta sensibilidad (HS-GNSS) que permite al usuario determinar su posición en entornos de difícil propagación como puede ser el caso de los escenarios interiores. Los datos experimentales se analizan en función del nivel de multipath que afecta a la señal de cada uno de los satélites, y la degradación que los escenarios interiores provocan en las señales, a causa del mobiliario, paredes, personas, etc. Para analizar los datos experimentales, se ha utilizado una métrica presentada en el congreso internacional EuCAP 2009, con la que es posible caracterizar las señales en función del nivel de multipath.

Simultaneous cell morphometry and refractive index measurement with dual-wavelength digital holographic microscopy and dye-enhanced dispersion of perfusion medium.

Digital holographic microscopy (DHM) allows optical-path-difference (OPD) measurements with nanometric accuracy. OPD induced by transparent cells depends on both the refractive index (RI) of cells and their morphology. This Letter presents a dual-wavelength DHM that allows us to separately measure both the RI and the cellular thickness by exploiting an enhanced dispersion of the perfusion medium achieved by the utilization of an extracellular dye. The two wavelengths are chosen in the vicinity of the absorption peak of the dye, where the absorption is accompanied by a significant variation of the RI as a function of the wavelength.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Sub-cortical and brainstem sites associated with chemo-stimulated increases in ventilation in humans.

We investigated the neural basis for spontaneous chemo-stimulated increases in ventilation in awake, healthy humans. Blood oxygen level dependent (BOLD) functional MRI was performed in nine healthy subjects using T2 weighted echo planar imaging. Brain volumes (52 transverse slices, cortex to high spinal cord) were acquired every 3.9 s. The 30 min paradigm consisted of six, 5-min cycles, each cycle comprising 45 s of hypoxic-isocapnia, 45 s of isooxic-hypercapnia and 45 s of hypoxic-hypercapnia, with 55 s of non-stimulatory hyperoxic-isocapnia (control) separating each stimulus period. Ventilation was significantly (p<0.001) increased during hypoxic-isocapnia, isooxic-hypercapnia and hypoxic-hypercapnia (17.0, 13.8, 24.9 L/min respectively) vs. control (8.4 L/min) and was associated with significant (p<0.05, corrected for multiple comparisons) signal increases within a bilateral network that included the basal ganglia, thalamus, red nucleus, cerebellum, parietal cortex, cingulate and superior mid pons. The neuroanatomical structures identified provide evidence for the spontaneous control of breathing to be mediated by higher brain centres, as well as respiratory nuclei in the brainstem.

Electrical neuroimaging reveals intensity-dependent activation of human cortical gustatory and somatosensory areas by electric taste.

To analyze the neural basis of electric taste we performed electrical neuroimaging analyses of event-related potentials (ERPs) recorded while participants received electrical pulses to the tongue. Pulses were presented at individual taste threshold to excite gustatory fibers selectively without concomitant excitation of trigeminal fibers and at high intensity evoking a prickling and, thus, activating trigeminal fibers. Sour, salty and metallic tastes were reported at both intensities while clear prickling was reported at high intensity only. ERPs exhibited augmented amplitudes and shorter latencies for high intensity. First activations of gustatory areas (bilateral anterior insula, medial orbitofrontal cortex) were observed at 70-80ms. Common somatosensory regions were more strongly, but not exclusively, activated at high intensity. Our data provide a comprehensive view on the dynamics of cortical processing of the gustatory and trigeminal portions of electric taste and suggest that gustatory and trigeminal afferents project to overlapping cortical areas.

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

Abstracting qualitative information for process supervision

Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.