Theory and numerical integration of subsurface light transport

En synthèse d’images, reproduire les effets complexes de la lumière sur des matériaux transluminescents, tels que la cire, le marbre ou la peau, contribue grandement au réalisme d’une image. Malheureusement, ce réalisme supplémentaire est couteux en temps de calcul. Les modèles basés sur la théorie de la diffusion visent à réduire ce coût en simulant le comportement physique du transport de la lumière sous surfacique tout en imposant des contraintes de variation sur la lumière incidente et sortante. Une composante importante de ces modèles est leur application à évaluer hiérarchiquement l’intégrale numérique de l’illumination sur la surface d’un objet. Cette thèse révise en premier lieu la littérature actuelle sur la simulation réaliste de la transluminescence, avant d’investiguer plus en profondeur leur application et les extensions des modèles de diffusion en synthèse d’images. Ainsi, nous proposons et évaluons une nouvelle technique d’intégration numérique hiérarchique utilisant une nouvelle analyse fréquentielle de la lumière sortante et incidente pour adapter efficacement le taux d’échantillonnage pendant l’intégration. Nous appliquons cette théorie à plusieurs modèles qui correspondent à l’état de l’art en diffusion, octroyant une amélioration possible à leur efficacité et précision.

Theory for the Photoacoustic Response to X-Ray Absorption

A microscopic theory is presented for the photoacoustic effect induced in solids by x-ray absorption. The photoacoustic effect results from the thermalization of the excited Auger electrons and photoelectrons. We explain the dependence of the photoacoustic signal S on photon energy and the proportionality to the x-ray absorption coefficient in agreement with recent experiments on Cu. Results are presented for the dependence of S on photon energy, sample thickness, and the electronic structure of the absorbing solid.

1.55 µm High-Speed QDs Lasers for Optical Telecommunication Applications

In this work investigation of the QDs formation and the fabrication of QD based semiconductor lasers for telecom applications are presented. InAs QDs grown on AlGaInAs lattice matched to InP substrates are used to fabricate lasers operating at 1.55 µm, which is the central wavelength for far distance data transmission. This wavelength is used due to its minimum attenuation in standard glass fibers. The incorporation of QDs in this material system is more complicated in comparison to InAs QDs in the GaAs system. Due to smaller lattice mismatch the formation of circular QDs, elongated QDs and quantum wires is possible. The influence of the different growth conditions, such as the growth temperature, beam equivalent pressure, amount of deposited material on the formation of the QDs is investigated. It was already demonstrated that the formation process of QDs can be changed by the arsenic species. The formation of more round shaped QDs was observed during the growth of QDs with As2, while for As4 dash-like QDs. In this work only As2 was used for the QD growth. Different growth parameters were investigated to optimize the optical properties, like photoluminescence linewidth, and to implement those QD ensembles into laser structures as active medium. By the implementation of those QDs into laser structures a full width at half maximum (FWHM) of 30 meV was achieved. Another part of the research includes the investigation of the influence of the layer design of lasers on its lasing properties. QD lasers were demonstrated with a modal gain of more than 10 cm-1 per QD layer. Another achievement is the large signal modulation with a maximum data rate of 15 Gbit/s. The implementation of optimized QDs in the laser structure allows to increase the modal gain up to 12 cm-1 per QD layer. A reduction of the waveguide layer thickness leads to a shorter transport time of the carriers into the active region and as a result a data rate up to 22 Gbit/s was achieved, which is so far the highest digital modulation rate obtained with any 1.55 µm QD laser. The implementation of etch stop layers into the laser structure provide the possibility to fabricate feedback gratings with well defined geometries for the realization of DFB lasers. These DFB lasers were fabricated by using a combination of dry and wet etching. Single mode operation at 1.55 µm with a high side mode suppression ratio of 50 dB was achieved.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A methodology and a tool to design of mixed-signal technology

This paper presents a tool box developed to read files describing a SIMULINK® model and translates it into a structural VHDL-AMS description. In translation process, all files and directory structures to simulate the translated model on SystemVision™ environment is generate. The tool box named MS2SV was tested by three models of commercially available digital-to-analogue converters. All models use the R2R ladder network to conversion, but the functionality of these three components is different. The methodology of conversion of the model is presents together with sort theory about R-2R ladder network. In the evaluation of the translated models, we used a sine waveform input signal and the waveform generated by D/A conversion process was compared by FFT analysis. The results show the viability of this type of approach. This work considers some of challenges set by the electronic industry for the further development of simulation methodologies and tools in the field of mixed-signal technology. © 2007 IEEE.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

Enhancing weak signal transmission through a feedforward network

The ability to transmit and amplify weak signals is fundamental to signal processing of artificial devices in engineering. Using a multilayer feedforward network of coupled double-well oscillators as well as Fitzhugh-Nagumo oscillators, we here investigate the conditions under which a weak signal received by the first layer can be transmitted through the network with or without amplitude attenuation. We find that the coupling strength and the nodes' states of the first layer act as two-state switches, which determine whether the transmission is significantly enhanced or exponentially decreased. We hope this finding is useful for designing artificial signal amplifiers.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

A Unitary Approach to Information and Estimation Theory in Digital Communication Systems

This thesis presents the outcomes of a Ph.D. course in telecommunications engineering. It is focused on the optimization of the physical layer of digital communication systems and it provides innovations for both multi- and single-carrier systems. For the former type we have first addressed the problem of the capacity in presence of several nuisances. Moreover, we have extended the concept of Single Frequency Network to the satellite scenario, and then we have introduced a novel concept in subcarrier data mapping, resulting in a very low PAPR of the OFDM signal. For single carrier systems we have proposed a method to optimize constellation design in presence of a strong distortion, such as the non linear distortion provided by satellites' on board high power amplifier, then we developed a method to calculate the bit/symbol error rate related to a given constellation, achieving an improved accuracy with respect to the traditional Union Bound with no additional complexity. Finally we have designed a low complexity SNR estimator, which saves one-half of multiplication with respect to the ML estimator, and it has similar estimation accuracy.

Performance Tuning Non-Uniform Sampling for Sensitivity Enhancement of Signal-Limited Biological NMR

Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20-40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling H-1,N-15-HSQC experiments on natural abundance protein samples and H-1,C-13-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.

Distortion-free enhancement of terahertz signals measured by electro-optic sampling. I. Theory

We present three methods for the distortion-free enhancement of THz signals measured by electro-optic sampling in zinc blende-type detector crystals, e.g., ZnTe or GaP. A technique commonly used in optically heterodyne-detected optical Kerr effect spectroscopy is introduced, which is based on two measurements at opposite optical biases near the zero transmission point in a crossed polarizer detection geometry. In contrast to other techniques for an undistorted THz signal enhancement, it also works in a balanced detection scheme and does not require an elaborate procedure for the reconstruction of the true signal as the two measured waveforms are simply subtracted to remove distortions. We study three different approaches for setting an optical bias using the Jones matrix formalism and discuss them also in the framework of optical heterodyne detection. We show that there is an optimal bias point in realistic situations where a small fraction of the probe light is scattered by optical components. The experimental demonstration will be given in the second part of this two-paper series [J. Opt. Soc. Am. B, doc. ID 204877 (2014, posted online)].