Noise induced processes in neural systems

Real neurons, and their networks, are far too complex to be described exactly by simple deterministic equations. Any description of their dynamics must therefore incorporate noise to some degree. It is my thesis that the nervous system is organized in such a way that its performance is optimal, subject to this constraint. I further contend that neuronal dynamics may even be enhanced by noise, when compared with their deterministic counter-parts. To support my thesis I will present and analyze three case studies. I will show how noise might (i) extend the dynamic range of mammalian cold-receptors and other cells that exhibit a temperature-dependent discharge; (ii) feature in the perception of ambiguous figures such as the Necker cube; (iii) alter the discharge pattern of single cells

Image Restoration

This book represents a sample of recent contributions of researchers all around the world in the field of image restoration. The book consists of 15 chapters organized in three main sections (Theory, Applications, Interdisciplinarity). Topics cover some different aspects of the theory of image restoration, but this book is also an occasion to highlight some new topics of research related to the emergence of some original imaging devices. From this arise some real challenging problems related to image reconstruction/restoration that open the way to some new fundamental scientific questions closely related with the world we interact with

Advances in the Role of Quantitative NMR in Medicine: Deep Learning applied to MR Fingerprinting and Trabecular Bone Volume Fraction Estimation through Single-Sided NMR

Nuclear Magnetic Resonance (NMR) has been a powerful and widespread tool since its birth thanks to its flexibility in assessing properties of physical systems without being invasive and without using ionizing radiations. Although applications of NMR for medical purposes have rapidly developed since the introduction of MR imaging (MRI), most of the clinical protocols retrieve qualitative information about biological tissues. Being able to retrieve also quantitative information with NMR may be beneficial to identify biomarkers for understanding and describing the pathophysiology of complex diseases in many tissues. However, established quantitative MRI (qMRI) methods require long scan times that not only can represent more exposure to image artifacts and more discomfort for the patient, but they also increase the costs of MRI protocols. To improve the clinical feasibility of quantitative NMR, one can focus on optimizing qMRI protocols to increase data acquisition efficiency, i.e. minimizing the acquisition times and maximising the number of retrieved information. Alternatively, one can focus on the application of low-cost, portable and low maintenance NMR devices in the medical field, such as single-sided devices. This Ph.D thesis presents studies that aim to advance the role of quantitative NMR in medicine using the two directions stated above. The first part of the thesis proposes a deep learning approach based on deep Fully Connected Networks (NN), for pixel-wise MR parameter prediction task in Magnetic Resonance Fingerprinting (MRF) as a solution to overcome the curse of dimensionality affecting the gold standard dictionary approach. The second part proposes a methodology to assess the trabecular bone-volume-to-total-volume (BV/TV) ratio using single-side NMR by means of NMR relaxometry measurements. Nowadays there are not well-established methodologies to assess trabecular BV/TV that are suitable for wide screening campaigns of the population at risk of bone fractures related to diseases such as osteoporosis

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Optical Microwave Signal Generation for Data Transmission in Optical Networks

The massive growth of telecommunication services and the increasing global data traffic boost the development, implementation, and integration of different networks for data transmission. An example of this development is the optical fiber networks, responsible today for the inter-continental connection through long-distance links and high transfer rates. The optical networks, as well as the networks supported by other transmission media, use electrical signals at specific frequencies for the synchronization of the network elements. The quality of these signals is usually determined in terms of phase noise. Due to the major impact of the phase noise over the system performance, its value should be minimized. The research work presented in this document describes the design and implementation of an optoelectronic system for the microwave signal generation using a vertical-cavity surface-emitting laser (VCSEL) and its integration into an optical data transmission system. Considering that the proposed system incorporates a directly modulated VCSEL, a theoretical and experimental characterization was developed based on the laser rate equations, dynamic and static measurements, and an equivalent electrical model of the active region. This procedure made possible the extraction of some VCSEL intrinsic parameters, as well as the validation and simulation of the VCSEL performance under specific modulation conditions. The VCSEL emits in C-band, this wavelength was selected because it is used in long-haul links. The proposed system is a self-initiated oscillation system caused by internal noise sources, which includes a VCSEL modulated in large signal to generate optical pulses (gain switching). The optical pulses, and the optical frequency comb associated, generate in electrical domain simultaneously a fundamental frequency (determined by a band-pass filter) and several harmonics. The phase noise measured at 10 kHz from the carrier at 1.25 GHz was -127.8 dBc/Hz, and it is the lowest value reported in the literature for this frequency and architecture. Both the jitter and optical pulse width were determined when different resonant cavities and polarization currents were employed. The lowest pulse duration was 85 ps and was achieved when the fundamental frequency was 2.5 GHz. As for the optical frequency comb, it was demonstrated that its flatness depends on the electrical modulation conditions. The flattest profiles are obtained when the fundamental frequency is higher than the VCSEL relaxation frequency. Both the electrical and the optical output of the system were integrated into an optical transmitter. The electrical signal provides the synchronization of the data generating equipment, whereas the optical pulses are employed as an optical carrier. Data transmissions at 155.52 Mb/s, 622.08 Mb/s and 1.25 Gb/s were experimentally validated. It was demonstrated that the fundamental frequency and harmonics could be extracted from the optical data signal transmitted by a band-pass filter. It was also experimentally proved that the pulsed return-to-zero (RZ) transmitter at 1.25 Gb/s, achieves bit error rates (BER) lower than $10^{-9}$ when the optical power at the receiver is higher than -33 dBm.La masificación de los servicios de telecomunicaciones y el creciente tráfico global de datos han impulsado el desarrollo, despliegue e integración de diferentes redes para la transmisión de datos. Un ejemplo de este despliegue son las redes de fibra óptica, responsables en la actualidad de la interconexión de los continentes a través de enlaces de grandes longitudes y altas tasas de transferencia. Las redes ópticas, al igual que las redes soportadas por otros medios de transmisión, utilizan señales eléctricas a frecuencias específicas para la sincronización de los elementos de red. La calidad de estas señales es determinante en el desempeño general del sistema, razón por la que su ruido de fase debe ser lo más pequeño posible. El trabajo de investigación presentado en este documento describe el diseño e implementación de un sistema optoelectrónico para la generación de señales microondas utilizando diodos láser de cavidad vertical (VCSEL) y su integración en un sistema de transmisión de datos óptico. Teniendo en cuenta que el sistema propuesto incorpora un láser VCSEL modulado directamente, se desarrolló una caracterización teórico-experimental basada en las ecuaciones de evolución del láser, mediciones dinámicas y estáticas, y un modelo eléctrico equivalente de la región activa. Este procedimiento posibilitó la extracción de algunos parámetros intrínsecos del VCSEL, al igual que la validación y simulación de su desempeño bajo diferentes condiciones de modulación. El VCSEL utilizado emite en banda C y fue seleccionado considerando que esta banda es comúnmente utilizada en enlaces de largo alcance. El sistema propuesto consiste en un lazo cerrado que inicia la oscilación gracias a las fuentes de ruido de los componentes y modula el VCSEL en gran señal para generar pulsos ópticos (conmutación de ganancia). Estos pulsos ópticos, que en el dominio de la frecuencia corresponden a un peine de frecuencia óptico, son detectados para generar simultáneamente una frecuencia fundamental (determinada por un filtro pasa banda) y varios armónicos. El ruido de fase medido a 10 kHz de la portadora a 1.25 GHz fue -127.8 dBc/Hz, y es el valor más bajo reportado en la literatura para esta frecuencia y arquitectura. Tanto la fluctuación de fase (jitter) y el ancho de los pulsos ópticos fueron determinados cuando diferentes cavidades resonantes y corrientes de polarización fueron empleadas. La duración de pulso más baja fue 85 ps y se obtuvo cuando la frecuencia fundamental del sistema era 2.5 GHz. En cuanto al peine de frecuencia óptico, se demostró que su planitud (flatness) depende de las condiciones eléctricas de modulación y que los perfiles más planos se obtienen cuando la frecuencia fundamental es superior a la frecuencia de relajación del VCSEL. Tanto la salida eléctrica como la salida óptica del sistema fueron integradas en un transmisor óptico. La señal eléctrica permite la sincronización de los equipos encargados de generar los datos, mientras que los pulsos ópticos son utilizados como portadora óptica. La transmisión de datos a 155.52 Mb/s, 622.08 Mb/s y 1.25 Gb/s fue validada experimentalmente. Se demostró que la frecuencia fundamental y los armónicos pueden ser extraídos de la señal óptica de datos transmitida mediante un filtro pasa banda. También se comprobó experimentalmente que el transmisor de datos pulsados con retorno a cero (RZ) a 1.25 Gb/s, logra tasas de error de bit (BER) menores a 10-9 cuando la potencia óptica en el receptor es mayor a -33 dBm.Gobernación de NariñoBPIN 2013000100092Doctorad

Phase Transitions Induced by Diversity and Examples in Biological Systems

Tesis leída en l'Universitat de les Illes Balears en diciembre de 2010The present thesis covers various topics that range over di erent aspects of scientific research. On one end there is the specific analysis of a precise form that models some experimental observations. A good theoretical understanding of the mathematics that describe the observations can be a guide to the experimentalist and help estimate the validity of the measurements. On the other end there are abstract models whose relation to physical systems seem far but they are prototypic for a broad range of di erent systems and the drawn conclusions tend to be quite general. Depending on the abstraction and on the simplifications in use the distinction between both ends might not be sharp. The ordering of the research results presented in part II of this thesis somehow reflects the seamless transition from one end to the other. To introduce the reader into the context of the genuine results we provide introductory material in the chapters of the present part I.Peer reviewe

Tumour grading and discrimination based on class assignment and quantitative texture analysis techniques

Medical imaging represents the utilisation of technology in biology for the purpose of noninvasively revealing the internal structure of the organs of the human body. It is a way to improve the quality of the patient's life through a more precise and rapid diagnosis, and with limited side-effects, leading to an effective overall treatment procedure. The main objective of this thesis is to propose novel tumour discrimination techniques that cover both micro and macro-scale textures encountered in computed tomography (CI') and digital microscopy (DM) modalities, respectively. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and classification. The fractal dimension (FO) as a texture measure was applied to contrast enhanced CT lung tumour images in an aim to improve tumour grading accuracy from conventional CI' modality, and quantitative performance analysis showed an accuracy of 83.30% in distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant tumours. A different approach was adopted for subtype discrimination of brain tumour OM images via a set of statistical and model-based texture analysis algorithms. The combined Gaussian Markov random field and run-length matrix texture measures outperformed all other combinations, achieving an overall class assignment classification accuracy of 92.50%. Also two new histopathological multi resolution approaches based on applying the FO as the best bases selection for discrete wavelet packet transform, and when fused with the Gabor filters' energy output improved the accuracy to 91.25% and 95.00%, respectively. While noise is quite common in all medical imaging modalities, the impact of noise on the applied texture measures was assessed as well. The developed lung and brain texture analysis techniques can improve the physician's ability to detect and analyse pathologies leading for a more reliable diagnosis and treatment of disease

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Audio source separation for music in low-latency and high-latency scenarios

Aquesta tesi proposa mètodes per tractar les limitacions de les tècniques existents de separació de fonts musicals en condicions de baixa i alta latència. En primer lloc, ens centrem en els mètodes amb un baix cost computacional i baixa latència. Proposem l'ús de la regularització de Tikhonov com a mètode de descomposició de l'espectre en el context de baixa latència. El comparem amb les tècniques existents en tasques d'estimació i seguiment dels tons, que són passos crucials en molts mètodes de separació. A continuació utilitzem i avaluem el mètode de descomposició de l'espectre en tasques de separació de veu cantada, baix i percussió. En segon lloc, proposem diversos mètodes d'alta latència que milloren la separació de la veu cantada, gràcies al modelatge de components específics, com la respiració i les consonants. Finalment, explorem l'ús de correlacions temporals i anotacions manuals per millorar la separació dels instruments de percussió i dels senyals musicals polifònics complexes.Esta tesis propone métodos para tratar las limitaciones de las técnicas existentes de separación de fuentes musicales en condiciones de baja y alta latencia. En primer lugar, nos centramos en los métodos con un bajo coste computacional y baja latencia. Proponemos el uso de la regularización de Tikhonov como método de descomposición del espectro en el contexto de baja latencia. Lo comparamos con las técnicas existentes en tareas de estimación y seguimiento de los tonos, que son pasos cruciales en muchos métodos de separación. A continuación utilizamos y evaluamos el método de descomposición del espectro en tareas de separación de voz cantada, bajo y percusión. En segundo lugar, proponemos varios métodos de alta latencia que mejoran la separación de la voz cantada, gracias al modelado de componentes que a menudo no se toman en cuenta, como la respiración y las consonantes. Finalmente, exploramos el uso de correlaciones temporales y anotaciones manuales para mejorar la separación de los instrumentos de percusión y señales musicales polifónicas complejas.This thesis proposes specific methods to address the limitations of current music source separation methods in low-latency and high-latency scenarios. First, we focus on methods with low computational cost and low latency. We propose the use of Tikhonov regularization as a method for spectrum decomposition in the low-latency context. We compare it to existing techniques in pitch estimation and tracking tasks, crucial steps in many separation methods. We then use the proposed spectrum decomposition method in low-latency separation tasks targeting singing voice, bass and drums. Second, we propose several high-latency methods that improve the separation of singing voice by modeling components that are often not accounted for, such as breathiness and consonants. Finally, we explore using temporal correlations and human annotations to enhance the separation of drums and complex polyphonic music signals