Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

Efficient asynchronous scheduling algorithms for cost-effective buffered crossbar switches

Buffered crossbar switches have recently attracted considerable attention as the next generation of high speed interconnects. They are a special type of crossbar switches with an exclusive buffer at each crosspoint of the crossbar. They demonstrate unique advantages over traditional unbuffered crossbar switches, such as high throughput, low latency, and asynchronous packet scheduling. However, since crosspoint buffers are expensive on-chip memories, it is desired that each crosspoint has only a small buffer. This dissertation proposes a series of practical algorithms and techniques for efficient packet scheduling for buffered crossbar switches. To reduce the hardware cost of such switches and make them scalable, we considered partially buffered crossbars, whose crosspoint buffers can be of an arbitrarily small size. Firstly, we introduced a hybrid scheme called Packet-mode Asynchronous Scheduling Algorithm (PASA) to schedule best effort traffic. PASA combines the features of both distributed and centralized scheduling algorithms and can directly handle variable length packets without Segmentation And Reassembly (SAR). We showed by theoretical analysis that it achieves 100% throughput for any admissible traffic in a crossbar with a speedup of two. Moreover, outputs in PASA have a large probability to avoid the more time-consuming centralized scheduling process, and thus make fast scheduling decisions. Secondly, we proposed the Fair Asynchronous Segment Scheduling (FASS) algorithm to handle guaranteed performance traffic with explicit flow rates. FASS reduces the crosspoint buffer size by dividing packets into shorter segments before transmission. It also provides tight constant performance guarantees by emulating the ideal Generalized Processor Sharing (GPS) model. Furthermore, FASS requires no speedup for the crossbar, lowering the hardware cost and improving the switch capacity. Thirdly, we presented a bandwidth allocation scheme called Queue Length Proportional (QLP) to apply FASS to best effort traffic. QLP dynamically obtains a feasible bandwidth allocation matrix based on the queue length information, and thus assists the crossbar switch to be more work-conserving. The feasibility and stability of QLP were proved, no matter whether the traffic distribution is uniform or non-uniform. Hence, based on bandwidth allocation of QLP, FASS can also achieve 100% throughput for best effort traffic in a crossbar without speedup.

A family of perfect hashing methods

Minimal perfect hash functions are used for memory efficient storage and fast retrieval of items from static sets. We present an infinite family of efficient and practical algorithms for generating order preserving minimal perfect hash functions. We show that almost all members of the family construct space and time optimal order preserving minimal perfect hash functions, and we identify the one with minimum constants. Members of the family generate a hash function in two steps. First a special kind of function into an r-graph is computed probabilistically. Then this function is refined deterministically to a minimal perfect hash function. We give strong theoretical evidence that the first step uses linear random time. The second step runs in linear deterministic time. The family not only has theoretical importance, but also offers the fastest known method for generating perfect hash functions.

On Approximate KKT Condition and its Extension to Continuous Variational Inequalities

In this work, we introduce a necessary sequential Approximate-Karush-Kuhn-Tucker (AKKT) condition for a point to be a solution of a continuous variational inequality, and we prove its relation with the Approximate Gradient Projection condition (AGP) of Garciga-Otero and Svaiter. We also prove that a slight variation of the AKKT condition is sufficient for a convex problem, either for variational inequalities or optimization. Sequential necessary conditions are more suitable to iterative methods than usual punctual conditions relying on constraint qualifications. The AKKT property holds at a solution independently of the fulfillment of a constraint qualification, but when a weak one holds, we can guarantee the validity of the KKT conditions.

The dark side of the board: advances in chess Kriegspiel

While imperfect information games are an excellent model of real-world problems and tasks, they are often difficult for computer programs to play at a high level of proficiency, especially if they involve major uncertainty and a very large state space. Kriegspiel, a variant of chess making it similar to a wargame, is a perfect example: while the game was studied for decades from a game-theoretical viewpoint, it was only very recently that the first practical algorithms for playing it began to appear. This thesis presents, documents and tests a multi-sided effort towards making a strong Kriegspiel player, using heuristic searching, retrograde analysis and Monte Carlo tree search algorithms to achieve increasingly higher levels of play. The resulting program is currently the strongest computer player in the world and plays at an above-average human level.

Context-aware wireless networks

This thesis investigates context-aware wireless networks, capable to adapt their behavior to the context and the application, thanks to the ability of combining communication, sensing and localization. Problems of signals demodulation, parameters estimation and localization are addressed exploiting analytical methods, simulations and experimentation, for the derivation of the fundamental limits, the performance characterization of the proposed schemes and the experimental validation. Ultrawide-bandwidth (UWB) signals are in certain cases considered and non-coherent receivers, allowing the exploitation of the multipath channel diversity without adopting complex architectures, investigated. Closed-form expressions for the achievable bit error probability of novel proposed architectures are derived. The problem of time delay estimation (TDE), enabling network localization thanks to ranging measurement, is addressed from a theoretical point of view. New fundamental bounds on TDE are derived in the case the received signal is partially known or unknown at receiver side, as often occurs due to propagation or due to the adoption of low-complexity estimators. Practical estimators, such as energy-based estimators, are revised and their performance compared with the new bounds. The localization issue is addressed with experimentation for the characterization of cooperative networks. Practical algorithms able to improve the accuracy in non-line-of-sight (NLOS) channel conditions are evaluated on measured data. With the purpose of enhancing the localization coverage in NLOS conditions, non-regenerative relaying techniques for localization are introduced and ad hoc position estimators are devised. An example of context-aware network is given with the study of the UWB-RFID system for detecting and locating semi-passive tags. In particular a deep investigation involving low-complexity receivers capable to deal with problems of multi-tag interference, synchronization mismatches and clock drift is presented. Finally, theoretical bounds on the localization accuracy of this and others passive localization networks (e.g., radar) are derived, also accounting for different configurations such as in monostatic and multistatic networks.

Procesado de imágenes médicas en MATLAB

La relación entre la ingeniería y la medicina cada vez se está haciendo más estrecha, y debido a esto se ha creado una nueva disciplina, la bioingeniería, ámbito en el que se centra el proyecto. Este ámbito cobra gran interés debido al rápido desarrollo de nuevas tecnologías que en particular permiten, facilitan y mejoran la obtención de diagnósticos médicos respecto de los métodos tradicionales. Dentro de la bioingeniería, el campo que está teniendo mayor desarrollo es el de la imagen médica, gracias al cual se pueden obtener imágenes del interior del cuerpo humano con métodos no invasivos y sin necesidad de recurrir a la cirugía. Mediante métodos como la resonancia magnética, rayos X, medicina nuclear o ultrasonidos, se pueden obtener imágenes del cuerpo humano para realizar diagnósticos. Para que esas imágenes puedan ser utilizadas con ese fin hay que realizar un correcto tratamiento de éstas mediante técnicas de procesado digital. En ése ámbito del procesado digital de las imágenes médicas es en el que se ha realizado este proyecto. Gracias al desarrollo del tratamiento digital de imágenes con métodos de extracción de información, mejora de la visualización o resaltado de rasgos de interés de las imágenes, se puede facilitar y mejorar el diagnóstico de los especialistas. Por todo esto en una época en la que se quieren automatizar todos los procesos para mejorar la eficacia del trabajo realizado, el automatizar el procesado de las imágenes para extraer información con mayor facilidad, es muy útil. Actualmente una de las herramientas más potentes en el tratamiento de imágenes médicas es Matlab, gracias a su toolbox de procesado de imágenes. Por ello se eligió este software para el desarrollo de la parte práctica de este proyecto, su potencia y versatilidad simplifican la implementación de algoritmos. Este proyecto se estructura en dos partes. En la primera se realiza una descripción general de las diferentes modalidades de obtención de imágenes médicas y se explican los diferentes usos de cada método, dependiendo del campo de aplicación. Posteriormente se hace una descripción de las técnicas más importantes de procesado de imagen digital que han sido utilizadas en el proyecto. En la segunda parte se desarrollan cuatro aplicaciones en Matlab para ejemplificar el desarrollo de algoritmos de procesado de imágenes médicas. Dichas implementaciones demuestran la aplicación y utilidad de los conceptos explicados anteriormente en la parte teórica, como la segmentación y operaciones de filtrado espacial de la imagen, así como otros conceptos específicos. Las aplicaciones ejemplo desarrolladas han sido: obtención del porcentaje de metástasis de un tejido, diagnóstico de las deformidades de la columna vertebral, obtención de la MTF de una cámara de rayos gamma y medida del área de un fibroadenoma de una ecografía de mama. Por último, para cada una de las aplicaciones se detallará su utilidad en el campo de la imagen médica, los resultados obtenidos y su implementación en una interfaz gráfica para facilitar su uso. ABSTRACT. The relationship between medicine and engineering is becoming closer than ever giving birth to a recently appeared science field: bioengineering. This project is focused on this subject. This recent field is becoming more and more important due to the fast development of new technologies that provide tools to improve disease diagnosis, with regard to traditional procedures. In bioengineering the fastest growing field is medical imaging, in which we can obtain images of the inside of the human body without need of surgery. Nowadays by means of the medical modalities of magnetic resonance, X ray, nuclear medicine or ultrasound, we can obtain images to make a more accurate diagnosis. For those images to be useful within the medical field, they should be processed properly with some digital image processing techniques. It is in this field of digital medical image processing where this project is developed. Thanks to the development of digital image processing providing methods for data collection, improved visualization or data highlighting, diagnosis can be eased and facilitated. In an age where automation of processes is much sought, automated digital image processing to ease data collection is extremely useful. One of the most powerful image processing tools is Matlab, together with its image processing toolbox. That is the reason why that software was chosen to develop the practical algorithms in this project. This final project is divided into two main parts. Firstly, the different modalities for obtaining medical images will be described. The different usages of each method according to the application will also be specified. Afterwards we will give a brief description of the most important image processing tools that have been used in the project. Secondly, four algorithms in Matlab are implemented, to provide practical examples of medical image processing algorithms. This implementation shows the usefulness of the concepts previously explained in the first part, such as: segmentation or spatial filtering. The particular applications examples that have been developed are: calculation of the metastasis percentage of a tissue, diagnosis of spinal deformity, approximation to the MTF of a gamma camera, and measurement of the area of a fibroadenoma in an ultrasound image. Finally, for each of the applications developed, we will detail its usefulness within the medical field, the results obtained, and its implementation in a graphical user interface to ensure ease of use.

Computer aided manufacturing of geometric models

As systems for computer-aided-design and production of mechanical parts have developed, there has arisen a need for techniques for the comprehensive description of the desired part, including its 3-D shape. The creation and manipulation of shapes is generally known as geometric modelling. It is desirable that links be established between geometric modellers and machining programs. Currently, unbounded APT and some bounded geometry systems are being widely used in manufacturing industry for machining operations such as: milling, drilling, boring and turning, applied mainly to engineering parts. APT systems, however, are presently only linked to wire-frame drafting systems. The combination of a geometric modeller and APT will provide a powerful manufacturing system for industry from the initial design right through part manufacture using NC machines. This thesis describes a recently developed interface (ROMAPT) between a bounded geometry modeller (ROMULUS) and an unbounded NC processor (APT). A new set of theoretical functions and practical algorithms for the computer aided manufacturing of 3D solid geometric model has been investigated. This work has led to the development of a sophisticated computer program, ROMAPT, which provides a new link between CAD (in form of a goemetric modeller ROMULUS) and CAM (in form of the APT NC system). ROMAPT has been used to machine some engineering prototypes successfully both in soft foam material and aluminium. It has been demonstrated above that the theory and algorithms developed by the author for the development of computer aided manufacturing of 3D solid modelling are both valid and applicable. ROMAPT allows the full potential of a solid geometric modeller (ROMULUS) to be further exploited for NC applications without requiring major investment in new NC processor. ROMAPT supports output in APT-AC, APT4 and the CAM-I SSRI NC languages.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Practical Aspects of Genetic Algorithms’ Implementation in Life Cycle Management of Electrotechnical Equipment

Some practical aspects of Genetic algorithms’ implementation regarding to life cycle management of electrotechnical equipment are considered.

Performance comparison of the optimal and the zero-forcing beamforming algorithms under practical conditions

The optimal and the zero-forcing beamformers are two commonly used algorithms in the subspace-based blind beamforming technology. The optimal beamformer is regarded as the algorithm with the best output SINR. The zero-forcing algorithm emphasizes the co-channel interference cancellation. This paper compares the performance of these two algorithms under some practical conditions: the effect of the finite data length and the existence of the angle estimation error. The investigation reveals that the zero-forcing algorithm can be more robust in the practical environment than the optimal algorithm.

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process