40 resultados para Digital Signal Processing
Resumo:
The constant development of digital systems in radio communications demands the adaptation of the current receiving equipment to the new technologies. In this context, a new Software Defined Radio based receiver is being implemented with the aim of carrying out different experiments to analyze the propagation of signals through the atmosphere from a satellite beacon. The receiver selected for this task is the PERSEUS SDR from the Italian company Microtelecom s.r.l. It is a software defined VLF-LF-MF-HF receiver based on an outstanding direct sampling digital architecture which features a 14 bit 80 MSamples/s analog-to-digital converter, a high-performance FPGA-based digital down-converter and a high-speed 480 Mbit/s USB2.0 PC interface. The main goal is to implement the related software and adapt the new receiver to the current working environment. In this paper, SDR technology guidelines are given and PERSEUS receiver digital signal processing is presented with the most remarkable results.
Resumo:
Modern Field Programmable Gate Arrays (FPGAs) are power packed with features to facilitate designers. Availability of features like huge block memory (BRAM), Digital Signal Processing (DSP) cores, embedded CPU makes the design strategy of FPGAs quite different from ASICs. FPGA are also widely used in security-critical application where protection against known attacks is of prime importance. We focus ourselves on physical attacks which target physical implementations. To design countermeasures against such attacks, the strategy for FPGA designers should also be different from that in ASIC. The available features should be exploited to design compact and strong countermeasures. In this paper, we propose methods to exploit the BRAMs in FPGAs for designing compact countermeasures. BRAM can be used to optimize intrinsic countermeasures like masking and dual-rail logic, which otherwise have significant overhead (at least 2X). The optimizations are applied on a real AES-128 co-processor and tested for area overhead and resistance on Xilinx Virtex-5 chips. The presented masking countermeasure has an overhead of only 16% when applied on AES. Moreover Dual-rail Precharge Logic (DPL) countermeasure has been optimized to pack the whole sequential part in the BRAM, hence enhancing the security. Proper robustness evaluations are conducted to analyze the optimization for area and security.
Resumo:
Neurological Diseases (ND) are affecting larger segments of aging population every year. Treatment is dependent on expensive accurate and frequent monitoring. It is well known that ND leave correlates in speech and phonation. The present work shows a method to detect alterations in vocal fold tension during phonation. These may appear either as hypertension or as cyclical tremor. Estimations of tremor may be produced by auto-regressive modeling of the vocal fold tension series in sustained phonation. The correlates obtained are a set of cyclicality coefficients, the frequency and the root mean square amplitude of the tremor. Statistical distributions of these correlates obtained from a set of male and female subjects are presented. Results from five study cases of female voice are also given.
Resumo:
The Glottal Source correlates reconstructed from the phonated parts of voice may render interesting information with applicability in different fields. One of them is defective closure (gap) detection. Through the paper the background to explain the physical foundations of defective gap are reviewed. A possible method to estimate defective gap is also presented based on a Wavelet Description of the Glottal Source. The method is validated using results from the analysis of a gender-balanced speakers database. Normative values for the different parameters estimated are given. A set of study cases with deficient glottal closure is presented and discussed.
Resumo:
Optical communications receivers using wavelet signals processing is proposed in this paper for dense wavelength-division multiplexed (DWDM) systems and modal-division multiplexed (MDM) transmissions. The optical signal-to-noise ratio (OSNR) required to demodulate polarization-division multiplexed quadrature phase shift keying (PDM-QPSK) modulation format is alleviated with the wavelet denoising process. This procedure improves the bit error rate (BER) performance and increasing the transmission distance in DWDM systems. Additionally, the wavelet-based design relies on signal decomposition using time-limited basis functions allowing to reduce the computational cost in Digital-Signal-Processing (DSP) module. Attending to MDM systems, a new scheme of encoding data bits based on wavelets is presented to minimize the mode coupling in few-mode (FWF) and multimode fibers (MMF). The Shifted Prolate Wave Spheroidal (SPWS) functions are proposed to reduce the modal interference.
Resumo:
La tecnología moderna de computación ha permitido cambiar radicalmente la investigación tecnológica en todos los ámbitos. El proceso general utilizado previamente consistía en el desarrollo de prototipos analógicos, creando múltiples versiones del mismo hasta llegar al resultado adecuado. Este es un proceso costoso a nivel económico y de carga de trabajo. Es por ello por lo que el proceso de investigación actual aprovecha las nuevas tecnologías para lograr el objetivo final mediante la simulación. Gracias al desarrollo de software para la simulación de distintas áreas se ha incrementado el ritmo de crecimiento de los avances tecnológicos y reducido el coste de los proyectos en investigación y desarrollo. La simulación, por tanto, permite desarrollar previamente prototipos simulados con un coste mucho menor para así lograr un producto final, el cual será llevado a cabo en su ámbito correspondiente. Este proceso no sólo se aplica en el caso de productos con circuitería, si bien es utilizado también en productos programados. Muchos de los programas actuales trabajan con algoritmos concretos cuyo funcionamiento debe ser comprobado previamente, para después centrarse en la codificación del mismo. Es en este punto donde se encuentra el objetivo de este proyecto, simular algoritmos de procesado digital de la señal antes de la codificación del programa final. Los sistemas de audio están basados en su totalidad en algoritmos de procesado de la señal, tanto analógicos como digitales, siendo estos últimos los que están sustituyendo al mundo analógico mediante los procesadores y los ordenadores. Estos algoritmos son la parte más compleja del sistema, y es la creación de nuevos algoritmos la base para lograr sistemas de audio novedosos y funcionales. Se debe destacar que los grupos de desarrollo de sistemas de audio presentan un amplio número de miembros con cometidos diferentes, separando las funciones de programadores e ingenieros de la señal de audio. Es por ello por lo que la simulación de estos algoritmos es fundamental a la hora de desarrollar nuevos y más potentes sistemas de audio. Matlab es una de las herramientas fundamentales para la simulación por ordenador, la cual presenta utilidades para desarrollar proyectos en distintos ámbitos. Sin embargo, en creciente uso actualmente se encuentra el software Simulink, herramienta especializada en la simulación de alto nivel que simplifica la dificultad de la programación en Matlab y permite desarrollar modelos de forma más rápida. Simulink presenta una completa funcionalidad para el desarrollo de algoritmos de procesado digital de audio. Por ello, el objetivo de este proyecto es el estudio de las capacidades de Simulink para generar sistemas de audio funcionales. A su vez, este proyecto pretende profundizar en los métodos de procesado digital de la señal de audio, logrando al final un paquete de sistemas de audio compatible con los programas de edición de audio actuales. ABSTRACT. Modern computer technology has dramatically changed the technological research in multiple areas. The overall process previously used consisted of the development of analog prototypes, creating multiple versions to reach the proper result. This is an expensive process in terms of an economically level and workload. For this reason actual investigation process take advantage of the new technologies to achieve the final objective through simulation. Thanks to the software development for simulation in different areas the growth rate of technological progress has been increased and the cost of research and development projects has been decreased. Hence, simulation allows previously the development of simulated protoypes with a much lower cost to obtain a final product, which will be held in its respective field. This process is not only applied in the case of circuitry products, but is also used in programmed products. Many current programs work with specific algorithms whose performance should be tested beforehand, which allows focusing on the codification of the program. This is the main point of this project, to simulate digital signal processing algorithms before the codification of the final program. Audio systems are entirely based on signal processing, both analog and digital systems, being the digital systems which are replacing the analog world thanks to the processors and computers. This algorithms are the most complex part of every system, and the creation of new algorithms is the most important step to achieve innovative and functional new audio systems. It should be noted that development groups of audio systems have a large number of members with different roles, separating them into programmers and audio signal engineers. For this reason, the simulation of this algorithms is essential when developing new and more powerful audio systems. Matlab is one of the most important tools for computer simulation, which has utilities to develop projects in different areas. However, the use of the Simulink software is constantly growing. It is a simulation tool specialized in high-level simulations which simplifies the difficulty of programming in Matlab and allows the developing of models faster. Simulink presents a full functionality for the development of algorithms for digital audio processing. Therefore, the objective of this project is to study the posibilities of Simulink to generate funcional audio systems. In turn, this projects aims to get deeper into the methods of digital audio signal processing, making at the end a software package of audio systems compatible with the current audio editing software.
Resumo:
La Ingeniería Biomédica surgió en la década de 1950 como una fascinante mezcla interdisciplinaria, en la cual la ingeniería, la biología y la medicina aunaban esfuerzos para analizar y comprender distintas enfermedades. Las señales existentes en este área deben ser analizadas e interpretadas, más allá de las capacidades limitadas de la simple vista y la experiencia humana. Aquí es donde el procesamiento digital de la señal se postula como una herramienta indispensable para extraer la información relevante oculta en dichas señales. La electrocardiografía fue una de las primeras áreas en las que se aplicó el procesado digital de señales hace más de 50 años. Las señales electrocardiográficas continúan siendo, a día de hoy, objeto de estudio por parte de cardiólogos e ingenieros. En esta área, las técnicas de procesamiento de señal han ayudado a encontrar información oculta a simple vista que ha cambiado la forma de tratar ciertas enfermedades que fueron ya diagnosticadas previamente. Desde entonces, se han desarrollado numerosas técnicas de procesado de señales electrocardiográficas, pudiéndose resumir estas en tres grandes categorías: análisis tiempo-frecuencia, análisis de organización espacio-temporal y separación de la actividad atrial del ruido y las interferencias. Este proyecto se enmarca dentro de la primera categoría, análisis tiempo-frecuencia, y en concreto dentro de lo que se conoce como análisis de frecuencia dominante, la cual se va a aplicar al análisis de señales de fibrilación auricular. El proyecto incluye una parte teórica de análisis y desarrollo de algoritmos de procesado de señal, y una parte práctica, de programación y simulación con Matlab. Matlab es una de las herramientas fundamentales para el procesamiento digital de señales por ordenador, la cual presenta importantes funciones y utilidades para el desarrollo de proyectos en este campo. Por ello, se ha elegido dicho software como herramienta para la implementación del proyecto. ABSTRACT. Biomedical Engineering emerged in the 1950s as a fascinating interdisciplinary blend, in which engineering, biology and medicine pooled efforts to analyze and understand different diseases. Existing signals in this area should be analyzed and interpreted, beyond the limited capabilities of the naked eye and the human experience. This is where the digital signal processing is postulated as an indispensable tool to extract the relevant information hidden in these signals. Electrocardiography was one of the first areas where digital signal processing was applied over 50 years ago. Electrocardiographic signals remain, even today, the subject of close study by cardiologists and engineers. In this area, signal processing techniques have helped to find hidden information that has changed the way of treating certain diseases that were already previously diagnosed. Since then, numerous techniques have been developed for processing electrocardiographic signals. These methods can be summarized into three categories: time-frequency analysis, analysis of spatio-temporal organization and separation of atrial activity from noise and interferences. This project belongs to the first category, time-frequency analysis, and specifically to what is known as dominant frequency analysis, which is one of the fundamental tools applied in the analysis of atrial fibrillation signals. The project includes a theoretical part, related to the analysis and development of signal processing algorithms, and a practical part, related to programming and simulation using Matlab. Matlab is one of the fundamental tools for digital signal processing, presenting significant functions and advantages for the development of projects in this field. Therefore, we have chosen this software as a tool for project implementation.
Resumo:
La teoría de reconocimiento y clasificación de patrones y el aprendizaje automático son actualmente áreas de conocimiento en constante desarrollo y con aplicaciones prácticas en múltiples ámbitos de la industria. El propósito de este Proyecto de Fin de Grado es el estudio de las mismas así como la implementación de un sistema software que dé solución a un problema de clasificación de ruido impulsivo, concretamente mediante el desarrollo de un sistema de seguridad basado en la clasificación de eventos sonoros en tiempo real. La solución será integral, comprendiendo todas las fases del proceso, desde la captación de sonido hasta el etiquetado de los eventos registrados, pasando por el procesado digital de señal y la extracción de características. Para su desarrollo se han diferenciado dos partes fundamentales; una primera que comprende la interfaz de usuario y el procesado de la señal de audio donde se desarrollan las labores de monitorización y detección de ruido impulsivo y otra segunda centrada únicamente en la clasificación de los eventos sonoros detectados, definiendo una arquitectura de doble clasificador donde se determina si los eventos detectados son falsas alarmas o amenazas, etiquetándolos como de un tipo concreto en este segundo caso. Los resultados han sido satisfactorios, mostrando una fiabilidad global en el proceso de entorno al 90% a pesar de algunas limitaciones a la hora de construir la base de datos de archivos de audio, lo que prueba que un dispositivo de seguridad basado en el análisis de ruido ambiente podría incluirse en un sistema integral de alarma doméstico aumentando la protección del hogar. ABSTRACT. Pattern classification and machine learning are currently expertise areas under continuous development and also with extensive applications in many business sectors. The aim of this Final Degree Project is to study them as well as the implementation of software to carry on impulsive noise classification tasks, particularly through the development of a security system based on sound events classification. The solution will go over all process stages, from capturing sound to the labelling of the events recorded, without forgetting digital signal processing and feature extraction, everything in real time. In the development of the Project a distinction has been made between two main parts. The first one comprises the user’s interface and the audio signal processing module, where monitoring and impulsive noise detection tasks take place. The second one is focussed in sound events classification tasks, defining a double classifier architecture where it is determined whether detected events are false alarms or threats, labelling them from a concrete category in the latter case. The obtained results have been satisfactory, with an overall reliability of 90% despite some limitations when building the audio files database. This proves that a safety device based on the analysis of environmental noise could be included in a full alarm system increasing home protection standards.
Resumo:
MPEG-M is a suite of ISO/IEC standards (ISO/IEC 23006) that has been developed under the auspices of Moving Picture Experts Group (MPEG). MPEG-M, also known as Multimedia Service Platform Technologies (MSPT), facilitates a collection of multimedia middleware APIs and elementary services as well as service aggregation so that service providers can offer users a plethora of innovative services by extending current IPTV technology toward the seamless integration of personal content creation and distribution, e-commerce, social networks and Internet distribution of digital media.
Resumo:
This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection
Resumo:
This paper presents an automatic modulation classifier for electronic warfare applications. It is a pattern recognition modulation classifier based on statistical features of the phase and instantaneous frequency. This classifier runs in a real time operation mode with sampling rates in excess of 1 Gsample/s. The hardware platform for this application is a Field Programmable Gate Array (FPGA). This AMC is subsidiary of a digital channelised receiver also implemented in the same platform.
Resumo:
Matlab, uno de los paquetes de software matemático más utilizados actualmente en el mundo de la docencia y de la investigación, dispone de entre sus muchas herramientas una específica para el procesado digital de imágenes. Esta toolbox de procesado digital de imágenes está formada por un conjunto de funciones adicionales que amplían la capacidad del entorno numérico de Matlab y permiten realizar un gran número de operaciones de procesado digital de imágenes directamente a través del programa principal. Sin embargo, pese a que MATLAB cuenta con un buen apartado de ayuda tanto online como dentro del propio programa principal, la bibliografía disponible en castellano es muy limitada y en el caso particular de la toolbox de procesado digital de imágenes es prácticamente nula y altamente especializada, lo que requiere que los usuarios tengan una sólida formación en matemáticas y en procesado digital de imágenes. Partiendo de una labor de análisis de todas las funciones y posibilidades disponibles en la herramienta del programa, el proyecto clasificará, resumirá y explicará cada una de ellas a nivel de usuario, definiendo todas las variables de entrada y salida posibles, describiendo las tareas más habituales en las que se emplea cada función, comparando resultados y proporcionando ejemplos aclaratorios que ayuden a entender su uso y aplicación. Además, se introducirá al lector en el uso general de Matlab explicando las operaciones esenciales del programa, y se aclararán los conceptos más avanzados de la toolbox para que no sea necesaria una extensa formación previa. De este modo, cualquier alumno o profesor que se quiera iniciar en el procesado digital de imágenes con Matlab dispondrá de un documento que le servirá tanto para consultar y entender el funcionamiento de cualquier función de la toolbox como para implementar las operaciones más recurrentes dentro del procesado digital de imágenes. Matlab, one of the most used numerical computing environments in the world of research and teaching, has among its many tools a specific one for digital image processing. This digital image processing toolbox consists of a set of additional functions that extend the power of the digital environment of Matlab and allow to execute a large number of operations of digital image processing directly through the main program. However, despite the fact that MATLAB has a good help section both online and within the main program, the available bibliography is very limited in Castilian and is negligible and highly specialized in the particular case of the image processing toolbox, being necessary a strong background in mathematics and digital image processing. Starting from an analysis of all the available functions and possibilities in the program tool, the document will classify, summarize and explain each function at user level, defining all input and output variables possible, describing common tasks in which each feature is used, comparing results and providing illustrative examples to help understand its use and application. In addition, the reader will be introduced in the general use of Matlab explaining the essential operations within the program and clarifying the most advanced concepts of the toolbox so that an extensive prior formation will not be necessary. Thus, any student or teacher who wants to start digital image processing with Matlab will have a document that will serve to check and understand the operation of any function of the toolbox and also to implement the most recurrent operations in digital image processing.
Resumo:
A system for estimation of unknown rectangular room dimensions based on two radio transceivers, both capable of full duplex operations, is presented. The approach is based on CIR measurements taken at the same place where the signal is transmitted (generated), commonly known as self- to-self CIR. Another novelty is the receiver antenna design which consists of eight sectorized antennas with 45° aperture in the horizontal plane, whose total coverage corresponds to the isotropic one. The dimensions of a rectangular room are reconstructed directly from radio impulse responses by extracting the information regarding features like round trip time, received signal strength and reverberation time. Using radar approach the estimation of walls and corners positions are derived. Additionally, the analysis of the absorption coefficient of the test environment is conducted and a typical coefficient for office room with furniture is proposed. Its accuracy is confirmed through the results of volume estimation. Tests using measured data were performed, and the simulation results confirm the feasibility of the approach.
Resumo:
We consider the problem of developing efficient sampling schemes for multiband sparse signals. Previous results on multicoset sampling implementations that lead to universal sampling patterns (which guarantee perfect reconstruction), are based on a set of appropriate interleaved analog to digital converters, all of them operating at the same sampling frequency. In this paper we propose an alternative multirate synchronous implementation of multicoset codes, that is, all the analog to digital converters in the sampling scheme operate at different sampling frequencies, without need of introducing any delay. The interleaving is achieved through the usage of different rates, whose sum is significantly lower than the Nyquist rate of the multiband signal. To obtain universal patterns the sampling matrix is formulated and analyzed. Appropriate choices of the parameters, that is the block length and the sampling rates, are also proposed.
Resumo:
Many problems in digital communications involve wideband radio signals. As the most recent example, the impressive advances in Cognitive Radio systems make even more necessary the development of sampling schemes for wideband radio signals with spectral holes. This is equivalent to considering a sparse multiband signal in the framework of Compressive Sampling theory. Starting from previous results on multicoset sampling and recent advances in compressive sampling, we analyze the matrix involved in the corresponding reconstruction equation and define a new method for the design of universal multicoset codes, that is, codes guaranteeing perfect reconstruction of the sparse multiband signal.