Medida e análise de atividade espetral

Mestrado em Engenharia Electrónica e TelecomunicaçõesThe dissertation deals with measuring and analyzing spectrum occupancy of a GSM900 band, DCS1800 band and all UMTS bandwidth. A modelization for analog power and binary quantized power is given. In the case of analog power, histograms of the power distribution during one working day are presented. In the case of quantized power the two time statistics, the time period of opportunities distribution and the time between opportunities distribution are presented, described and modeled. The measurement setup is standing in line of sight with the base station. Also, in terms of maximum sensitivity the measurement setup is described and analyzed. Spectrum non occupancy in terms of total time for the GSM900 band and the DCS1800 band is given, for a working day.Nesta dissertação são feitas medidas e a análise de ocupação de espectro em uma banda de GSM900, uma banda de DCS1800 e toda a largura de banda do UMTS. É apresentada uma modelização para potência analógica e para a potência binária quantizada. No caso da potência analógica são apresentados histogramas da distribuição de potência ao longo de um dia útil. No caso da potência quantizada as duas estatísticas, distribuição do período de tempo de oportunidades e distribuição do tempo entre oportunidades, são apresentadas, descritas e modeladas. O setup de medida encontra-se em linha de vista com a estação base. O setup é descrito e analisado em termos de máxima sensibilidade. A desocupação de espectro em termos de tempo total para a banda de GSM900 e para a banda DCS1800 é fornecida, para um dia de útil

Development of machine learning based speaker recognition system

In this thesis, we describe a biometric authentication system that is capable of recognizing its users??? voice using advanced machine learning and digital signal processing tools. The proposed system can both validate a person???s identity (i.e. verification) and recognize it from a larger known group of people (i.e. identification). We designed the entire speaker recognition system to be integrated into the Siebel Center???s infrastructure, and named it ???Biometric Authentication System for the Siebel Center (BASS)???. The main idea is to extract discriminative characteristics of an individual???s voiceprint, and employ them to train classifiers using binary classification. We formed the training data set by recording 11 speakers??? voices in a laboratory environment. The majority of the speakers were from different nations, with different language backgrounds and therefore various accents. They were considered to be a subset of the Siebel Center community. We asked them to speak 13 words including numeric digits (0-9) and proper nouns, and used triplet combinations of these words as passwords. We chose Mel-Frequency Cepstral Coefficients to represent the voice signals for forming frame-based feature vectors. With these we trained Support Vector Machine and Artificial Neural Network classifiers using ???One vs. all??? strategy. We tested our recognition models with unseen voice records from different speakers and found them very successful based on different criteria such as equal error rate, precision and recall values. In the scope of this work, we also assembled the hardware through which the software, including the algorithm and developed models, could operate. The hardware consists of several parts such as an infrared sensor that is used to sense the presence of users, a PIC microcontroller to communicate with the software and an LCD screen to display the passwords, etc. Based on the decision obtained from the software, BASS is also capable of opening the office door, where it is built to function

The Discrete Linear Chirp Transform and its Applications

In many applications in signal processing, the discrete Fourier transform (DFT) plays a significant role in analyzing characteristics of stationary signals in the frequency domain. The DFT can be implemented in a very efficient way using the fast Fourier transform (FFT) algorithm. However, many actual signals by their nature are non--stationary signals which make the choice of the DFT to deal with such signals not appropriate. Alternative tools for analyzing non--stationary signals come with the development of time--frequency distributions (TFD). The Wigner--Ville distribution is a time--frequency distribution that represents linear chirps in an ideal way, but it has the problem of cross--terms which makes the analysis of such tools unacceptable for multi--component signals. In this dissertation, we develop three definitions of linear chirp transforms which are: the continuous linear chirp transform (CLCT), the discrete linear chirp transform (DLCT), and the discrete cosine chirp transform (DCCT). Most of this work focuses on the discrete linear chirp transform (DLCT) which can be considered a generalization of the DFT to analyze non--stationary signals. The DLCT is a joint frequency chirp--rate transformation, capable of locally representing signals in terms of linear chirps. Important properties of this transform are discussed and explored. The efficient implementation of the DLCT is given by taking advantage of the FFT algorithm. Since this novel transform can be implemented in a fast and efficient way, this would make the proposed transform a candidate to be used for many applications, including chirp rate estimation, signal compression, filtering, signal separation, elimination of the cross--terms in the Wigner--Ville distribution, and in communication systems. In this dissertation, we will explore some of these applications

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field