Orientador: João Francisco Galera Monico / Resumo: O GPS tem mostrado ser capaz de apoiar uma grande variedade de aplicações. Porém, algumas aplicações enfrentam um obstáculo, ou seja, o efeito do multicaminho. O multicaminho é o fenômeno pelo qual um sinal chega à antena do receptor por caminhos múltiplos, devido à reflexão. O sinal refletido chega atrasado em relação ao sinal direto. Se estes atrasos forem curtos, ou seja, provenientes de reflexões próximas à antena do receptor, o efeito de multicaminho é caracterizado como de baixa freqüência, caso contrário, o efeito predominante é de alta freqüência. Este efeito distorce a modulação do sinal e a fase da portadora, conseqüentemente, degrada a acurácia e a precisão nos posicionamentos por ponto e relativo. Este efeito também pode impedir a fixação das ambigüidades, ou conduzir a uma solução incorreta das mesmas. Por isso, é de grande importância dispor de meios que possam atenuar o multicaminho. Uma possibilidade para atenuação deste efeito, tanto para fase como para a pseudodistância, é a utilização de uma poderosa ferramenta de análise espectral para o estudo de sinais: a transformada wavelets. Esta transformada decompõe o sinal, neste caso as duplas diferenças, separando as altas freqüências, onde se encontra o efeito do multicaminho proveniente de atrasos longos, das baixas freqüências, ou seja, a identidade do sinal e multicaminho de atrasos curtos. Após o processo de decomposição, utilizando os coeficientes wavelets o sinal pode ser reconstruído sem o efeito de multicaminho de alta freqüência. Esse procedimento é desenvolvido nesta dissertação de Mestrado. Os coeficientes wavelets relativos ao multicaminho obtidos das medidas de dupla diferença foram reconstruídos e, dessa forma, pôde-se analisar os erros e comprovar que satélites em baixos ângulos de elevação sofrem os maiores efeitos de multicaminho...(Resumo completo, clicar acesso eletrônico abaixo) / Abstract: GPS has shown to be capable of supporting a wide variety of applications. However, some applications face a major problem. This is the effect of multipath; witch is a phenomenon whereby a signal arrives at a receiver via multiple paths. The multipath distorts the signal modulation and the carrier phase, degrading the accuracy and precision of absolute and relative positioning. This effect can impede the ambiguities fixation or to induce to an incorrect solution of the same ones. A possibility for the reduction of this effect, either for the carrier phase or the pseudorange is the use of a powerful tool of the spectral analysis to study the signals: wavelet transform. This transform decomposes the double differences signal separating the high frequencies, where there is the multipath effect from long delays, of the low frequencies, that is, identity of the signal and multipath of short delays. After the decomposition process, using the wavelets coefficients the signal can be reconstructed without the high frequency effects. This procedure is developed in this dissertation. The wavelet coefficients relative to the estimated and removed multipath from the double difference were reconstructed and these errors could be analyzed and verified as well that satellites at low elevation angles cause larger multipath errors. The daily multipath repeatability was also verified. Even the high frequency multipath not causing great errors, because the largest cause of these errors is the low frequency one, the correction of this effect provided improvements of up to 30% at the pseudorange average residuals and up to 14% for the carrier phase. The results also showed that the ambiguities solution was more reliable after the high frequency multipath correction. On the other hand, if there were no high frequency multipath effect, the proposed method will not affect the results...(Complete abstract click electronic access below) / Mestre

O mercado de jogos eletrônicos online tem crescido em ritmo acelerado nos últimos anos, particularmente a partir do surgimento do modelo de negócio baseado em serviços. Como consequência, as publicadoras destes jogos passaram a compartilhar problemas comuns na área de serviços, como a erosão do lucro causada pela evasão de usuários. Modelos preditivos têm sido utilizados no combate à evasão em mercados como os de telefonia móvel e de cartões de crédito, setores que detêm um grande volume de informações demográficas e econômicas a respeito dos seus consumidores. Já os publicadores de jogos muitas vezes só possuem o endereço eletrônico dos jogadores. O objetivo deste trabalho é propor um modelo de previsão de evasão com base exclusivamente nos padrões de acesso de usuários em jogos online, onde estes registros temporais são submetidos a um conjunto de operadores que analisam os dados no domínio do plano tempo-frequência, utilizando a Transformada Discreta de Wavelet. Sua principal contribuição está na proposta de parametrização dos dados de entrada para classificadores probabilísticos baseados no algoritmo k-Nearest Neighbors. Testados com dados reais de acessos de usuários ao longo de alguns meses em um jogo online, os classificadores foram avaliados com o uso de curvas ROC (Receiver Operating Characteristic) e de elevação. A abordagem proposta nesta tese, baseada na análise no domínio do plano tempo-frequência, apresentou resultados satisfatórios. Não apenas superiores se comparados com as abordagens no domínio do tempo ou da frequência, mas também comparáveis aos desempenhos encontrados por modelos com centenas de variáveis preditivas utilizados em outros mercados. / The online gaming market has rapidly grown in recent years, particularly since the rise of the service-based business model. As a result, the publishers of these games have started to share usual problems from the services business, like the profit erosion caused by customer churn. Predictive models have been used to address the churn problem in the mobile phones and credit cards markets, where companies have a huge volume of demographic and economic data about their customers. While game publishers often have only their users email addresses. The goal of this study is to propose a model for churn prediction based solely on the online games users access patterns, where these time entries are fed into a set of operators that are able to analyze the data in the time-frequency plane domain, using the Discrete Wavelet Transform. Its main contribution is the input data parameterization proposed for the probabilistic classifiers based on the k-Nearest Neighbors algorithm. Tested with real data from an online game users access over a few months, the classifiers were evaluated using ROC (Receiver Operating Characteristic) and lift curves. The approach proposed in this thesis, based on the analysis of the time-frequency plane domain, has shown satisfactory results. Not only higher when compared with approaches based on both time or frequency domains, but also comparable to performances found on models with hundreds of predictive variables used in other markets.

Orientadores: Rafael Santos Mendes, Jonatas Manzolli / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-10T02:37:04Z (GMT). No. of bitstreams: 1 Luvizotto_AndreLuiz_M.pdf: 5323411 bytes, checksum: 87b1961bd111c6cc93b0d048c33bd164 (MD5) Previous issue date: 2007 / Resumo: Neste trabalho, as transformadas wavelet são utilizadas para recodificar e explorar sinais musicais. A idéia central do trabalho é mostrar que a reordenação adequada dos coeficientes provenientes das análises possibilita não somente recodificar de modo econômico o sinal como também transitar por sonoridades distintas. Ou seja, relaciona-se o posicionamento dos coeficientes wavelets, dentro de cada nível de multiresolução, com a geração de diferentes timbres. Uma vez definido o ordenamento dos coeficientes, duas formas de determinação de seus valores são exploradas. Na primeira forma, essas curvas ascendentes de coeficientes são aproximadas por uma função polinomial de grau p, levando a representações econômicas do sinal musical. Já no segundo modelo, os coeficientes de um sinal distinto (chamado sinal de base) são ordenados de forma ascendente. São então reordenados através das posições equivalentes do sinal original, também chamado de alvo, permitindo a sua reobtenção e também o trânsito entre as duas sonoridades envolvidas. Os resultados deste trabalho destacam a grande importância que o posicionamento dos coeficientes exercem na sonoridade com relação aos seus valores. Com os experimentos realizados, foi possível constatar que valores aproximados de coeficientes, corretamente dispostos no tempo, geram timbres alvos diversos de forma satisfatória. As análises dos resultados são feitas por metodologias diversas e pela audição dos arquivos de áudio gerados, que acompanham o texto em cd. Por fim, uma discussão sobre os resultados obtidos é realizada e uma proposta de continuação da pesquisa é sugerida, baseada em grupos de permutações como forma de síntese / Abstract: Musical signals are encoded and represented using wavelet transforms. Starting upon wavelet analysis, the main research idea is to show how an adequate re-ordination of wavelet coefticients makes possible to decode the signal economically and also to obtain different sonorities. Moreover, we relate a specific set of wavelet coeflicients from °each multi-resolution leveI to generate new timbres. Given re-ordination procedures, two forms to determine their values are explored. First one, coeflicient curves in ascendent order are approximated by a polynomial function of degree p that leads to an economic representation of musical signals. In the second approach, coeflicients from another signal (named "base"signal) are ordinated in ascendent order also. After they are re-ordinate across the positions ofthe original signal, called "target"signal. The results ofthis research highlight the great importance of the wavelet coeflicient's order to manipulate timbre. Experiments presented . here showed that coeflicients with approximated values and correct1y disposed in time, can be used to generate target timbres in a satisfactory way. The analysis of the results were done by different methodologies and by listening to the sound examples from the CD attached to this dissertation. Finally, a discussion of research aims is presented and a proposal for further work based on Mathematical Group of Permutation is projected as a way to develop a new synthesis method / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

No description available.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / We explore the idea of matching a scaling function - the basic building block of a wavelet function - to a desired spectrum. This would allow the scaling function to be used as the signal pulse for a digital communication system that is matched to the channel, avoiding problems such as energy loss or noise amplification due to spectral nulls. An unconstrained parameterization of the scaling function coefficients represents the scaling functions. This parameterization is adapted using gradient descent. Tests indicate that the adaptation is able to capture major features of a desired spectrum, including spectral nulls and major lobes.

No description available.

by Chan, Kin Pong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 100-105). / Abstracts in English and Chinese. / Acknowledgments --- p.ii / Abstract --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Wavelet Transform --- p.4 / Chapter 1.2 --- Time Warping --- p.5 / Chapter 1.3 --- Outline of the Thesis --- p.6 / Chapter 2 --- Related Work --- p.8 / Chapter 2.1 --- Similarity Models for Time Series --- p.8 / Chapter 2.2 --- Dimensionality Reduction --- p.11 / Chapter 2.3 --- Wavelet Transform --- p.15 / Chapter 2.4 --- Similarity Search under Time Warping --- p.16 / Chapter 3 --- Dimension Reduction by Wavelets --- p.21 / Chapter 3.1 --- The Proposed Approach --- p.21 / Chapter 3.1.1 --- Haar Wavelets --- p.23 / Chapter 3.1.2 --- DFT versus Haar Transform --- p.27 / Chapter 3.1.3 --- Guarantee of no False Dismissal --- p.29 / Chapter 3.2 --- The Overall Strategy --- p.34 / Chapter 3.2.1 --- Pre-processing --- p.35 / Chapter 3.2.2 --- Range Query --- p.35 / Chapter 3.2.3 --- Nearest Neighbor Query --- p.36 / Chapter 3.3 --- Performance Evaluation --- p.39 / Chapter 3.3.1 --- Stock Data --- p.39 / Chapter 3.3.2 --- Synthetic Random Walk Data --- p.45 / Chapter 3.3.3 --- Scalability Test --- p.51 / Chapter 3.3.4 --- Other Wavelets --- p.52 / Chapter 4 --- Time Warping --- p.55 / Chapter 4.1 --- Similarity Search based on K-L Transform --- p.60 / Chapter 4.2 --- Low Resolution Time Warping --- p.63 / Chapter 4.2.1 --- Resolution Reduction of Sequences --- p.63 / Chapter 4.2.2 --- Distance Compensation --- p.67 / Chapter 4.2.3 --- Time Complexity --- p.73 / Chapter 4.3 --- Adaptive Time Warping --- p.77 / Chapter 4.3.1 --- Time Complexity --- p.79 / Chapter 4.4 --- Performance Evaluation --- p.80 / Chapter 4.4.1 --- Accuracy versus Runtime --- p.80 / Chapter 4.4.2 --- Precision versus Recall --- p.85 / Chapter 4.4.3 --- Overall Runtime --- p.91 / Chapter 4.4.4 --- Starting Up Evaluation --- p.93 / Chapter 5 --- Conclusion and Future Work --- p.95 / Chapter 5.1 --- Conclusion --- p.95 / Chapter 5.2 --- Future Work --- p.96 / Chapter 5.2.1 --- Application of Wavelets on Biomedical Signals --- p.96 / Chapter 5.2.2 --- Moving Average Similarity --- p.98 / Chapter 5.2.3 --- Clusters-based Matching in Time Warping --- p.98 / Bibliography --- p.99

Chan Chun Ping. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 134-137). / Text in English; abstracts in English and Chinese. / Chan Chun Ping. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Automatic Speech Recognition --- p.1 / Chapter 1.2 --- Review of Speech Recognition Techniques --- p.2 / Chapter 1.3 --- Review of Signal Representation --- p.4 / Chapter 1.4 --- Review of Wavelet Transform --- p.7 / Chapter 1.5 --- Objective of Thesis --- p.11 / Chapter 1.6 --- Thesis Outline --- p.11 / References --- p.13 / Chapter 2 --- Baseline Speech Recognition System --- p.17 / Chapter 2.1 --- Intoduction --- p.17 / Chapter 2.2 --- Feature Extraction --- p.18 / Chapter 2.3 --- Hidden Markov Model for Speech Recognition --- p.24 / Chapter 2.3.1 --- The Principle of Using HMM in Speech Recognition --- p.24 / Chapter 2.3.2 --- Elements of an HMM --- p.27 / Chapter 2.3.3 --- Parameters Estimation and Recognition Algorithm --- p.30 / Chapter 2.3.4 --- Summary of HMM based Speech Recognition --- p.31 / Chapter 2.4 --- TIMIT Continuous Speech Corpus --- p.32 / Chapter 2.5 --- Baseline Speech Recognition Experiments --- p.36 / Chapter 2.6 --- Summary --- p.39 / References --- p.40 / Chapter 3 --- Multi-Resolution Based Acoustic Features --- p.42 / Chapter 3.1 --- Introduction --- p.42 / Chapter 3.2 --- Discrete Wavelet Transform --- p.43 / Chapter 3.3 --- Periodic Discrete Wavelet Transform --- p.47 / Chapter 3.4 --- Multi-Resolution Analysis on STFT Spectrum --- p.49 / Chapter 3.5 --- Principal Component Analysis --- p.52 / Chapter 3.5.1 --- Related Work --- p.52 / Chapter 3.5.2 --- Theoretical Background of PCA --- p.53 / Chapter 3.5.3 --- Examples of Basis Vectors Found by PCA --- p.57 / Chapter 3.6 --- Experiments for Multi-Resolution Based Feature --- p.60 / Chapter 3.6.1 --- Experiments with Clean Speech --- p.60 / Chapter 3.6.2 --- Experiments with Noisy Speech --- p.64 / Chapter 3.7 --- Summary --- p.69 / References --- p.70 / Chapter 4 --- Wavelet Packet Based Acoustic Features --- p.72 / Chapter 4.1 --- Introduction --- p.72 / Chapter 4.2 --- Wavelet Packet Filter-Bank --- p.74 / Chapter 4.3 --- Dimensionality Reduction --- p.76 / Chapter 4.4 --- Filter-Bank Parameters --- p.77 / Chapter 4.4.1 --- Mel-Scale Wavelet Packet Filter-Bank --- p.77 / Chapter 4.4.2 --- Effect of Down-Sampling --- p.78 / Chapter 4.4.3 --- Mel-Scale Wavelet Packet Tree --- p.81 / Chapter 4.4.4 --- Wavelet Filters --- p.84 / Chapter 4.5 --- Experiments Using Wavelet Packet Based Acoustic Features --- p.86 / Chapter 4.6 --- Broad Phonetic Class Analysis --- p.89 / Chapter 4.7 --- Discussion --- p.92 / Chapter 4.8 --- Summary --- p.99 / References --- p.100 / Chapter 5 --- De-Noising by Wavelet Transform --- p.101 / Chapter 5.1 --- Introduction --- p.101 / Chapter 5.2 --- De-Noising Capability of Wavelet Transform --- p.103 / Chapter 5.3 --- Wavelet Transform Based Wiener Filtering --- p.105 / Chapter 5.3.1 --- Sub-Band Position for Wiener Filtering --- p.107 / Chapter 5.3.2 --- Estimation of Short-Time Speech and Noise Power --- p.109 / Chapter 5.4 --- De-Noising Embedded in Wavelet Packet Filter-Bank --- p.115 / Chapter 5.5 --- Experiments Using Wavelet Build-in De-Noising Properties --- p.118 / Chapter 5.6 --- Discussion --- p.120 / Chapter 5.6.1 --- Broad Phonetic Class Analysis --- p.122 / Chapter 5.6.2 --- Distortion Measure --- p.124 / Chapter 5.7 --- Summary --- p.132 / References --- p.134 / Chapter 6 --- Conclusions and Future Work --- p.138 / Chapter 6.1 --- Conclusions --- p.138 / Chapter 6.2 --- Future Work --- p.140 / References --- p.142 / Appendix 1 Jacobi's Method --- p.143 / Appendix 2 Broad Phonetic Class --- p.148

Vehicle vibration is inherently random and non-stationary with a non-Gaussian distribution. In addition, variations in vehicle parameters, product payloads and distribution journeys mean that the characteristics of vibration are not identical for all distribution journeys. Because vehicle vibration and shock are key causes of damage during distribution, their simulation in pre-distribution testing is vital in order to ensure that adequate protection is provided for transported products. The established method set out in the current testing standards utilises a global set of averaged accelerated power spectral density spectra to construct random vibration signals. These signals are stationary with Gaussian distributions and, therefore, do not fully represent actual vehicle vibration, only an average. The aim of the investigation, reported on in this Thesis, was to create an improved test regime for simulating vehicle vibration for pre-distribution testing of packaging. This aim has been achieved through the construction of representative tests and the creation of realistic simulations with statistical significance. A journey database has been created, in which historic road profile data along with a quarter vehicle model have been used to approximate a known vehicle’s vibration on a specific distribution journey. Additionally, a wavelet decomposition method, in which wavelet analysis is used to decompose the approximate vehicle vibration in to a series of Gaussian approximations of varying amplitude and spectral content, has been developed. Along with theoretical work, case studies have been undertaken in order to validate the test regime.

Dentre as inúmeras técnicas de conversão de voz utilizadas atualmente, aquelas baseadas em bancos de filtros wavelet, associadas com redes neurais artificiais,têm se destacado. Este trabalho se concentra em tais técnicas, realizando um estudo que relaciona qual a melhor wavelet para conversão de determinados padrões de voz, apresentando uma análise detalhada de quais são as características que levam a estes resultados. Os testes são realizados com vozes da base de dados TIMIT do Linguistic Data Consortium (LDC). / Dentre as inúmeras técnicas de conversão de voz utilizadas atualmente, aquelas baseadas em bancos de filtros wavelet, associadas com redes neurais artificiais, têm se destacado. Este trabalho se concentra em tais técnicas, realizando um estudo que relaciona qual a melhor wavelet para conversão de determinados padrões de voz, apresentando uma análise detalhada de quais são as características que levam a estes resultados. Os testes são realizados com vozes da base de dados TIMIT do Linguistic Data Consortium (LDC).