International Telemetering Conference Proceedings / October 29-November 02, 1990 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Fast Fourier Transform (FFT) converts digitally sampled time domain data into the frequency domain. This paper will provide an advanced introduction for the telemetry engineer to basic FFT theory and then present and explain the different user preprocessing options that are available when using the FFT. These options include: using windowing functions, “zero filling” for frequency data interpolation, and setting the frequency resolution of the FFT resultant spectrum,

Electronic devices have acquired an increasingly important role in our society and are integrated in our lives making both the users and their devices more accessible. Currently in the western world most families have at least one computer. This computer is generally equipped with multimedia accessories and an Internet connection. Portable devices, such as mobile phones and PDAs, are part of this technological and social environment. One might think about using a hands free Bluetooth headset together with a mobile phone, to obtain better sound quality, using a keyboard such as the Handykey Corp. Twiddler in order to dial/type quicker or send SMS messages in an easier way, watching a video on a large computer screen that had previously been downloaded to your mobile phone, etcetera. However, there is a problem when it comes to the interconnectivity between all these devices. Today users face many difficulties when attempting to use what should be the aggregated possibilities of their devices, rather than simply the functionality of each device. The hypothesis of this project is that the user's difficulties could be overcome if their devices could be internetworked. For example, even though mobile phones and PDAs often have a USB interface, unlike typical desktop or laptop computers these devices have been designed to only be USB slaves -- hence other USB devices cannot be directly attached to them. There are some signs of this changing with the introduction of USB On-The-Go - but we believe that this is a short-sighted evolutionary step. The obvious solution is to internetwork these devices. For example, by attaching these various USB devices to a computer that is a USB bus master (host) - we can enable the user to use their USB Twiddler with a USB phone. In this way, a user could remotely access the functions of the set of all of their portable devices - without worrying about how to directly interconnect them in pairs. This could enable new functionality, such as the user being able to answer an incoming call to their cellular phone with the keypad of the Twiddler, while using the audio input and output functions of their Bluetooth headset. We begin by examining a number of means to establish and use remote connections to access systems remotely. We have focused on the most popular desktop sharing systems, specifically those that use remote desktop protocols. Initially we require manual configuration or use of a discovery protocol to identify the different devices. Later we will examine additional protocols, along with some potentially automatic configuration mechanisms. / Elektroniska apparater har fått en att starkare position i vårt samhälle, integerationen i våra liv gör dem mer tillgängliga. Nu för tiden har de flesta familjer i västvärlden, minst en dator per hushåll. Datorerna har allt som oftast flera multimedia tillbehör och en internett uppkopling. Handhållna aparater så som mobiltelefoner och PDA’er är också en del av teknologiska och sociala miljön. Kanske vill man andvända en handsfree med blue tooth för att förbättra ljudkvaliteten, eller ett tangentbord t.ex. ett Handykey Corp. En twiddler för att ringa eller skicka SMS. Se på högkavitets video på en stor skärm som du tidigare lastat ner till din mobiltelefon, etc. Hur som hälst uppstår det problem vid sammankopplingen mellan olika tillbehör. Dagens användare får en stor utmaning i användade av den kombinerade funktionen i stället för den ensamstående apparatens funktioner och förmåga. Hypotesen av detta projekt är att detta problem kan övervinnas om alla apparater var ihopkoplade via internetwork. Till exempel, även om de flesta mobiltelefoner och PDA’er har USB gränssnitt, har dem tillskillnad från vanliga stationära datorer och laptops bara designats för att vara USB-slavar. Detta betyder att USB-tillbehör inte kan kopplas direkt till apparaten. Det finns tecken på tekniker som t.ex. USB On-The-Go men detta ser ut som en kortsiktig lösning. En uppenbar lösning är att parkoppla dessa apparater via internetwork. Om man t.ex. kopplar alla dessa USB-tillbehör till en stationär eller bärbar dator, kan vi låta användaren komma åt dessa via sin telefon med USB. På så sätt kan användaren trådlöst komma åt alla tillkopplade tillbehör, utan att oroa sig över att para samman dem fysiskt. Möjligheten för nya funktioner och användningsområden visar sig då, som t.ex. att svara på inkommande samtal med den tillkoplade twiddler’n medans samtidigt tala via det trådlösa headsettet. Vi börjar med att undersöka olika tekniker för att upprätta trådlös tillkoppling till olika system. Vi har focuserat på de populäraste datasystemen, framför allt de som använder trådlösa protokoll. Sådana som kräver manuell installation eller använder upptäkande protokoll för att identifiera olika tillbehör. Senare visar vi exempel på andra protokoll med några potensial att automatisk konfigurera tillkopplingen. / 1F1421 Project report Oral presentation given 2008-07-30 14:00 http://www.ict.kth.se/info/GRU/Events/Old-Seminars/2008/20080730-14.00-CCS-Exjobb-presentation.html

This master thesis aims for Inter-carrier interference (ICI) mitigation in orthogonal frequency division multiplexing (OFDM) system by considering designs of frequency domain cyclic extension(FDCE) and optimal windowing pulse shape. Although OFDM system has been put forward in the 1970s, it has just emerged in 4G. In the early stage, it has been restricted by its high computational complexity. With the discovery that modulation and demodulation process of OFDM can be realized by discrete Fourier transform (DFT) and inverse discrete Fourier transform (IDFT), it is widely used in 4G and 5G-New Ratio (NR). Based on OFDM system, a variety of derivative systems are further proposed and applied. With the development of 5G technology in the mobile communication, the requirement of signal propagation between high-speed mobile user and base station (BS) is higher and higher. With the increase of the moving speed of objects, the frequency shift caused by Doppler eff ect can not be underestimated. ICI caused by Doppler shift is becoming more and more serious. Therefore, how to eliminate the ICI caused by Doppler shift has become an inevitable potential problem. In this thesis, two eff ective approaches for ICI mitigation have been explored and studied. By adding FDCE and optimal windowing pulse shape, the system performance is analyzed and the system simulation is constructed in MATLAB.

Estudos de expressão gênica têm sido de extrema importância, permitindo desenvolver terapias, exames diagnósticos, medicamentos e desvendar uma infinidade de processos biológicos. No entanto, estes estudos envolvem uma série de dificuldades: grande quantidade de genes, sendo que geralmente apenas um pequeno número deles está envolvido no problema estudado; presença de ruído nos dados analisados; entre muitas outras. O projeto de pesquisa deste mestrado consiste no estudo de algoritmos de indução de árvores de decisão; na definição de uma metodologia capaz de tratar dados de expressão gênica usando árvores de decisão; e na implementação da metodologia proposta como algoritmos capazes de extrair conhecimento a partir desse tipo de dados. A indução de árvores de decisão procura por características relevantes nos dados que permitam modelar precisamente um conceito, mas tem também a preocupação com a compreensibilidade do modelo gerado, auxiliando os especialistas na descoberta de conhecimento, algo importante nas áreas médica e biológica. Por outro lado, tais indutores apresentam relativa instabilidade, podendo gerar modelos bem diferentes com pequenas mudanças nos dados de treinamento. Este é um dos problemas tratados neste mestrado. Mas o principal problema tratado se refere ao comportamento destes indutores em dados de alta dimensionalidade, mais especificamente dados de expressão gênica: atributos irrelevantes prejudicam o aprendizado e vários modelos com desempenho similar podem ser gerados. Diversas técnicas foram exploradas para atacar os problemas mencionados, mas este estudo se concentrou em duas delas: windowing, que foi a técnica mais explorada e para a qual este mestrado propôs uma série de alterações com vistas à melhoria de seu desempenho; e lookahead, que procura construir a árvore levando em considerações passos subsequentes do processo de indução. Quanto ao windowing, foram explorados aspectos relacionados ao procedimento de poda das árvores geradas durante a execução do algoritmo; uso do erro estimado em substituição ao erro de treinamento; uso de ponderação do erro calculado durante a indução de acordo com o tamanho da janela; e uso da confiança na classificação para decidir quais exemplos utilizar na atualização da janela corrente. Com relação ao lookahead, foi implementada uma versão de um passo à frente, ou seja, para tomar a decisão na iteração corrente, o indutor leva em consideração a razão de ganho de informação do passo seguinte. Os resultados obtidos, principalmente com relação às medidas de desempenho baseadas na compreensibilidade dos modelos induzidos, mostram que os algoritmos aqui propostos superaram algoritmos clássicos de indução de árvores. / Gene expression studies have been of great importance, allowing the development of new therapies, diagnostic exams, drugs and the understanding of a variety of biological processes. Nevertheless, those studies involve some obstacles: a huge number of genes, while only a very few of them are really relevant to the problem at hand; data with the presence of noise; among others. This research project consists of: the study of decision tree induction algorithms; the definition of a methodology capable of handling gene expression data using decision trees; and the implementation of that methodology as algorithms that can extract knowledge from that kind of data. The decision tree induction searches for relevant characteristics in the data which would allow it to precisely model a certain concept, but it also worries about the comprehensibility of the generated model, helping specialists to discover new knowledge, something very important in the medical and biological areas. On the other hand, such inducers present some instability, because small changes in the training data might produce great changes in the generated model. This is one of the problems being handled in this Master\'s project. But the main problem this project handles refers to the behavior of those inducers when it comes to high-dimensional data, more specifically to gene expression data: irrelevant attributes may harm the learning process and many models with similar performance may be generated. A variety of techniques have been explored to treat those problems, but this study focused on two of them: windowing, which was the most explored technique and to which this project has proposed some variations in order to improve its performance; and lookahead, which builds each node of a tree taking into consideration subsequent steps of the induction process. As for windowing, the study explored aspects related to the pruning of the trees generated during intermediary steps of the algorithm; the use of the estimated error instead of the training error; the use of the error weighted according to the size of the current window; and the use of the classification confidence as the window update criterion. As for lookahead, a 1-step version was implemented, i.e., in order to make the decision in the current iteration, the inducer takes into consideration the information gain ratio of the next iteration. The results show that the proposed algorithms outperform the classical ones, especially considering measures of complexity and comprehensibility of the induced models.

Estudos de expressão gênica têm sido de extrema importância, permitindo desenvolver terapias, exames diagnósticos, medicamentos e desvendar uma infinidade de processos biológicos. No entanto, estes estudos envolvem uma série de dificuldades: grande quantidade de genes, sendo que geralmente apenas um pequeno número deles está envolvido no problema estudado; presença de ruído nos dados analisados; entre muitas outras. O projeto de pesquisa deste mestrado consiste no estudo de algoritmos de indução de árvores de decisão; na definição de uma metodologia capaz de tratar dados de expressão gênica usando árvores de decisão; e na implementação da metodologia proposta como algoritmos capazes de extrair conhecimento a partir desse tipo de dados. A indução de árvores de decisão procura por características relevantes nos dados que permitam modelar precisamente um conceito, mas tem também a preocupação com a compreensibilidade do modelo gerado, auxiliando os especialistas na descoberta de conhecimento, algo importante nas áreas médica e biológica. Por outro lado, tais indutores apresentam relativa instabilidade, podendo gerar modelos bem diferentes com pequenas mudanças nos dados de treinamento. Este é um dos problemas tratados neste mestrado. Mas o principal problema tratado se refere ao comportamento destes indutores em dados de alta dimensionalidade, mais especificamente dados de expressão gênica: atributos irrelevantes prejudicam o aprendizado e vários modelos com desempenho similar podem ser gerados. Diversas técnicas foram exploradas para atacar os problemas mencionados, mas este estudo se concentrou em duas delas: windowing, que foi a técnica mais explorada e para a qual este mestrado propôs uma série de alterações com vistas à melhoria de seu desempenho; e lookahead, que procura construir a árvore levando em considerações passos subsequentes do processo de indução. Quanto ao windowing, foram explorados aspectos relacionados ao procedimento de poda das árvores geradas durante a execução do algoritmo; uso do erro estimado em substituição ao erro de treinamento; uso de ponderação do erro calculado durante a indução de acordo com o tamanho da janela; e uso da confiança na classificação para decidir quais exemplos utilizar na atualização da janela corrente. Com relação ao lookahead, foi implementada uma versão de um passo à frente, ou seja, para tomar a decisão na iteração corrente, o indutor leva em consideração a razão de ganho de informação do passo seguinte. Os resultados obtidos, principalmente com relação às medidas de desempenho baseadas na compreensibilidade dos modelos induzidos, mostram que os algoritmos aqui propostos superaram algoritmos clássicos de indução de árvores. / Gene expression studies have been of great importance, allowing the development of new therapies, diagnostic exams, drugs and the understanding of a variety of biological processes. Nevertheless, those studies involve some obstacles: a huge number of genes, while only a very few of them are really relevant to the problem at hand; data with the presence of noise; among others. This research project consists of: the study of decision tree induction algorithms; the definition of a methodology capable of handling gene expression data using decision trees; and the implementation of that methodology as algorithms that can extract knowledge from that kind of data. The decision tree induction searches for relevant characteristics in the data which would allow it to precisely model a certain concept, but it also worries about the comprehensibility of the generated model, helping specialists to discover new knowledge, something very important in the medical and biological areas. On the other hand, such inducers present some instability, because small changes in the training data might produce great changes in the generated model. This is one of the problems being handled in this Master\'s project. But the main problem this project handles refers to the behavior of those inducers when it comes to high-dimensional data, more specifically to gene expression data: irrelevant attributes may harm the learning process and many models with similar performance may be generated. A variety of techniques have been explored to treat those problems, but this study focused on two of them: windowing, which was the most explored technique and to which this project has proposed some variations in order to improve its performance; and lookahead, which builds each node of a tree taking into consideration subsequent steps of the induction process. As for windowing, the study explored aspects related to the pruning of the trees generated during intermediary steps of the algorithm; the use of the estimated error instead of the training error; the use of the error weighted according to the size of the current window; and the use of the classification confidence as the window update criterion. As for lookahead, a 1-step version was implemented, i.e., in order to make the decision in the current iteration, the inducer takes into consideration the information gain ratio of the next iteration. The results show that the proposed algorithms outperform the classical ones, especially considering measures of complexity and comprehensibility of the induced models.

A speech visualization system is proposed thatcould be used by a deaf person for understanding speech.Several novel techniques are proposed, including: (1) Minimizing spectral leakage in the Fourier transform by using avariable-length window. (2) Making use of the fact that there is no spectral leakage in order to calculate how much of the energy of the speech signal is due to its periodic component vs. its nonperiodic component. (3) Modelling the mouth and lips as a band-pass filter and estimating the central frequency and bandwidth of this filter in order to assign colours tounvoiced speech sounds.

In this dissertation, multicarrier schemes are reviewed within the framework of Gabor Systems. Their fundamental elements; what to transmit, i.e., symbols, how to transmit, i.e., filters or pulse shape, and where/when to transmit, i.e., lattices are investigated extensively. The relations between different types of multicarrier schemes are discussed. Within the framework of Gabor systems, a new windowing approach, edge windowing, is developed to address the out-of-band (OOB) radiation problem of orthogonal frequency division multiplexing (OFDM) based multicarrier schemes. To the best of our knowledge, for the first time, the diversity on the range of the users is exploited to suppress the sidelobes of OFDM. In addition to that, the concept of using different filters in OFDM structure is proposed. Besides the improvement on the OOB radiation performance of OFDM via edge windowing, conventional lattice structure of OFDM frame is enhanced considering the diversity in the network. The lattice structure of an OFDM frame is designed based on the statistical characteristics of the range of the users and the mobility. The concept of channel-aware frame structure is developed, which allows more efficient and reliable transmission. In addition to the aforementioned improvements on OFDM, interference issues in uncoordinated networks are addressed in this dissertation considering different multicarrier schemes. It is stressed that the interference from other links in the network sharing the same spectrum might degrade the link performance between the devices in an uncoordinated network, significantly. Considering the degradation due to other-user interference, the concept of partially overlapping tones (POT) is proposed. With the concept of partially overlapping tones, the interference energy observed at the victim receiver is mitigated via an intentional frequency offset between the links. The usefulness of intentional frequency offset to combat with the asynchronous nature of other-user interference without any timing constraint between interfering signals is emphasized. To the best of our knowledge, for the first time, the efficacy of non-orthogonal schemes are shown along with POT to address the other-user interference, which relies on the fact that self-interference problem is easier than other-user interference problem in an uncoordinated network. In the last part of this dissertation, required number of equalizer taps for multicarrier schemes is investigated to address the potential self-interference problems (e.g. due to the non-orthogonal multicarrier schemes with the concept of POT). Composite impact of transmit pulse shape, communication medium, and receive filter on the characteristics of the interference among the symbols in time and frequency is analyzed. It is emphasized that while taking less number of taps into account for the channel estimation causes lack of description of the composite effect, using more number of taps folds the noise into the estimated channel. The number of interfering symbols and their locations are obtained in both time and frequency for a given multicarrier scheme and signal-to-noise ratio. It is shown that correct number of taps yields not only improvement on BER performance but also less complex equalizer structures in practice.

In this paper, we present a nonlinear curvelet-based sparsity-promoting formulation for three problems related to seismic noise, namely the ’good’, corresponding to noise generated by random sampling; the ’bad’, corresponding to coherent noise for which (inaccurate) predictions exist and the ’ugly’ for which no predictions exist. We will show that the compressive capabilities of curvelets on seismic data and images can be used to tackle these three categories of noise-related problems.

No description available.

The standard processing architectures are enough to satisfy a lot of applications by employing already existing stream processing frameworks which are able to manage distributed data processing. In some specific cases, having geographically distributed data sources requires to distribute even more the processing over a large area by employing a geographically distributed architecture.‌ The issue addressed in this work is the reduction of data movement across the network which is continuously flowing in a geo-distributed architecture from streaming sources to the processing location and among processing entities within the same distributed cluster. Reduction of data movement can be critical for decreasing bandwidth costs since accessing links placed in the middle of the network can be costly and can increase as the amount of data exchanges increase. In this work we want to create a different concept to deploy geographically distributed architectures by relying on Apache Spark Structured Streaming and Apache Kafka. The features needed for an algorithm to run on a geo-distributed architecture are provided. The algorithms to be executed on this architecture apply the windowing and the data synopses techniques to produce a summaries of the input data and to address issues of the geographically distributed architecture. The computation of the average and the Misra-Gries algorithm are then implemented to test the designed architecture. This thesis work contributes in providing a new model of building geographically distributed architecture. The experimental results show that, for the algorithms running on top of the geo distributed architecture, the computation time is reduced on average by 70% compared to the distributed setup. Similarly, and the amount of data exchanged across the network is reduced on average by 99%, compared to the distributed setup. / Standardbehandlingsarkitekturer är tillräckligt för uppfylla behoven av många tillämpningar genom användning av befintliga ramverk för flödesbehandling med stöd för distribuerad databehandling. I specifika fall kan geografiskt fördelade datakällor kräva att databehandlingen fördelas över ett stort område med hjälp av en geografiskt distribuerad arkitektur. Problemet som behandlas i detta arbete är minskningen av kontinuerlig dataöverföring i ett nätverk med geo-distribuerad arkitektur. Minskad dataöverföring kan vara avgörande för minskade bandbreddskonstnader då åtkomst av länkar placerade i mitten av ett nätverk kan vara dyrt och öka ytterligare med tilltagande dataöverföring. I det här arbetet vill vi skapa ett nytt koncept för att upprätta geografiskt distribuerade arkitekturer med hjälp av Apache Spark Structured Streaming och Apache Kafka. Funktioner och förutsättningar som behövs för att en algoritm ska kunna köras på en geografisk distribuerad arkitektur tillhandahålls. Algoritmerna som ska köras på denna arkitektur tillämpar “windowing synopsing” och “data synopses”-tekniker för att framställa en sammanfattning av ingående data samt behandla problem beträffande den geografiskt fördelade arkitekturen. Beräkning av medelvärdet och Misra-Gries-algoritmen implementeras för att testa den konstruerade arkitekturen. Denna avhandling bidrar till att förse ny modell för att bygga geografiskt distribuerad arkitektur. Experimentella resultat visar att beräkningstiden reduceras i genomsnitt 70% för de algoritmer som körs ovanför den geo-distribuerade arkitekturen jämfört med den distribuerade konfigurationen. På liknande sätt reduceras mängden data som utväxlas över nätverket med 99% i snitt jämfört med den distribuerade inställningen.