Inferência da força de interação nos fenômenos físicos/biológicos é objetivo comum a diversas áreas da ciência. Em particular, nas neurociências tem-se assistido a uma mudança no paradigma experimental em que a atenção tem-se voltado à compreensão da interação entre grupamentos neuronais. Em vista desta demanda surgiram naturalmente diversos métodos estatísticos de medida de dependência entre grupamentos neurais. Alguns foram desenhados para inferência de fluxo de informação, sem contudo precisar o que se entende por fluxo de informação, gerando consequentemente controvérsias na literatura. O principal objetivo deste trabalho é aplicar os conceitos da Teoria da Informação na análise de processos estacionários de segunda ordem para precisar as idéias de fluxo de informação utilizadas na literatura de forma ad hoc e obter um melhor entendimento da relação existente entre as diferentes medidas de dependência propostas. / We study the relationship between different measures of causality or information flow. We show that the concept of partial measures of dependence are related to the definition of inverse random variables.

Although the overall levels of harmonics in modern power supply systems are in most of the practical cases still below the prescribed tolerance limits and thresholds (e.g. these stipulated in [IEC 61000-3-2 and 61000-3-12]), the sources of harmonics are constantly increasing in numbers and are expected to increase even more in the future. Some of the examples of modern non-linear power electronic (PE) devices that are expected to be employed on a much wider scale in LV networks in the future include: light-emitting diode (LED) lamps, switched-mode power supplies (SMPS'), electric vehicle battery chargers (EVBCs) and photovoltaic inverters (PVIs), which are all analysed in this thesis. The thesis first reviews the conventional harmonic analysis methods, investigating their applicability to modern PE devices. After that, the two most widely used forms of harmonic models, i.e. component-based models (CBMs) and frequency-domain models (FDMs), are applied for modelling of the four abovementioned types of modern PE devices and their models are fully validated by measurements. The thesis next investigates the impact of supply voltage conditions and operating modes (e.g. low vs high operating powers) on the device characteristics and performance, using both measurements and developed CBMs and FDMs. The obtained results confirm that both supply conditions and operating modes have an impact on the characteristics of most of the considered PE devices, which is taken into account in the developed models and demonstrated on a number of case studies. As the next contribution, the thesis proposes new indices for the evaluation of current waveform distortions, allowing for a separate analysis of contributions of low and high frequency harmonics and interharmonics to the total waveform distortion of PE devices. As the modern PE devices are normally based on high-frequency switching converters or inverters, the impact of circuit topologies and control algorithms on their harmonic emission characteristics and performance is also investigated. Special attention is given to the operation of PE devices at low powers, when there is a significant increase of current waveform distortion, a substantial decrease of efficiency and power factors and when input ac current might lose its periodicity with the supply voltage frequency. This is analysed in detail for SMPS', resulting in the proposal of a new methodology ("operating cycle based method") for evaluating overall performance of PE devices across the entire range of operating powers. Finally, a novel and simple hybrid harmonic modelling technique, allowing for the use of both time-domain and frequency-domain models in the same simulation environment, is proposed and illustrated on the selected case studies. This is accompanied with a frequency-domain aggregation approach, which is applied in the thesis to investigate the impact of increasing numbers of different types of modern PE devices on the LV network. The implementation of the developed hybrid harmonic modelling approach and frequency-domain aggregation technique is demonstrated on the example of a typical (UK) urban generic LV distribution network and used for the analysis of different deployment levels of EVs and PVIs. The presented harmonic modelling framework for individual PE devices and, particularly, for their aggregate models, fills the gap in the existing literature on harmonic modelling and characterisation of modern PE devices, which is important for the correct evaluation of their harmonic interactions and analysis of the impact of their large-scale deployment on the overall network performance.

Accurate linear and nonlinear models for devices and components are essential for successful RF/microwave computer aided engineering (CAE). The modeling techniques can be categorized in different levels based on the abstraction of the model as well as the application of the models at various design phases. This dissertation deals with behavioral modeling techniques for nonlinear RF components, especially amplifiers. There is an increasing demand for accurate behavioral models of RF and microwave components, or integrated circuit (IC) blocks used in wireless system designs. Accurate behavioral models help designers evaluate and select the appropriate components at simulation phase, thereby cutting development cost. However, there isnt a practical (or flexible) solution for accurate and effective behavioral model generation. This dissertation tries to tackle this problem. Power amplifiers and devices are the main components studied in this dissertation. The primary focus is on the characterization of the loadpull performance of power amplifiers and devices. Major contributions of this dissertation include development of advanced loadpull measurement procedures, large-signal load-aware behavioral model, and a load-aware behavioral model with memory-effect capabilities. There are two advanced loadpull measurements documented in this dissertation: the AM-PM loadpull measurement and the digital demodulation loadpull measurement. These two measurements may have been used internally by some research groups, however, according to the best knowledge of the author, they havent received much attention in the literature. This is the first published work on these two topics. It is shown in this work that the AM-PM performance can be strongly dependent on the load conditions. This property provides important information about the nonlinearities of power amplifiers and is used herein to create better behavioral models. This newly developed digital demodulation loadpull measurement procedure enables system designers to evaluate power amplifiers directly against digital communication system parameters such as error vector magnitude (EVM). Two example measurements are given to demonstrate the measurement system setup and the correlations between traditional nonlinear figure-of-merits and system metrics. A new behavioral modeling technique / procedure is developed based on loadpull AM-AM and AM-PM measurements. The large-signal scattering function theory is applied in the technique to formulate the model. The created model is able to automatically detect the load impedance and generate corresponding nonlinear properties. Three example models are presented to demonstrate the capability of this technique to predict accurately the output power contours, 50 ohm large-signal S21, and 3rd order intermodulation products (through additional file-based model). Finally, a modeling technique is demonstrated to enable predicting the linear memory effect within a varying load condition. The nonlinear block used in the traditional two-box model structure is replaced with the large-signal loadpull model mentioned above. By adding this new feature, the resulting model is able to predict the load-related AM-AM and AM-PM properties, which will improve the accuracy of ACPR prediction.

<p>Efficient radio resource management is of paramount importance for achieving the high bit rates targeted by the 3GPP for the 3GPP Long-Term Evolution. The radio air interface must be able to provide both high peak bit rates and acceptable cell-edge bit rates. This thesis therefore investigates three methods which try to combine the peak bit rate of a reuse-1 system with the cell-edge bit rate of a reuse-3 system in an OFDM-based downlink. These methods are soft frequency reuse, reuse partitioning and one variation of soft frequency reuse, reuse-1 with prioritization.</p><p>In static simulations with one user per cell and a system load of 100 percent, a Shannon capacity gain of up to 18 percent at the 10th percentile is shown with reuse partitioning compared to a reuse-1 system. This gain comes coupled with a loss of only 5 percent at the median. Soft frequency reuse is also investigated statically and shows a 13 percent gain at the 10th percentile compared to a reuse-1 system. Having a lower 10th percentile gain than reuse partitioning, it also shows a slightly smaller loss of 4 percent at the median and a much smaller loss at the 90th percentile.</p><p>Dynamic simulations with a traffic model and multiple users per cell offer a more realistic scenario and show that the proposed intercell interference management methods do not provide the same throughput gains in the dynamic case at low system loads. If interference is not an issue, interference coordination is still costly in terms of limiting bandwidth and/or decreasing the scheduling gain, but provides no significant interference reduction. At low system loads, reuse-1 is therefore the best scheme although interference coordination might prove necessary to provide edge-user throughput at high loads. For such purposes, soft frequency reuse is shown to be a potential candidate and although not investigated in a dynamic setting, reuse partitioning is believed to have similar performance. The traffic model chosen in this thesis only allows study of low system loads but at these loads, soft frequency reuse performs promisingly close to a reuse-1 system.</p>

Industrirobotar är idag en väsentlig del i tillverkningsindustrin där de bland annat används för att minska kostnader, öka produktivitet och kvalitet och ersätta människor i farliga eller slitsamma uppgifter. Höga krav på noggrannhet och snabbhet hos robotens rörelser innebär också höga krav på de matematiska modeller som ligger till grund för robotens styrsystem. Modellerna används där för att beskriva det komplicerade sambandet mellan robotarmens rörelser och de motorer som orsakar rörelsen. Tillförlitliga modeller är också nödvändiga för exempelvis mekanisk design, simulering av prestanda, diagnos och övervakning. En trend idag är att bygga lättviktsrobotar, vilket innebär att robotens vikt minskas men att den fortfarande kan hantera en lika tung last. Orsaken till detta är främst att minska kostnaden, men också säkerhetsaspekter spelar in. En lättare robotarm ger dock en vekare struktur där elastiska effekter inte längre kan försummas i modellen om man kräver hög prestanda. De elastiska effekterna beskrivs i den matematiska modellen med hjälp av fjädrar och dämpare. Denna avhandling handlar om hur dessa matematiska modeller kan tas fram genom systemidentifiering, vilket är ett viktigt verktyg där mätningar från robotens rörelser används för att bestämma okända parametrar i modellen. Det som mäts är position och moment hos robotens alla motorer. Identifiering av industrirobotar är ett utmanande problem bland annat eftersom robotens beteende varierar beroende på armens position. Den metod som föreslås i avhandlingen innebär att man först identifierar lokala modeller i ett antal positioner. Var och en av dessa beskriver robotens beteende kring en viss arbetspunkt. Sedan anpassas parametrarna i en global modell, som är giltig för alla positioner, så att den så väl som möjligt beskriver det lokala beteendet i de olika positionerna. I avhandlingen analyseras olika metoder för att ta fram lokala modeller. För att få bra resultat krävs att experimenten är omsorgsfullt utformade. För att minska osäkerheten i den globala modellens identifierade parametrar ingår också valet av optimala positioner för experimenten. Olika metoder för att identifiera parametrarna jämförs i avhandlingen och experimentella resultat visar användbarheten av den föreslagna metoden. Den identifierade robotmodellen ger en bra global beskrivning av robotens beteende. Resultatet av forskningen har även gjorts tillgängligt i ett datorverktyg för att noggrant kunna ta fram lokala modeller och identifiera parametrar i dynamiska robotmodeller. / Industrial robots are today essential components in the manufacturing industry where they are used to save costs, increase productivity and quality, and eliminate dangerous and laborious work. High demands on accuracy and speed of the robot motion require that the mathematical models, used in the motion control system, are accurate. The models are used to describe the complicated nonlinear relation between the robot motion and the motors that cause the motion. Accurate dynamic robot models are needed in many areas, such as mechanical design, performance simulation, control, diagnosis, and supervision. A trend in industrial robots is toward lightweight robot structures, where the weight is reduced but with a preserved payload capacity. This is motivated by cost reduction as well as safety issues, but results in a weaker (more compliant) mechanical structure with enhanced elastic effects. For high performance, it is therefore necessary to have models describing these elastic effects. This thesis deals with identification of dynamic robot models, which means that measurements from the robot motion are used to estimate unknown parameters in the models. The measured signals are angular position and torque of the motors. Identifying robot models is a challenging task since an industrial robot is a multivariable, nonlinear, unstable, and resonant system. In this thesis, the unknown parameters (typically spring-damper pairs) in a physically parameterized nonlinear dynamic model are identified, mainly in the frequency domain, using estimates of the nonparametric frequency response function (FRF) in different robot configurations/positions. Each nonparametric FRF then describe the local behavior around an operating point. The nonlinear parametric robot model is linearized in the same operating points and the optimal parameters are obtained by minimizing the discrepancy between the nonparametric FRFs and the parametric FRFs (the FRFs of the linearized parametric robot model). Methods for estimating the nonparametric FRF from experimental data are analyzed with respect to bias, variance, and nonlinearities. In order to accurately estimate the nonparametric FRF, the experiments must be carefully designed. To minimize the uncertainty in the estimated parameters, the selection of optimal robot configurations/positions for the experiments is also part of the design. Different parameter estimators are compared in the thesis and experimental results show the usefulness of the proposed identification procedure. The identified nonlinear robot model gives a good global description of the dynamics in the frequency range of interest. The research work is also implemented and made easily available in a software tool for accurate estimation of nonparametric FRFs as well as parametric robot models.

In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.

Efficient radio resource management is of paramount importance for achieving the high bit rates targeted by the 3GPP for the 3GPP Long-Term Evolution. The radio air interface must be able to provide both high peak bit rates and acceptable cell-edge bit rates. This thesis therefore investigates three methods which try to combine the peak bit rate of a reuse-1 system with the cell-edge bit rate of a reuse-3 system in an OFDM-based downlink. These methods are soft frequency reuse, reuse partitioning and one variation of soft frequency reuse, reuse-1 with prioritization. In static simulations with one user per cell and a system load of 100 percent, a Shannon capacity gain of up to 18 percent at the 10th percentile is shown with reuse partitioning compared to a reuse-1 system. This gain comes coupled with a loss of only 5 percent at the median. Soft frequency reuse is also investigated statically and shows a 13 percent gain at the 10th percentile compared to a reuse-1 system. Having a lower 10th percentile gain than reuse partitioning, it also shows a slightly smaller loss of 4 percent at the median and a much smaller loss at the 90th percentile. Dynamic simulations with a traffic model and multiple users per cell offer a more realistic scenario and show that the proposed intercell interference management methods do not provide the same throughput gains in the dynamic case at low system loads. If interference is not an issue, interference coordination is still costly in terms of limiting bandwidth and/or decreasing the scheduling gain, but provides no significant interference reduction. At low system loads, reuse-1 is therefore the best scheme although interference coordination might prove necessary to provide edge-user throughput at high loads. For such purposes, soft frequency reuse is shown to be a potential candidate and although not investigated in a dynamic setting, reuse partitioning is believed to have similar performance. The traffic model chosen in this thesis only allows study of low system loads but at these loads, soft frequency reuse performs promisingly close to a reuse-1 system.

In this thesis, we investigate the use of adaptive antenna algorithms for OFDM systems to suppress interference in various channel conditions including narrowband and wideband interference, flat and frequency selective fading. We propose a novel frequency-domain beamformer, based on the linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm for OFDM systems to improve the performance of interference suppression in AWGN channel with narrowband interference, Rayleigh fast fading channel with phase distortion, and the multipath environment. To verify the merits of the frequency-domain beamformer, the effect due to narrowband interference and random phase distortion are investigated. Moreover, to improve the performance of adaptive beamforming algorithm, the frequency-domain linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm is proposed. Computer simulation results show that the proposed frequency-domain LCMCM-HLMS beamformer has good capability of interference supression in various environment, and can mitigate the phase distortion of channel. However, in the time-domain beamformer based on LMS [33], RLS ,LC-LMS and LC-FLS algorithm for OFDM systems, the performance may severely degraded under some situations. We will show that in terms of output SINR, beampatern, received signal constellation and mean square error (MSE), for narrowband interference suppression in AWGN channel, phase distortion in Rayleigh fast fading channel and the multipath environment.

<p>In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.</p>

Viscoelastic materials can today be found in a wide range of practical applications. In order to make efficient use of these materials in construction, it is of importance to know how they behave when subjected to dynamic load. Characterization of viscoelastic materials is therefore an important topic, that has received a lot of attention over the years. This thesis treats different methods for identifying the complex modulus of an viscoelastic material. The complex modulus is a frequency dependent material function, that describes the deformation of the material when subjected to stress. With knowledge of this and other material functions, it is possible to simulate and predict how the material behaves under different kinds of dynamic load. The complex modulus is often identified through wave propagation testing, where the viscoelastic material is subjected to some kind of load and the response then measured. Models describing the wave propagation in the setups are then needed. In order for the identification to be accurate, it is important that these models can describe the wave propagation in an adequate way. A statistical test quantity is therefore derived and used to evaluate the wave propagation models in this thesis. Both nonparametric and parametric identification of the complex modulus is considered in this thesis.  An important aspect of the identification is the accuracy of the estimates.  Theoretical expressions for the variance of the estimates are therefore derived, both for the nonparametric and the parametric identification. In order for the identification to be as accurate as possible, it is also important that the experimental data contains as much valuable information as possible. Different experimental conditions, such as sensor locations and choice of excitation, can influence the amount of information in the data. The procedure of determining optimal values for such design parameters is known as optimal experiment design. In this thesis, both optimal sensor locations and optimal excitation are considered.