Thesis deals with the spectral analysis of 3D surface topography. The surface is described by a random function. Theoretical starting points necessary for right introduction and understanding of basic notions used within the framework of the surface topography spectral analysis are exactly formulated. They lie in the theory of random functions, the theory of the Fourier transform and the theory of signal processing. The notions mentioned are: the areal power spectral density (APSD) of a surface, the radial power spectral density (RPSD) of a surface and the angular power spectrum density (AnPSD) of a surface. These notions are introduced in their discrete form and generalized for the two-dimensional case. The thorough discussion of possible mistakes and inaccuracies which can be done during the application of spectral analysis techniques in a surface topography evaluation is performed. The procedure of APSD estimation by means of the periodogram method combined with the Welch´s method is discussed. The principle and capabilities of the optical profilometer MicroProf?FRT used for the surface topography measurement are described. Our original computer program computing APSD, RPSD and AnPSD is described too. The 3D spectral analyses is applied to surfaces generated by AWJ cutting, plane grinding and casting. We have focused our attention to AWJ cut surfaces, 3D spectral analyses of which brings new still unpublished opportunities of the surfaces topography evaluation. The influence of technological parameters on these AWJ cut surfaces topography is studied. The conclusion of the study is that results of the spectral analyses of these surfaces topography strongly depend on the technological conditions of the surfaces generation. An original procedure of the ASPD shape evaluation within individual regions of its frequency domain is mentioned. This procedure brings new substantial knowledge concerning the topography of surfaces. Results obtained from surfaces generated by plane grinding and casting are presented like examples of results from non-isotropic and isotropic surfaces.

No description available.

O Ruído de Baixa Frequência (LFN), tais como o ruído flicker e o Random Telegraph Noise (RTN), são limitadores de performance em muitos circuitos analógicos e digitais. Para transistores diminutos, a densidade espectral de potência do ruído pode variar muitas ordens de grandeza, impondo uma séria limitação na performance do circuito e também em sua confiabilidade. Nesta tese, nós propomos um novo modelo de RTN estatístico para descrever o ruído de baixa frequência em MOSFETs. Utilizando o modelo proposto, pode-se explicar e calcular o valor esperado e a variabilidade do ruído em função das polarizações, geometrias e dos parâmetros físicos do transistor. O modelo é validado através de inúmeros resultados experimentais para dispositivos com canais tipo n e p, e para diferentes tecnologias CMOS. É demonstrado que a estatística do ruído LFN dos dispositivos de canal tipo n e p podem ser descritos através do mesmo mecanismo. Através dos nossos resultados e do nosso modelo, nós mostramos que a densidade de armadilhas dos transistores de canal tipo p é fortemente dependente do nível de Fermi, enquanto para o transistor de tipo n a densidade de armadilhas pode ser considerada constante na energia. Também é mostrado e explicado, através do nosso modelo, o impacto do implante de halo nas estatísticas do ruído. Utilizando o modelo demonstra-se porque a variabilidade, denotado por σ[log(SId)], do RTN/LFN não segue uma dependência 1/√área; e fica demonstrado que o ruído, e sua variabilidade, encontrado em nossas medidas pode ser modelado utilizando parâmetros físicos. Além disso, o modelo proposto pode ser utilizado para calcular o percentil do ruído, o qual pode ser utilizado para prever ou alcançar certo rendimento do circuito. / Low Frequency Noise (LFN) and Random Telegraph Noise (RTN) are performance limiters in many analog and digital circuits. For small area devices, the noise power spectral density can easily vary by many orders of magnitude, imposing serious threat on circuit performance and possibly reliability. In this thesis, we propose a new RTN model to describe the statistics of the low frequency noise in MOSFETs. Using the proposed model, we can explain and calculate the Expected value and Variability of the noise as function of devices’ biases, geometry and physical parameters. The model is validated through numerous experimental results for n-channel and p-channel devices from different CMOS technology nodes. We show that the LFN statistics of n-channel and p-channel MOSFETs can be described by the same mechanism. From our results and model, we show that the trap density of the p-channel device is a strongly varying function of the Fermi level, whereas for the n-channel the trap density can be considered constant. We also show and explain, using the proposed model, the impact of the halo-implanted regions on the statistics of the noise. Using this model, we clarify why the variability, denoted by σ[log(SId)], of RTN/LFN doesn't follow a 1/√area dependence; and we demonstrate that the noise, and its variability, found in our measurements can be modeled using reasonable physical quantities. Moreover, the proposed model can be used to calculate the percentile quantity of the noise, which can be used to predict or to achieve certain circuit yield.

No description available.

Sensitive devices are affected by extreme vibration excitations during operation so require isolation from high levels of vibration excitations. When these excitation characteristics of the devices are well known, the vibration isolation can be achieved accurately. However, it is possible to have expected profile information of the excitations with respect to frequency. Therefore, it is practical and useful to implement this information in the design process for vibration isolation. In this thesis, passive vibration isolation technique is examined and a computer code is developed which would assist the isolator selection process. Several sample cases in six degree of freedom are designed for a sample excitation and for sample assumptions defined for an inertial measurement unit. Different optimization methods for design optimizations are initially compared and then different designs are arranged according to the optimization results using isolators from catalogues for these sample cases. In the next step, the probable designs are compared according to their isolator characteristics. Finally, one of these designs are selected for each case, taking into account both the probable location deviations and property deviations of isolators.

In a large number of applications arising in various fields of study, time series are approximated using linear MMSE estimates. Such approximations include finite order moving average and autoregressive approximations as well as the causal Wiener filter. In this dissertation, we study two topics related to the estimation of wide sense stationary (WSS) time series using linear MMSE estimates. In the first part of this dissertation, we study the asymptotic behaviour of autoregressive (AR) and moving average (MA) approximations. Our objective is to investigate how faithfully such approximations replicate the original sequence, as the model order as well as the number of samples approach infinity. We consider two aspects: convergence of spectral density of MA and AR approximations when the covariances are known and when they are estimated. Under certain mild conditions on the spectral density and the covariance sequence, it is shown that the spectral densities of both approximations converge in L2 as the order of approximation increases. It is also shown that the spectral density of AR approximations converges at the origin under the same conditions. Under additional regularity assumptions, we show that similar results hold for approximations from empirical covariance estimates. In the second part of this dissertation, we address the problem of detecting interdependence relations within a group of time series. Ideally, in order to infer the complete interdependence structure of a complex system, dynamic behaviour of all the processes involved should be considered simultaneously. However, for large systems, use of such a method may be infeasible and computationally intensive, and pairwise estimation techniques may be used to obtain sub-optimal results. Here, we investigate the problem of determining Granger-causality in an interdependent group of jointly WSS time series by using pairwise causal Wiener filters. Analytical results are presented, along with simulations that compare the performance of a method based on finite impulse response Wiener filters to another using directed information, a tool widely used in literature. The problem is studied in the context of cyclostationary processes as well. Finally, a new technique is proposed that allows the determination of causal connections under certain sparsity conditions.

Abstract Cognitive Radio (CR) improves the efficiency of spectrum utilization by allowing non- licensed users to utilize bands when not occupied by licensed users. In this thesis, we address several challenges currently limiting the wide use of cognitive radios. These challenges include identification of unoccupied bands, energy consumption and other technical challenges. Improved accuracy edge detection techniques are developed for CR to mitigate both noise and estimation error variance effects. Next, a reduced complexity Simplified DFT (SDFT) is proposed for use in CR. Then, a sub-Nyquist rate A to D converter is introduced to reduce energy consumption. Finally, a novel multi-resolution PSD estimation based on expectation-maximization algorithm is introduced that can obtain a more accurate PSD within a specified sensing time.

Cette thèse présente une étude expérimentale et numérique d'essais de chute libre et de vibrations aléatoires d'emballages en carton ondulé contenant différents calages en mousse. Un modèle d'homogénéisation efficace pour le carton ondulé a été développé. Dans ce modèle homogénéisé, le carton ondulé est représenté par une plaque 2D. Au lieu d'utiliser une loi de comportement locale (reliant les déformations aux contraintes) à chaque point d'intégration, l'homogénéisation conduit aux rigidités globales (reliant les déformations généralisées aux forces résultantes) pour la plaque équivalente homogène. Ce modèle a été implémenté dans le logiciel Abaqus. Le comportement de la mousse a été déterminé expérimentalement et modélisé avec un modèle de mousse déformable d'Abaqus. Les emballages sont soumis à des tests de chute libre d'une hauteur donnée sur un sol rigide et des essais de vibrations aléatoires type bruit blanc sur table vibrante. Les résultats numériques obtenus en utilisant la simulation avec le modèle homogénéisé concordent bien avec les résultats expérimentaux. Nous avons également montré que la contribution de la caisse en carton ondulé à la réponse au choc et à la vibration aléatoire ne pouvait pas être négligée dans la conception des calages. / This thesis presents experimental and numerical studies of drop tests random vibrations of corrugated cardboard packaging containing different foam cushions. An efficient homogenization model for the corrugated cardboard has been developed. In this homogenized model, the corrugated cardboard is represented by a 2D plate. Instead of using a local constitutive law (relating the strains to the stresses) at each material point, the homogenization leads to global rigidities (relating the generalized strains to the resultant forces) for the equivalent homogeneous plate. This model was implemented into the FE software Abaqus. The foam behaviour was experimentally determined and modelled using a crushable foam model of Abaqus. The packages are tested in free fall from a given height on a rigid floor and submitted to white noise random vibrations. The numerical results obtained using the FE simulation with the homogenized model agree well with the experimental results. We have also shown that the contribution of the corrugated cardboard box to the shock and random vibration responses could not be neglected in the design of cushioning package.

The operating motion of a ground compactor uses high power vibrations to improve mechanical properties of a compacted ground. This motion gives a good base for the vibration analysis with an aid of Signal Processing. In this thesis, the motion of a bottom plate in a compactor is of the main interest. The thesis concerns usage of two main spectral analyzing tools, Power Spectrum estimators and Power Spectral Density estimators, presenting advantages and disadvantages in the application of a vibration analysis. Moreover, an influence of two window applications, a Flattop window, and a Hanning window, is described in relation to both analyzing approaches. The results present problems that occur when a vibration with a present modulated frequency is analyzed and how a Power Spectral Density estimator arise in a more consistent estimate over analyzed vibration spectrum. What is more, an Ordinary Deflection Shapes for a simplified bottom plate model, under different motion excitations, are presented at the end of this thesis, giving a better view of the operational motion of an analyzed system.

O Ruído de Baixa Frequência (LFN), tais como o ruído flicker e o Random Telegraph Noise (RTN), são limitadores de performance em muitos circuitos analógicos e digitais. Para transistores diminutos, a densidade espectral de potência do ruído pode variar muitas ordens de grandeza, impondo uma séria limitação na performance do circuito e também em sua confiabilidade. Nesta tese, nós propomos um novo modelo de RTN estatístico para descrever o ruído de baixa frequência em MOSFETs. Utilizando o modelo proposto, pode-se explicar e calcular o valor esperado e a variabilidade do ruído em função das polarizações, geometrias e dos parâmetros físicos do transistor. O modelo é validado através de inúmeros resultados experimentais para dispositivos com canais tipo n e p, e para diferentes tecnologias CMOS. É demonstrado que a estatística do ruído LFN dos dispositivos de canal tipo n e p podem ser descritos através do mesmo mecanismo. Através dos nossos resultados e do nosso modelo, nós mostramos que a densidade de armadilhas dos transistores de canal tipo p é fortemente dependente do nível de Fermi, enquanto para o transistor de tipo n a densidade de armadilhas pode ser considerada constante na energia. Também é mostrado e explicado, através do nosso modelo, o impacto do implante de halo nas estatísticas do ruído. Utilizando o modelo demonstra-se porque a variabilidade, denotado por σ[log(SId)], do RTN/LFN não segue uma dependência 1/√área; e fica demonstrado que o ruído, e sua variabilidade, encontrado em nossas medidas pode ser modelado utilizando parâmetros físicos. Além disso, o modelo proposto pode ser utilizado para calcular o percentil do ruído, o qual pode ser utilizado para prever ou alcançar certo rendimento do circuito. / Low Frequency Noise (LFN) and Random Telegraph Noise (RTN) are performance limiters in many analog and digital circuits. For small area devices, the noise power spectral density can easily vary by many orders of magnitude, imposing serious threat on circuit performance and possibly reliability. In this thesis, we propose a new RTN model to describe the statistics of the low frequency noise in MOSFETs. Using the proposed model, we can explain and calculate the Expected value and Variability of the noise as function of devices’ biases, geometry and physical parameters. The model is validated through numerous experimental results for n-channel and p-channel devices from different CMOS technology nodes. We show that the LFN statistics of n-channel and p-channel MOSFETs can be described by the same mechanism. From our results and model, we show that the trap density of the p-channel device is a strongly varying function of the Fermi level, whereas for the n-channel the trap density can be considered constant. We also show and explain, using the proposed model, the impact of the halo-implanted regions on the statistics of the noise. Using this model, we clarify why the variability, denoted by σ[log(SId)], of RTN/LFN doesn't follow a 1/√area dependence; and we demonstrate that the noise, and its variability, found in our measurements can be modeled using reasonable physical quantities. Moreover, the proposed model can be used to calculate the percentile quantity of the noise, which can be used to predict or to achieve certain circuit yield.