<p>This master thesis has been performed at Sectra Communications AB in Linköping where they manufacture electronic encryption devices. In cryptology it is essential that an eavesdropper cannot find the plain text. To assure that a system is safe, all devices are thoroughly examined so that they don’t emit any secret information, so called Compromising Emanations (CE). This is done by comparing the secret signal with measured signals on the screen of an oscilloscope, a process that is very time consuming and furthermore, the risk of missing compromising emanations is high. The purpose of this thesis is to investigate the possibilities to let a computer do this job. Two methods for comparing the signals have been suggested and implemented; cross covariance and model estimation. In the cross covariance method, the cross covariance is calculated and its highest value determine how well the signals match. In the model estimation method, a number of ARX models are estimated, and if the best model is successful in explaining the output signal, it is assumed that there exists CE. </p><p>The work shows that both these methods are functional for solving the task, yet with a few limitations. Both methods announce CE for clock signals, which really aren’t compromising. The cross covariance method is limited only to find compromising emanations that look like the secret signal or certain frequently occurring non-linearities of it. The model estimation method is more general and detects CE for all linear systems, along with the known non-linearities. However, this method has a flaw: the time delay in the system must be known approximately. Further, the results show that the model estimation method is considerably more time consuming than the cross covariance method. The measurement is carried out with a computer communicating with oscilloscope and spectrum analyzer via the GPIB interface. The implementation has been done in LabView with calculation modules coded in C++.</p>

This master thesis has been performed at Sectra Communications AB in Linköping where they manufacture electronic encryption devices. In cryptology it is essential that an eavesdropper cannot find the plain text. To assure that a system is safe, all devices are thoroughly examined so that they don’t emit any secret information, so called Compromising Emanations (CE). This is done by comparing the secret signal with measured signals on the screen of an oscilloscope, a process that is very time consuming and furthermore, the risk of missing compromising emanations is high. The purpose of this thesis is to investigate the possibilities to let a computer do this job. Two methods for comparing the signals have been suggested and implemented; cross covariance and model estimation. In the cross covariance method, the cross covariance is calculated and its highest value determine how well the signals match. In the model estimation method, a number of ARX models are estimated, and if the best model is successful in explaining the output signal, it is assumed that there exists CE. The work shows that both these methods are functional for solving the task, yet with a few limitations. Both methods announce CE for clock signals, which really aren’t compromising. The cross covariance method is limited only to find compromising emanations that look like the secret signal or certain frequently occurring non-linearities of it. The model estimation method is more general and detects CE for all linear systems, along with the known non-linearities. However, this method has a flaw: the time delay in the system must be known approximately. Further, the results show that the model estimation method is considerably more time consuming than the cross covariance method. The measurement is carried out with a computer communicating with oscilloscope and spectrum analyzer via the GPIB interface. The implementation has been done in LabView with calculation modules coded in C++.

Cette thèse porte sur le problème d'identification des systèmes non linéaires sur la base des modèles blocs. Deux types de modèles sont considérés ici, ceux de type Hammerstein et ceux de type Wiener. La plupart des solutions antérieures ont été élaborées sous des hypothèses assez contraignantes concernant le sous-système non linéaire du modèle. Celui-ci a souvent été supposé lisse (voire polynomial), inversible et sans mémoire. Les travaux présentés dans cette thèse tentent de repousser ces limites. Dans le cas des systèmes de type Hammerstein, nous élaborons un schéma d'identification qui ne fait aucune hypothèse sur l'élément non linéaire, à l'exception du fait qu'il est sans mémoire et l¥-stable ; ce schéma estime parfaitement (du moins dans la cas idéal) les paramètres du sous-système dynamique linéaire et un nuage de points de la caractéristique de l'élément non linéaire. Ce schéma est ensuite adapté au cas où l'on connaît la structure de l'élément non linéaire ; à ce propos, les non-linéarités statiques affines par morceaux et discontinues jouissent d'une attention particulière. Nous terminons la partie consacrée à l'identification des systèmes de Hammerstein, en abordant le problème des systèmes impliquant un élément non linéaire à mémoire. Deux familles d'éléments de cette nature sont considérées : celle comprenant des éléments hystérétiques non saturés et celle des éléments hystérisis-relais. Le problème est appréhendé à l'aide d'un schéma d'identification dont on établit la consistance en présence de perturbations assimilables à un bruit blanc appliqué en sortie du système. <br /> La dernière partie du mémoire est centrée sur l'identification des systèmes de Wiener, dont l'élément non linéaire n'est pas supposé inversible. A cet effet, nous présentons deux schémas d'identification de type fréquentiel et établissons leur consistance dans les mêmes conditions que précédemment concernant les perturbations. L'exigence d'excitation persistante occupe une place centrale dans cette thèse. Pour procurer cette propriété aux différents schémas d'identifications proposés, il a été fait appel à une famille de signaux d'excitation de type impulsionnelle. Dans ce cadre, un lemme technique est élaboré précisant, pour les systèmes linéaires, le lien entre cette famille de signaux et la propriété d'excitation persistante. L'adaptation de ce lemme au cas des systèmes non linéaires est illustrée dans les différents schémas d'identification.

Anaerobic digestion, which is the process by which bacteria breakdown organic matter to produce biogas (renewable energy source) and digestate (biofertiliser) in the absence of oxygen, proves to be the ideal concept not only for sustainable energy provision but also for effective organic waste management. However, the production amount of biogas to keep up with the global demand is limited by the underperformance in the system implementing the AD process. This underperformance is due to the difficulty in obtaining and maintaining the optimal operating parameters/states for anaerobic bacteria to thrive with regards to attaining a specific critical population number, which results in maximising the biogas production. This problem continues to exist as a result of insufficient knowledge of the interactions between the operating parameters and bacterial community. In addition, the lack of sufficient knowledge of the composition of bacterial groups that varies with changes in the operating parameters such as temperature, substrate and retention time. Without sufficient knowledge of the overall impact of the physico-environmental operating parameters on anaerobic bacterial growth and composition, significant improvement of biogas production may be difficult to attain. In order to mitigate this problem, this study has presented a nonlinear multi-parameter system modelling of mesophilic AD. It utilised raw data sets generated from laboratory experimentation of the influence of four operating parameters, temperature, pH, mixing speed and pressure on biogas and methane production, signifying that this is a multiple input single output (MISO) system. Due to the nonlinear characteristics of the data, the nonlinear black-box modelling technique is applied. The modelling is performed in MATLAB through System Identification approach. Two nonlinear model structures, autoregressive with exogenous input (NARX) and Hammerstein-Wiener (NLHW) with different nonlinearity estimators and model orders are chosen by trial and error and utilised to estimate the models. The performance of the models is determined by comparing the simulated outputs of the estimated models and the output in the validation data. The approach is used to validate the estimated models by checking how well the simulated output of the models fits the measured output. The best models for biogas and methane production are chosen by comparing the outputs of the best NARX and NLHW models (each for biogas and methane production), and the validation data, as well as utilising the Akaike information criterion to measure the quality of each model relative to each of the other models. The NLHW models mhw2 and mhws2 are chosen for biogas and methane production, respectively. The identified NLHW models mhw2 and mhws2 represent the behaviour of the production of biogas and methane, respectively, from mesophilic AD. Among all the candidate models studied, the nonlinear models provide a superior reproduction of the experimental data over the whole analysed period. Furthermore, the models constructed in this study cannot be used for scale-up purpose because they are not able to satisfy the rules and criteria for applying dimensional analysis to scale-up.

The objective of this research work is to investigate, design and measurement of a digital predistortion linearizer that is able to compensate the dynamic nonlinear distortion of a High Power Amplifier (PA). The effectiveness of the proposed baseband predistorter (PD) on the performance of a WLAN OFDM transmitter utilizing a nonlinear PA with memory effect is observed and discussed. For this purpose, a 10W Class-A/B power amplifier with a gain of 22 dB, operated over the 3.5 GHz frequency band was designed and implemented. The proposed baseband PD is independent of the operating RF frequency and can be used in multiband applications. Its operation is based on the Hammerstein system, taking into account PA memory effect compensation, and demonstrates a noticeable improvement compared to memoryless predistorters. Different types of modelling procedures and linearizers were introduced and investigated, in which accurate behavioural models of Radio Frequency (RF) PAs exhibiting linear and nonlinear memory effects were presented and considered, based on the Wiener approach employing a linear parametric estimation technique. Three new linear methods of parameter estimation were investigated, with the aim of reducing the complexity of the required filtering process in linear memory compensation. Moreover, an improved wiener model is represented to include the nonlinear memory effect in the system. The validity of the PA modelling approaches and predistortion techniques for compensation of nonlinearities of a PA were verified by several tests and measurements. The approaches presented, based on the Wiener system, have the capacity to deal with the existing trade-off between accuracy and convergence speed compared to more computationally complex behavioural modelling algorithms considering memory effects, such as those based on Volterra series and Neural Networks. In addition, nonlinear and linear crosstalks introduced by the power amplifier nonlinear behaviour and antennas mutual coupling due to the compact size of a MIMO OFDM transmitter have been investigated.

This research work has made an effort to understand a novel line of radio frequency power amplifiers (RFPAs) that address initiatives for efficiency enhancement and linearity compensation to harmonize the fifth generation (5G) campaign. The objective is to enhance the performance of an orthogonal frequency division multiplexing-long term evolution (OFDM-LTE) transmitter by reducing the nonlinear distortion of the RFPA. The first part of this work explores the design and implementation of 15.5 W class AB RF power amplifier, adopting a balanced technique to stimulate efficiency enhancement and redeeming exhibition of excessive power in the transmitter. Consequently, this work goes beyond improving efficiency over a linear RF power amplifier design; in which a comprehensive investigation on the fundamental and harmonic components of class F RF power amplifier using a load-pull approach to realise an optimum load impedance and the matching network is presented. The frequency bandwidth for both amplifiers was allocated to operate in the 2.620-2.690 GHz of mobile LTE applications. The second part explores the development of the behavioural model for the class AB power amplifier. A particular novel, Hammerstein-Wiener based model is proposed to describe the dynamic nonlinear behaviour of the power amplifier. The RF power amplifier nonlinear distortion is approximated using a new linear parameter approximation approach. The first and second-order Hammerstein-Wiener using the Normalised Least Mean Square Error (NLMSE) algorithm is used with the aim of easing the complexity of filtering process during linear memory cancellation. Moreover, an enhanced adaptive Wiener model is proposed to explore the nonlinear memory effect in the system. The proposed approach is able to balance between convergence speed and high-level accuracy when compared with behavioural modelling algorithms that are more complex in computation. Finally, the adaptive predistorter technique is implemented and verified in the OFDM transceiver test-bed. The results were compared against the computed one from MATLAB simulation for OFDM and 5G modulation transmitters. The results have confirmed the reliability of the model and the effectiveness of the proposed predistorter. / Fundacão para a Ciência e a Tecnologia, Portugal, under European Union’s Horizon 2020 research and innovation programme ... grant agreement H2020-MSCA-ITN- 2016 SECRET-722424 I also acknowledge the role of the National Space Research and Development Agency (NASRDA) Sokoto State Government Petroleum Technology Trust Fund (PTDF)

L’amélioration du contraste des images échographiques occupe une place importante en imagerie ultrasonore médicale puisque la qualité des images impacte directement le diagnostic médical. Les imageries de contraste sous et ultra-harmoniques sont deux techniques permettant de produire des images à fort contraste. Le développement de techniques de filtrage, permettant de mieux extraire les composantes sous et ultra-harmoniques présentes dans les signaux renvoyés par les produits de contraste ultrasonore, a pour conséquence d’améliorer encore plus le contraste des images. Les modèles non linéaires dits « boîtes noires » du type Volterra, Hammerstein, et Wiener, sont souvent utilisés pour identifier et modéliser les systèmes non linéaires tels que les produits de contraste ultrasonore. Ces modèles, bien que très bien adaptés pour modéliser les composantes harmoniques entières, ne le sont plus en présence de sous et ultra-harmoniques. Dans les années 2000, une méthode permettant la modélisation de sous et ultra-harmoniques en utilisant un modèle de Volterra à plusieurs entrées (Multiple Input Single Output : MISO) a été développée. Pourtant, bien que cette méthode soit complètement originale dans le domaine considéré, les points clés qui la sous-tendent ne sont pas clairement identifiés. C’est en identifiant clairement les points clés de la méthode existante que nous pouvons la généraliser et proposer plusieurs nouveaux paradigmes pour la modélisation et l’extraction de sous et ultra-harmoniques. Nous proposons alors des alternatives beaucoup plus simples du type mono-entrée mono-sortie (Single Input Single Output : SISO). En modulant en fréquence l’entrée du système, nous avons pu ainsi identifier les réponses impulsionnelles des différents canaux du modèle de Hammerstein généralisé. À partir de ce cadre général, nous avons aussi proposé de nouvelles approches pour réduire la complexité du modèle de Volterra. / Contrast enhancement of echographic images occupies an important place in medical ultrasound imaging, since the quality of images has a direct impact on medical diagnosis. Sub and ultraharmonic contrast imaging are two imaging techniques that provide high contrast images. Developing filtering techniques, that allow better extraction of sub and ultra-harmonic components present in the echo backscattered by the ultrasound contrast agents, results in additional improvement of the contrast. Non linear models known as “black box” models, like Volterra model, Hammerstein model, and Wiener model are usually used to identify and model non linear systems such ultrasound contrast agents. Although these models are well suited to model integer harmonic components, they are not suitable in the presence of sub and ultra-harmonic components. In the 2000s, A method that allows the modeling of sub and ultra-harmonic components, using a multi inputs single output Volterra model (MISO) has been developed. Although this method was original in the considered domain, the key points underlying this method are not clearly identified. By clearly identifying the key points of the existing method, we can generalize it and propose new paradigms for modeling and extraction of sub and ultra-harmonics. We propose much simpler alternatives based on single input single output (SISO) models. By modulating the input frequency of the system, we can also identify the different impulse responses of the different channels of the generalized Hammerstein model. From this general framework, we also propose new approaches to reduce the complexity of Volterra model.

Une large classe de systèmes physiques peut être représentée à l'aide du modèle de Volterra. Il a notamment été montré que tout système non-linéaire, invariant dans le temps et à mémoire évanouissante peut être représenté par un modèle de Volterra de mémoire et d¤ordre finis. Ce modèle est donc particulièrement attrayant pour les besoins de modélisation et d'identification de systèmes non-linéaires. Un des atouts majeurs du modèle de Volterra est la linéarité par rapport à ses paramètres, c¤est à dire les coefficients de ses noyaux. Cette caractéristique permet d'étendre à ce modèle certains résultats établis pour l'identification des modèles linéaires. Il est à noter que le modèle de Volterra peut, par ailleurs, être vu comme une extension naturelle de la notion de réponse impulsionnelle des systèmes linéaires aux systèmes non-linéaires. Toutefois, certaines limitations sont à circonvenir: un nombre de paramètres qui peut être très élevé et un mauvais conditionnement de la matrice des moments de l'entrée intervenant dans l¤estimation du modèle au sens de l¤erreur quadratique moyenne minimale (EQMM). Il est à noter que ce mauvais conditionnement est aussi à l¤origine de la lenteur de convergence des algorithmes adaptatifs de type LMS (Least Mean Squares). Cette thèse traite principalement de ces deux questions. Les solutions apportées sont essentiellement basées sur la notion d'orthogonalité. D'une part, l'orthogonalité est envisagée vis à vis de la structure du modèle en développant les noyaux de Volterra sur une base orthogonale de fonctions rationnelles. Ce développement est d'autant plus parcimonieux que la base est bien choisie. Pour ce faire, nous avons développé de nouveaux outils d'optimisation des bases de Laguerre et BFOR (Base de Fonctions Orthonormales Rationnelles) pour la représentation des noyaux de Volterra. D'autre part, l'orthogonalité est envisagée en rapport avec les signaux d'entrée. En exploitant les propriétés statistiques de l¤entrée, des bases de polynômes orthogonaux multivariables ont été construites. Les paramètres du modèle de Volterra développé sur de telles bases sont alors estimés sans aucune inversion matricielle, ce qui simplifie significativement l¤estimation paramétrique au sens EQMM. L¤orthogonalisation des signaux d¤entrée a aussi été envisagée via une procédure de Gram-Schmidt. Dans un contexte adaptatif, il en résulte une accélération de la convergence des algorithmes de type LMS sans un surcoût de calcul excessif. Certains systèmes physiques peuvent être représentés à l¤aide d¤un modèle de Volterra simplifié, à faible complexité paramétrique, tel que le modèle de Hammerstein et celui de Wiener. C¤est le cas d¤un canal de communication représentant l'accès à un réseau sans fil via une fibre optique. Nous montrons notamment que les liaisons montante et descendante de ce canal peuvent respectivement être représentées par un modèle de Wiener et par un modèle de Hammerstein. Dans le cas mono-capteur, en utilisant un précodage de la séquence d'entrée, nous développons une solution permettant de réaliser l'estimation conjointe du canal de transmission et des symboles transmis de manière semiaveugle. Il est à noter que, dans le cas de la liaison montante, une configuration multi-capteurs peut aussi être envisagée. Pour une telle configuration, grâce à un précodage spécifique de la séquence d¤entrée, nous exploitons la diversité spatiale introduite par les capteurs et la diversité temporelle de sorte à obtenir une représentation tensorielle du signal reçu. En appliquant la technique de décomposition tensorielle dite PARAFAC, nous réalisons l'estimation conjointe du canal et des symboles émis de manière aveugle. Mots clés: Modélisation, Identification, Bases orthogonales, Base de Laguerre, Base de fonctions orthonormales rationnelles, Polynômes orthogonaux, Optimisation de pôles, Réduction de complexité, Egalisation, Modèle de Volterra, Modèle de Wiener, Modèle de Hammerstein, Décomposition PARAFAC.

Orientador: Furio Damiani / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-11T03:06:29Z (GMT). No. of bitstreams: 1 Werneck_NicolauLeal_M.pdf: 1556046 bytes, checksum: 677310006250588d7e6a0fb0eedfc170 (MD5) Previous issue date: 2007 / Resumo: Existem diversos problemas ligados à análise de sinais musicais que podem se beneficiar de um conhecimento mais detalhado da estrutura dos sinais gerados pelos diferentes instrumentos. Entre eles se destaca a compressão de sinais baseada em áudio estruturado, onde o codificador determina a partir de um sinal parâmetros para reproduzí-lo com um sintetizador inspirado em modelos físicos dos instrumentos. Para realizar este tipo de análise e síntese é necessário conhecermos as características físicas dos instrumentos e dos sinais produzidos. Este conhecimento é ainda útil para auxiliar no desenvolvimento de instrumentos e outros equipamentos utilizados por músicos para obter o timbre desejado. Esta dissertação apresenta experimentos realizados com uma guitarra elétrica para revelar a dinâmica não-linear de suas cordas e seu filtro linear associado, comparação de sinais gravados com resultados esperados por modelos matemáticos da forma de onda, e ainda uma proposta de uma potencial técnica para a medição de parâmetros para um modelo matemático de um circuito de distorção musical, além de uma maneira de se mapear um par destes parâmetros para um espaço de maior significado psicoacústico / Resumo: Existem diversos problemas ligados à análise de sinais musicais que podem se beneficiar de um conhecimento mais detalhado da estrutura dos sinais gerados pelos diferentes instrumentos. Entre eles se destaca a compressão de sinais baseada em áudio estruturado, onde o codificador determina a partir de um sinal parâmetros para reproduzí-lo com um sintetizador inspirado em modelos físicos dos instrumentos. Para realizar este tipo de análise e síntese é necessário conhecermos as características físicas dos instrumentos e dos sinais produzidos. Este conhecimento é ainda útil para auxiliar no desenvolvimento de instrumentos e outros equipamentos utilizados por músicos para obter o timbre desejado. Esta dissertação apresenta experimentos realizados com uma guitarra elétrica para revelar a dinâmica não-linear de suas cordas e seu filtro linear associado, comparação de sinais gravados com resultados esperados por modelos matemáticos da forma de onda, e ainda uma proposta de uma potencial técnica para a medição de parâmetros para um modelo matemático de um circuito de distorção musical, além de uma maneira de se mapear um par destes parâmetros para um espaço de maior significado psicoacústico / Mestrado / Eletrônica, Microeletrônica e Optoeletrônica / Mestre em Engenharia Elétrica

This thesis deals with a simulation of analogue audio effects using the nonlinear models that replace the analogue nonlinear devices in discrete domain. The thesis describes Volterra system model and simplified Volterra system model that can be realized in two ways, either Wiener model, or Hammerstein model. The method for the analysis and modeling of audio and acoustic nonlinear systems is presented in this thesis. This method allows through knowledge of the input swept-sine signal and the response of the analogue nonlinear system to the input signal to determine the coefficients of the discrete nonlinear system. This allows simulating the analogue nonlinear system in discrete domain. The method was first tested and then used successfully for simulation of the analogue nonlinear system in discrete domain. Concretely, it was simulated a musical guitar effect of the type of distortion. Last part of this thesis is devoted a description of VST technology and an implementation of VST plug-in module, which realizations Hammerstein model.