60 research outputs found
A simple algorithm for stable order reduction of z-domain Laguerre models
International audienceDiscrete-time Laguerre series are a well known and efficient tool in system identification and modeling. This paper presents a simple solution for stable and accurate order reduction of systems described by a Laguerre model
Identificação e controle de processos via desenvolvimentos em séries ortonormais. Parte A: identificação
In this paper, an overview about the identification of dynamic systems using orthonormal basis function models, such as those based on Laguerre and Kautz functions, is presented. The mathematical foundations of these models as well as their advantages and limitations are discussed within the contexts of linear, robust, and nonlinear identification. The discussions comprise a broad bibliographical survey on the subject and a comparative analysis involving some specific model realizations, namely, linear, Volterra, fuzzy, and neural models within the orthonormal basis function framework. Theoretical and practical issues regarding the identification of these models are also presented and illustrated by means of two case studies related to a polymerization process.O presente artigo apresenta uma visão geral do estado da arte na área de identificação de sistemas utilizando modelos dinâmicos com estrutura desenvolvida através de bases de funções ortonormais, como as funções de Laguerre, Kautz ou funções ortonormais generalizadas. Discute-se as vantagens e possíveis limitações desse tipo de estrutura bem como os fundamentos matemáticos dos modelos correspondentes nos contextos de identificação linear, linear com incertezas paramétricas (identificação robusta) e não linear, incluindo uma revisão bibliográfica abrangente sobre o tema. Diferentes realizações de modelos com funções de base ortonormal, a saber, modelos lineares, de Volterra, fuzzy e neurais, são detalhadas e discutidas comparativamente em termos de capacidade de representação, parcimônia, complexidade de projeto e interpretabilidade. Aspectos práticos da identificação desses modelos são também apresentados e ilustrados através de dois casos de estudo envolvendo um processo simulado de polimerização isotérmica.301321Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq
Modelling and Analysis of Drosophila Early Visual System A Systems Engineering Approach
Over the past century or so Drosophila has been established as an ideal model organism to
study, among other things, neural computation and in particular sensory processing. In this
respect there are many features that make Drosophila an ideal model organism, especially
the fact that it offers a vast amount of genetic and experimental tools for manipulating
and interrogating neural circuits. Whilst comprehensive models of sensory processing in
Drosophila are not yet available, considerable progress has been made in recent years in
modelling the early stages of sensory processing. When it comes to visual processing,
accurate empirical and biophysical models of the R1-R6 photoreceptors were developed
and used to characterize nonlinear processing at photoreceptor level and to demonstrate that
R1-R6 photoreceptors encode phase congruency.
A limitation of the latest photoreceptor models is that these do not account explicitly for
the modulation of photoreceptor responses by the network of interneurones hosted in the
lamina. As a consequence, these models cannot describe in a unifying way the photoreceptor
response in the absence of the feedback from the downstream neurons and thus cannot be
used to elucidate the role of interneurones in photoreceptor adaptation.
In this thesis, electrophysiological photoreceptor recordings acquired in-vivo from wild-
type and histamine defficient mutant fruit flies are used to develop and validate new com-
prehensive models of R1-R6 photoreceptors, which not only predict the response of these
photoreceptors in wild-type and mutant fruit flies, over the entire environmental range of
light intensities but also characterize explicitly the contribution of lamina neurons to photore-
ceptor adaptation. As a consequence, the new models provide suitable building blocks for
assembling a complete model of the retina which takes into account the true connectivity
between photoreceptors and downstream interneurones.
A recent study has demonstrated that R1-R6 photoreceptors employ nonlinear processing
to selectively encode and enhance temporal phase congruency. It has been suggested that
this processing strategy achieves an optimal trade-off between the two competing goals of
minimizing distortion in decoding behaviourally relevant stimuli features and minimizing
the information rate, which ultimately enables more efficient downstream processing of
spatio-temporal visual stimuli for edge and motion detection.Using rigorous information theoretic tools, this thesis derives and analyzes the rate-distortion characteristics associated with the linear and nonlinear transformations performed
by photoreceptors on a stimulus generated by a signal source with a well defined distribution
Nonlinear models and algorithms for RF systems digital calibration
Focusing on the receiving side of a communication system, the current trend in pushing the digital domain ever more closer to the antenna sets heavy constraints on the accuracy and linearity of the analog front-end and the conversion devices. Moreover, mixed-signal implementations of Systems-on-Chip using nanoscale CMOS processes result in an overall poorer analog performance and a reduced yield. To cope with the impairments of the low performance analog section in this "dirty RF" scenario, two solutions exist: designing more complex analog processing architectures or to identify the errors and correct them in the digital domain using DSP algorithms. In the latter, constraints in the analog circuits' precision can be offloaded to a digital signal processor.
This thesis aims at the development of a methodology for the analysis, the modeling and the compensation of the analog impairments arising in different stages of a receiving chain using digital calibration techniques.
Both single and multiple channel architectures are addressed exploiting the capability of the calibration algorithm to homogenize all the channels' responses of a multi-channel system in addition to the compensation of nonlinearities in each response. The systems targeted for the application of digital post compensation are a pipeline ADC, a digital-IF sub-sampling receiver and a 4-channel TI-ADC.
The research focuses on post distortion methods using nonlinear dynamic models to approximate the post-inverse of the nonlinear system and to correct the distortions arising from static and dynamic errors. Volterra model is used due to its general approximation capabilities for the compensation of nonlinear systems with memory. Digital calibration is applied to a Sample and Hold and to a pipeline ADC simulated in the 45nm process, demonstrating high linearity improvement even with incomplete settling errors enabling the use of faster clock speeds.
An extended model based on the baseband Volterra series is proposed and applied to the compensation of a digital-IF sub-sampling receiver. This architecture envisages frequency selectivity carried out at IF by an active band-pass CMOS filter causing in-band and out-of-band nonlinear distortions. The improved performance of the proposed model is demonstrated with circuital simulations of a 10th-order band pass filter, realized using a five-stage Gm-C Biquad cascade, and validated using out-of-sample sinusoidal and QAM signals. The same technique is extended to an array receiver with mismatched channels' responses showing that digital calibration can compensate the loss of directivity and enhance the overall system SFDR.
An iterative backward pruning is applied to the Volterra models showing that complexity can be reduced without impacting linearity, obtaining state-of-the-art accuracy/complexity performance.
Calibration of Time-Interleaved ADCs, widely used in RF-to-digital wideband receivers, is carried out developing ad hoc models because the steep discontinuities generated by the imperfect canceling of aliasing would require a huge number of terms in a polynomial approximation. A closed-form solution is derived for a 4-channel TI-ADC affected by gain errors and timing skews solving the perfect reconstruction equations. A background calibration technique is presented based on cyclo-stationary filter banks architecture. Convergence speed and accuracy of the recursive algorithm are discussed and complexity reduction techniques are applied
Design of Neural Network Filters
Emnet for n rv rende licentiatafhandling er design af neurale netv rks ltre. Filtre baseret pa neurale netv rk kan ses som udvidelser af det klassiske line re adaptive l-ter rettet mod modellering af uline re sammenh nge. Hovedv gten l gges pa en neural netv rks implementering af den ikke-rekursive, uline re adaptive model med additiv st j. Formalet er at klarl gge en r kke faser forbundet med design af neural netv rks arkitekturer med henblik pa at udf re forskellige \black-box " modellerings opgaver sa som: System identi kation, invers modellering og pr diktion af tidsserier. De v senligste bidrag omfatter: Formulering af en neural netv rks baseret kanonisk lter repr sentation, der danner baggrund for udvikling af et arkitektur klassi kationssystem. I hovedsagen drejer det sig om en skelnen mellem globale og lokale modeller. Dette leder til at en r kke kendte neurale netv rks arkitekturer kan klassi ceres, og yderligere abnes der mulighed for udvikling af helt nye strukturer. I denne sammenh ng ndes en gennemgang af en r kke velkendte arkitekturer. I s rdeleshed l gges der v gt pa behandlingen af multi-lags perceptron neural netv rket
Contributions à l’analyse des systèmes en réseau
La dernière décennie a vu l’émergence des travaux autour des systèmes dynamiques interconnectés (systèmes en réseaux ou systèmes cyberphysiques). Dans cette habilitation à diriger des recherches, je donne un aperçu des contributions qui ont été les miennes durant la dernière décennie sur : l’analyse des systèmes en réseaux (problème de consensus, observabilité et application à la préservation de la vie privée), le traitement des données de grandes dimensions (analyse tensorielle pour l’identification des systèmes non-linéaires, décomposition distribuée de tenseurs de grandes dimensions), et l’application à la mobilité intelligente (navigation en milieu urbain, prédiction et estimation de trafic, estimation d’attitude pour la navigation pédestre). Une prospective est ensuite développée autour de la sécurité des systèmes en réseaux, en se basant sur la théorie des systèmes, et sur l’analyse des données de grandes dimensions organisées dans des tenseurs de données avec des applications sur la mobilité intelligente
Modelação comportamental e pré-distorção digital de transmissores de rádio-frequência
Doutoramento em Engenharia ElectrotécnicaNos atuais sistemas de telecomunicações, os transmissores de rádio-frequência são desenvolvidos tendo maioritariamente em conta a eficiência da conversão da potência fornecida da fonte em potência de rádio-frequência. Este tipo de desenho resulta em amplificadores de potência com características de transmissão não-lineares, que distorcem severamente o envelope de informação no processo de amplificação, gerando distorção fora da banda. Para corrigir este problema utiliza-se um processo de compensação não linear, sendo que a pré-distorção digital se tem favorecido pela sua flexibilidade e precisão. Este método é tipicamente aplicado de uma forma cega, por força bruta até se obter a compensação desejada. No entanto, quando o método se mostra ineficaz, como se verificou em amplificadores de potência baseados em transístores de nitreto de gálio, é difícil saber o que modificar nos sistemas para os tornar de novo úteis. De forma a compreender e desenhar sistemas de pré-distorção digital robustos é necessário, por um lado, perceber o comportamento dos amplificadores de rádio-frequência, por outro, perceber as limitações e relações entre os modelos digitais e o comportamento real do amplificador. Nesse sentido, esta tese explora e descreve estas relações de forma a suportar a escolha de modelos de pré-distorção, desenvolve novos modelos baseados no comportamento dos transístores, e propõe métodos de caracterização para os amplificadores de RF.In current telecommunication systems, the main concern when developing the radio frequency transmitter is power efficiency. This type of design generally leads to a highly nonlinear transmission characteristic, mainly due to the radio frequency power amplifier. This nonlinear transmission severely distorts the information envelope, leading to spectral regrowth, out-of-band distortion. To correct this problem a nonlinear compensation process is employed. For this application, digital predistortion is generally favored for its flexibility and accuracy. Digital predistortion is mostly applied in a blind manner, using brute force until the desired compensation is achieved. Because of this, when the method fails, as it has in gallium nitride based power amplifiers, it is difficult to modify the system to achieve the desired results. To understand and design robust predistortion systems, it is both necessary to have knowledge of the power amplifiers’ behavior, on one hand, and understand the limitations and relations between the digital models and these behaviors, on the other. To do this, this thesis explores and describes these relationships, granting support to the digital predistortion model choice, it further develops new predistortion models based on the physics of the transistors’ behaviors, and it proposes methods for the characterization of radio frequency power amplifiers
Development of a Simulation based Powertrain Design Framework for Evaluation of Transient Soot Emissions from Diesel Engine Vehicles.
This dissertation presents the development of a modeling and simulation framework
for diesel engine vehicles to enable soot emissions as a constraint in powertrain design
and control. To this end, numerically efficient models for predicting temporallyresolved
transient soot emissions are identified in the form of a third-order dual-input
single-output (DISO) Volterra series from transient soot data recorded by integrating
real-time (RT) vehicle level models in Engine-in-the-loop (EIL) experiments. It is
shown that the prediction accuracy of transient soot significantly improves over the
steady-state maps, while the model remains computationally efficient for systemslevel
work.
The evaluation of powertrain design also requires a systematic procedure for dealing
with the issue that drivers potentially adapt their driving styles to a given design. In
order to evaluate the implications of different powertrain design changes on transient
soot production it is essential to compare these design changes on a consistent basis.
This problem is explored in the context of longitudinal motion of a vehicle following a standard drive-cycle repeatedly. This dissertation develops a proportional-derivative
(PD) type iterative learning based algorithm to synthesize driver actuator inputs that
seek to minimize soot emissions using the Volterra series based transient soot models.
The solution is compared to the one obtained using linear programming. Results
show that about 19% reduction in total soot can be achieved for the powertrain design
considered in about 40 iterations.
The two contributions of this dissertation: development of computationally efficient
system level transient soot models and the synthesis of driver inputs via iterative
learning for reducing soot, both contribute to improving the art of modeling and
simulation for diesel powertrain design and control.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86386/1/ahlawatr_1.pd
Contribuição ao estudo do impacto das não linearidades nos sistemas de telecomunicações
Doutoramento em Engenharia ElectrotécnicaEsta tese insere-se na área de Electrónica de Rádio Frequência e Microondas
e visa o desenvolvimento de ferramentas que permitam a melhor compreensão
e análise do impacto da distorção não linear produzida em amplificadores de
potência no desempenho de um sistema de telecomunicações sem fios.
Devido à crescente complexidade dos amplificadores a simulação baseada em
representações de circuito equivalente tornou-se extremamente pesada do
ponto de vista computacional. Assim têm surgido várias técnicas de simulação
de sistemas baseadas em modelos comportamentais, ou seja, que tentam
aproximar a resposta do sistema a um sinal de entrada, independentemente
dos elementos físicos que implementam o circuito.
Neste trabalho foram estudadas as principais técnicas de modelação
comportamental existentes assim como as principais características de um
amplificador de potência que o modelo comportamental deve ser capaz de
prever.
Uma nova formulação de um modelo comportamental baseado na série de
Volterra é apresentada em conjunto com o método de extracção ortogonal dos
seus coeficientes. A principal vantagem deste novo método de extracção é
permitir a determinação independente de cada valor coeficiente na série,
garantindo-se deste modo um modelo com uma capacidade de aproximação
óptima. A determinação dos coeficientes na série de modo independente é
conseguida com base na reorganização dos termos da série e na identificação
ortogonal de cada componente de saída.
Adicionalmente, a identificação das componentes de saída de uma não
linearidade é ainda utilizada na definição de uma métrica que permite avaliar
de modo simples qual é a degradação imposta à qualidade do sinal ao ser
passado num amplificador não linear. Esta métrica contabiliza
simultaneamente a degradação imposta pelo ruído e pela distorção.This thesis is related to the RF and Microwave Electronics field and the main
goal of this thesis is to develop tools that can contribute to understand and
analyse the impact of nonlinear distortion generated by power amplifiers on
wireless communication systems.
Due to the growing complexity of amplifiers, equivalent circuit based
simulations become a heavy computational task due to the large number of
nonlinear elements to account for. So, several system simulation techniques
have been proposed based on behavioural modelling, that is, models that can
approximate the system’s response to a given input signal regardless of the
physical circuit implementation description.
In this thesis, the most important behavioural modelling techniques have been
studied as well as the main power amplifier characteristics that the behavioural
model should account for.
A new formulation of a Volterra series based behavioural model is presented as
well as the corresponding coefficient orthogonal extraction procedure. The
main advantage of this new extraction method is to allow the independent
determination of the exact value of each coefficient, guaranteeing this way an
optimum approximation condition. The exact coefficient determination is
achieved by reorganizing the series terms to reach independent subsets and by
identifying separately each of systems’ output components.
In addition, nonlinearity output component separation is also used to define a
Figure of Merit that allows the simple evaluation of signal quality degradation
when passed through a nonlinear amplifier. This Figure takes into account
simultaneously the impact of noise and distortion.FCTFS
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