Nonlinear Black-Box Models of Digital Integrated Circuits via System Identification

This Thesis concerns the development of numerical macromodels of digi- tal Integrated Circuits input/output buffers. Such models are of paramount importance for the system-level simulation required for the assessment of Sig- nal Integrity and Electromagnetic Compatibility effects in high-performance electronic equipments via system-level simulations. In order to obtain accurate and efficient macromodels, we concentrate on the black-box modeling approach, exploiting system identification methods. The present study contributes to the systematic discussion of the IC mod- eling process, in order to obtain macromodels that can overcome strengths and limitations of the methodologies presented so far. The performances of different parametric representations, as Sigmoidal Basis Functions (SBF) ex- pansions, Echo State Networks (ESN) and Local Linear State-Space (LLSS) models are investigated. All representations have proven capabilities for the modeling of unknown nonlinear dynamic systems and are good candidates too be used for the modeling problem at hand. For each model representation, the most suitable estimation algorithm is considered and a systematic analy- sis is performed to highlight advantages and limitations. For this analysis, the modeling process is applied to a synthetic nonlinear device representative of IC ports, and designed to generate stiff responses. The tests carried out show that LLSS models provide the best overall performance for the modeling of digital devices, even with strong nonlinear dynamics. LLSS models can be estimated by means of an efficient algorithm providing a unique solution. Local stability of models is preconditioned and verified a posteriori. The effectiveness of the modeling process based on LLSS representations is verified by applying the proposed technique to the modeling of real devices involved in a realistic data communication link (an RF-to-Digital interface used in mobile phones). The obtained macromodels have been successfully used to predict both the functional signals and the power supply and ground fluctuations. Besides, they turn out to be very efficient, providing a signifi- cant simulation speed-up for the complete data link

Metamodeling-based Fast Optimization of Nanoscale Ams-socs

Modern consumer electronic systems are mostly based on analog and digital circuits and are designed as analog/mixed-signal systems on chip (AMS-SoCs). the integration of analog and digital circuits on the same die makes the system cost effective. in AMS-SoCs, analog and mixed-signal portions have not traditionally received much attention due to their complexity. As the fabrication technology advances, the simulation times for AMS-SoC circuits become more complex and take significant amounts of time. the time allocated for the circuit design and optimization creates a need to reduce the simulation time. the time constraints placed on designers are imposed by the ever-shortening time to market and non-recurrent cost of the chip. This dissertation proposes the use of a novel method, called metamodeling, and intelligent optimization algorithms to reduce the design time. Metamodel-based ultra-fast design flows are proposed and investigated. Metamodel creation is a one time process and relies on fast sampling through accurate parasitic-aware simulations. One of the targets of this dissertation is to minimize the sample size while retaining the accuracy of the model. in order to achieve this goal, different statistical sampling techniques are explored and applied to various AMS-SoC circuits. Also, different metamodel functions are explored for their accuracy and application to AMS-SoCs. Several different optimization algorithms are compared for global optimization accuracy and convergence. Three different AMS circuits, ring oscillator, inductor-capacitor voltage-controlled oscillator (LC-VCO) and phase locked loop (PLL) that are present in many AMS-SoC are used in this study for design flow application. Metamodels created in this dissertation provide accuracy with an error of less than 2% from the physical layout simulations. After optimal sampling investigation, metamodel functions and optimization algorithms are ranked in terms of speed and accuracy. Experimental results show that the proposed design flow provides roughly 5,000x speedup over conventional design flows. Thus, this dissertation greatly advances the state-of-the-art in mixed-signal design and will assist towards making consumer electronics cheaper and affordable

Model Order Reduction

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science

SCEE 2008 book of abstracts : the 7th International Conference on Scientific Computing in Electrical Engineering (SCEE 2008), September 28 – October 3, 2008, Helsinki University of Technology, Espoo, Finland

This report contains abstracts of presentations given at the SCEE 2008 conference.reviewe

A machine learning approach to appraise and enhance the structural resilience of buildings to seismic hazards

Earthquakes often affect buildings that did comply with regulations in force at the time of design, prompting the need for new approaches addressing the complex structural dynamics of seismic design. In this paper, we demonstrate how strucural resilience can be appraised to inform optimization pathways by utilising artificial neural networks, augmented with evolutionary computation. This involves efficient multi-layer computational models, to learn complex multi-aspects structural dynamics, through several levels of abstraction. By means of single and multi-objective optimization, an existing structural system is modelled with an accuracy in excess of 98% to simulate its structural loading behaviour, while a performance-based approach is used to determine the optimum parameter settings to maximize its earthquake resilience. We have used the 2008 Wenchuan Earthquake as a case study. Our results demonstrate that an estimated structural design cost increase of 20% can lead to a damage reduction of up to 75%, which drastically reduces the risk of fatality

Reduction of network models with a large number of sources

[no abstract

Model order reduction techniques in microelectromechanics

Ph.DDOCTOR OF PHILOSOPH

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