On Variable Selection of a Nonlinear Non-parametric System with a Limited Data Set: A Stepwise Algorithm

his paper considers a problem of identification for a high dimensional nonlinear non-parametric system when only a limited data set is available. The algorithms are proposed for this purpose which exploit the relationship between the input variables and the output and further the inter-dependence of input variables so that the importance of the input variables can be established. A key to these algorithms is the non-parametric two stage input selection algorithm.

On Infinite Time Performance of Nonlinear Model Predictive Controllers

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

Performance Limits of MIMO Systems with Nonlinear Power Amplifiers

The development of 5G enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable. Hence, it is first necessary to fully understand how and how much the performance of multiple-input multiple-output (MIMO) systems deteriorates with PA nonlinearities. In this paper, we first reduce the ergodic achievable rate (EAR) optimization from a power allocation to a power control problem with only one optimization variable, i.e. total input power. Then, we develop a closed-form expression for the EAR, where this variable is fixed. Since this expression is intractable for further analysis, two simple lower bounds and one upper bound are proposed. These bounds enable us to find the best input power and approach the channel capacity. Finally, our simulation results evaluate the EAR of MIMO channels in the presence of nonlinearities. An important observation is that the MIMO performance can be significantly degraded if we utilize the whole power budget.

Wide-Area Phase-Angle Measurements for Islanding Detection—An Adaptive Nonlinear Approach

The integration of an ever growing proportion of large scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to non-synchronous penetration in a power grid, system wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide area phase angle measurements. This is challenging, since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis is proposed to model the time-varying and nonlinear trends in the voltage phase angle data. The effectiveness of the technique is exemplified using both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.

Weakly nonlinear ion-acoustic excitations in a relativistic model for dense quantum plasma

The dynamics of linear and nonlinear ionic-scale electrostatic excitations propagating in a magnetized relativistic quantum plasma is studied. A quantum-hydrodynamic model is adopted and degenerate statistics for the electrons is taken into account. The dispersion properties of linear ion acoustic waves are examined in detail. A modified characteristic charge screening length and "sound speed" are introduced, for relativistic quantum plasmas. By employing the reductive perturbation technique, a Zakharov-Kuznetzov-type equation is derived. Using the small-k expansion method, the stability profile of weakly nonlinear slightly supersonic electrostatic pulses is also discussed. The effect of electron degeneracy on the basic characteristics of electrostatic excitations is investigated. The entire analysis is valid in a three-dimensional as well as in two-dimensional geometry. A brief discussion of possible applications in laboratory and space plasmas is included.

Modelling the nonlinear behaviour and fracture process of AS4/PEKK thermoplastic composite under shear loading

The accurate determination of non-linear shear behaviour and fracture toughness of continuous carbon-fibre/polymer composites remains a considerable challenge. These measurements are often necessary to generate material parameters for advanced computational damage models. In particular, there is a dearth of detailed shear fracture toughness characterisation for thermoplastic composites which are increasingly generating renewed interest within the aerospace and automotive sectors. In this work, carbon fibre (AS4)/ thermoplastic Polyetherketoneketone (PEKK) composite V-notched cross-ply specimens were manufactured to investigate their non-linear response under pure shear loading. Both monotonic and cyclic loading were applied to study the shear modulus degradation and progressive failure. For the first time in the reported literature, we use the essential work of fracture approach to measure the shear fracture toughness of continuous fibre reinforced composite laminates. Excellent geometric similarity in the load-displacement curves was observed for ligament-scaled specimens. The laminate fracture toughness was determined by linear regression, of the specific work of fracture values, to zero ligament thickness, and verified with computational models. The matrix intralaminar fracture toughness (ply level fracture toughness), associated with shear loading was determined by the area method. This paper also details the numerical implementation of a new three-dimensional phenomenological model for carbon fibre thermoplastic composites using the measured values, which is able to accurately represent the full non-linear mechanical response and fracture process. The constitutive model includes a new non-linear shear profile, shear modulus degradation and load reversal. It is combined with a smeared crack model for representing ply-level damage initiation and propagation. The model is shown to accurately predict the constitutive response in terms of permanent plastic strain, degraded modulus as well as load reversal. Predictions are also shown to compare favourably with the evolution of damage leading to final fracture.

Performance of polarisation functionals for linear and nonlinear optical properties of bulk zinc chalcogenides ZnX (X=S,Se,Te).

We calculated the frequency dependent macroscopic dielectric function and second-harmonic generation of cubic ZnS, ZnSe and ZnTe within time-dependent density-polarisation functional theory. The macroscopic dielectric function is calculated in a linear response framework, and second-harmonic generation in a real-time framework. The macroscopic exchange–correlation electric field that enters the time-dependent Kohn–Sham equations and accounts for long range correlation is approximated as a simple polarisation functional αP, where P is the macroscopic polarisation. Expressions for α are taken from the recent literature. The performance of the resulting approximations for the exchange–correlation electric field is analysed by comparing the theoretical spectra with experimental results and results obtained at the levels of the independent particle approximation and the random-phase approximation. For the dielectric function we also compare with state-of-the art calculations at the level of the Bethe–Salpeter equation.

A high-energy, high-flux source of gamma-rays from all-optical nonlinear Thomson scattering

γ-Ray sources are among the most fundamental experimental tools currently available to modern physics. As well as the obvious benefits to fundamental research, an ultra-bright source of γ-rays could form the foundation of scanning of shipping containers for special nuclear materials and provide the bases for new types of cancer therapy.

However, for these applications to prove viable, γ-ray sources must become compact and relatively cheap to manufacture. In recent years, advances in laser technology have formed the cornerstone of optical sources of high energy electrons which already have been used to generate synchrotron radiation on a compact scale. Exploiting the scattering induced by a second laser, one can further enhance the energy and number of photons produced provided the problems of synchronisation and compact γ-ray detection are solved.

Here, we report on the work that has been done in developing an all-optical and hence, compact non-linear Thomson scattering source, including the new methods of synchronisation and compact γ-ray detection. We present evidence of the generation of multi-MeV (maximum 16–18 MeV) and ultra-high brilliance (exceeding 10²⁰ photons s⁻¹mm⁻²mrad⁻² 0.1% BW at 15 MeV) γ-ray beams. These characteristics are appealing for the paramount practical applications mentioned above.

Counter-Mappings: Cartography and Difference

Introduction to the co-edited book 'Cartographies of Differences: Interdisciplinary Perspectives

Study of the impact from nonlinear distortion in radio receiver architectures

A dissertação de doutoramento apresentada insere-se na área de electrónica não-linear de rádio-frequência (RF), UHF e microondas, tendo como principal campo de acção o estudo da distorção nãolinear em arquitecturas de recepção rádio, nomeadamente receptores de conversão directa como Power Meters, RFID (Radio Frequency IDentification) ou SDR (Software Define Radio) front-ends. Partindo de um estudo exaustivo das actuais arquitecturas de recepção de radiofrequência e revendo todos os conceitos teóricos relacionados com o desempenho não-linear dos sistemas/componentes electrónicos, foram desenvolvidos algoritmos matemáticos de modulação dos comportamentos não-lineares destas arquitecturas, simulados e testados em laboratório e propostas novas arquitecturas para a minimização ou cancelamento do impacto negativo de grandes interferidores em frequências vizinhas ao do sistema pretendido.

Nonlinear behavioral modeling of mixed signal RF-digital I/O devices

Esta tese investiga a caracterização (e modelação) de dispositivos que realizam o interface entre os domínios digital e analógico, tal como os buffers de saída dos circuitos integrados (CI). Os terminais sem fios da atualidade estão a ser desenvolvidos tendo em vista o conceito de rádio-definido-por-software introduzido por Mitola. Idealmente esta arquitetura tira partido de poderosos processadores e estende a operação dos blocos digitais o mais próximo possível da antena. Neste sentido, não é de estranhar que haja uma crescente preocupação, no seio da comunidade científica, relativamente à caracterização dos blocos que fazem o interface entre os domínios analógico e digital, sendo os conversores digital-analógico e analógico-digital dois bons exemplos destes circuitos. Dentro dos circuitos digitais de alta velocidade, tais como as memórias Flash, um papel semelhante é desempenhado pelos buffers de saída. Estes realizam o interface entre o domínio digital (núcleo lógico) e o domínio analógico (encapsulamento dos CI e parasitas associados às linhas de transmissão), determinando a integridade do sinal transmitido. Por forma a acelerar a análise de integridade do sinal, aquando do projeto de um CI, é fundamental ter modelos que são simultaneamente eficientes (em termos computacionais) e precisos. Tipicamente a extração/validação dos modelos para buffers de saída é feita usando dados obtidos da simulação de um modelo detalhado (ao nível do transístor) ou a partir de resultados experimentais. A última abordagem não envolve problemas de propriedade intelectual; contudo é raramente mencionada na literatura referente à caracterização de buffers de saída. Neste sentido, esta tese de Doutoramento foca-se no desenvolvimento de uma nova configuração de medição para a caracterização e modelação de buffers de saída de alta velocidade, com a natural extensão aos dispositivos amplificadores comutados RF-CMOS. Tendo por base um procedimento experimental bem definido, um modelo estado-da-arte é extraído e validado. A configuração de medição desenvolvida aborda não apenas a integridade dos sinais de saída mas também do barramento de alimentação. Por forma a determinar a sensibilidade das quantias estimadas (tensão e corrente) aos erros presentes nas diversas variáveis associadas ao procedimento experimental, uma análise de incerteza é também apresentada.

Numerical tools for isogeometric analysis in the nonlinear regime

The present work deals with the development of robust numerical tools for Isogeometric Analysis suitable for problems of solid mechanics in the nonlinear regime. To that end, a new solid-shell element, based on the Assumed Natural Strain method, is proposed for the analysis of thin shell-like structures. The formulation is extensively validated using a set of well-known benchmark problems available in the literature, in both linear and nonlinear (geometric and material) regimes. It is also proposed an alternative formulation which is focused on the alleviation of the volumetric locking pathology in linear elastic problems. In addition, an introductory study in the field of contact mechanics, in the context of Isogeometric Analysis, is also presented, with special focus on the implementation of a the Point-to-Segment algorithm. All the methodologies presented in the current work were implemented in a in-house code, together with several pre- and post-processing tools. In addition, user subroutines for the commercial software Abaqus were also implemented.

Phase transitions and nonlinear phenomena in neuronal network models

Communication and cooperation between billions of neurons underlie the power of the brain. How do complex functions of the brain arise from its cellular constituents? How do groups of neurons self-organize into patterns of activity? These are crucial questions in neuroscience. In order to answer them, it is necessary to have solid theoretical understanding of how single neurons communicate at the microscopic level, and how cooperative activity emerges. In this thesis we aim to understand how complex collective phenomena can arise in a simple model of neuronal networks. We use a model with balanced excitation and inhibition and complex network architecture, and we develop analytical and numerical methods for describing its neuronal dynamics. We study how interaction between neurons generates various collective phenomena, such as spontaneous appearance of network oscillations and seizures, and early warnings of these transitions in neuronal networks. Within our model, we show that phase transitions separate various dynamical regimes, and we investigate the corresponding bifurcations and critical phenomena. It permits us to suggest a qualitative explanation of the Berger effect, and to investigate phenomena such as avalanches, band-pass filter, and stochastic resonance. The role of modular structure in the detection of weak signals is also discussed. Moreover, we find nonlinear excitations that can describe paroxysmal spikes observed in electroencephalograms from epileptic brains. It allows us to propose a method to predict epileptic seizures. Memory and learning are key functions of the brain. There are evidences that these processes result from dynamical changes in the structure of the brain. At the microscopic level, synaptic connections are plastic and are modified according to the dynamics of neurons. Thus, we generalize our cortical model to take into account synaptic plasticity and we show that the repertoire of dynamical regimes becomes richer. In particular, we find mixed-mode oscillations and a chaotic regime in neuronal network dynamics.

Joint turbo equalization and cancelation of nonlinear distortion effects in MC-CDMA signals

In this paper, we consider low-PMEPR (Peak-to-Mean Envelope Power Ratio) MC-CDMA (Multicarrier Coded Division Multiple Access) schemes. We develop frequencydomain turbo equalizers combined with an iterative estimation and cancellation of nonlinear distortion effects. Our receivers have relatively low complexity, since they allow FFT-based (Fast Fourier Transform) implementations. The proposed turbo receivers allow significant performance improvements at low and moderate SNR (Signal-to-Noise Ratio), even when a low-PMEPR MC-CDMA transmission is intended.