Kernel-based local order estimation of nonlinear nonparametric systems

We consider the local order estimation of nonlinear autoregressive systems with exogenous inputs (NARX), which may have different local dimensions at different points. By minimizing the kernel-based local information criterion introduced in this paper, the strongly consistent estimates for the local orders of the NARX system at points of interest are obtained. The modification of the criterion and a simple procedure of searching the minimum of the criterion, are also discussed. The theoretical results derived here are tested by simulation examples.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

Kernel based approaches to local nonlinear non-parametric variable selection

In this paper, we consider the variable selection problem for a nonlinear non-parametric system. Two approaches are proposed, one top-down approach and one bottom-up approach. The top-down algorithm selects a variable by detecting if the corresponding partial derivative is zero or not at the point of interest. The algorithm is shown to have not only the parameter but also the set convergence. This is critical because the variable selection problem is binary, a variable is either selected or not selected. The bottom-up approach is based on the forward/backward stepwise selection which is designed to work if the data length is limited. Both approaches determine the most important variables locally and allow the unknown non-parametric nonlinear system to have different local dimensions at different points of interest. Further, two potential applications along with numerical simulations are provided to illustrate the usefulness of the proposed algorithms.

Estudio de la interacción docente-estudiante como factor de apropiación de conocimientos en educación de primera infancia colombiana

La interacción docente-estudiante es un elemento primordial en el proceso de formación de los niños de primera infancia. Los cambios del rol docente en dicho proceso de formación están ligado al tipo de modelo pedagógico que lo defina, por esto desde un análisis tradicional este cumple un papel más de emisor de información, caso contrario al establecido en el modelo constructivista, en el que el docente es quien provee los medios y la metodologías para la construcción del conocimiento. Con el fin de analizar la interacción entre estos dos actores, se parte definiendo el término de primera infancia para posteriormente abordar los tipos de modelos pedagógicos existentes y los cambios de los mismos en la educación colombiana, haciendo énfasis en el constructivismo en primera infancia. De igual forma se estudia la apropiación de las teorías constructivistas por parte de los docentes de primera infancia, teniendo en cuenta que estos son uno de los actores principales que hacen parte del proceso de formación, a partir de lo cual finalmente se estudia la interacción docente-estudiante de primera infancia para la apropiación del conocimiento.

Génesis del proyecto educativo de un colegio : College Claretain de Victiriaville, Quebec, Canadá.

Sintetizar el plan de acción de un colegio, elaborado por todos los agentes de la educación a partir de realidades concretas en vista del desenvolvimiento total del niño, con ayuda de la utilización racional de los recursos disponibles. 240 alumnos. Encuestas y entrevistas a los padres y alumnos. Estadística descriptiva. Los datos ajustados a una curva normal. La familiaridad con las exigencias de las funciones cognitivas y los principios del aprendizaje no dan la solución automatica de los problemas en la clase. El efecto educador se debe objetivar a la acción pedagógica de los principios psico-pedagógicos a fin de mejorar la comprensión para tener una visión sintetica, armónica y reciclar los objetivos, contenidos y métodos así como la evaluación de los aprendizajes. La educación es un hacer de corazón, pero sólo las funciones cognitivas pueden dar al acto educativo un sentido humano, una perspectiva, un devenir, una historia.

A stable one-step-ahead predictive control of non-linear systems

In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.

The relative order and inverses of recurrent networks

Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

Optimal control of a class of discrete–continuous non-linear systems — decomposition and hierarchical structure

A technique is derived for solving a non-linear optimal control problem by iterating on a sequence of simplified problems in linear quadratic form. The technique is designed to achieve the correct solution of the original non-linear optimal control problem in spite of these simplifications. A mixed approach with a discrete performance index and continuous state variable system description is used as the basis of the design, and it is shown how the global problem can be decomposed into local sub-system problems and a co-ordinator within a hierarchical framework. An analysis of the optimality and convergence properties of the algorithm is presented and the effectiveness of the technique is demonstrated using a simulation example with a non-separable performance index.

A tutorial on pseudospectral methods for computational optimal control

[English] This paper is a tutorial introduction to pseudospectral optimal control. With pseudospectral methods, a function is approximated as a linear combination of smooth basis functions, which are often chosen to be Legendre or Chebyshev polynomials. Collocation of the differential-algebraic equations is performed at orthogonal collocation points, which are selected to yield interpolation of high accuracy. Pseudospectral methods directly discretize the original optimal control problem to recast it into a nonlinear programming format. A numerical optimizer is then employed to find approximate local optimal solutions. The paper also briefly describes the functionality and implementation of PSOPT, an open source software package written in C++ that employs pseudospectral discretization methods to solve multi-phase optimal control problems. The software implements the Legendre and Chebyshev pseudospectral methods, and it has useful features such as automatic differentiation, sparsity detection, and automatic scaling. The use of pseudospectral methods is illustrated in two problems taken from the literature on computational optimal control. [Portuguese] Este artigo e um tutorial introdutorio sobre controle otimo pseudo-espectral. Em metodos pseudo-espectrais, uma funcao e aproximada como uma combinacao linear de funcoes de base suaves, tipicamente escolhidas como polinomios de Legendre ou Chebyshev. A colocacao de equacoes algebrico-diferenciais e realizada em pontos de colocacao ortogonal, que sao selecionados de modo a minimizar o erro de interpolacao. Metodos pseudoespectrais discretizam o problema de controle otimo original de modo a converte-lo em um problema de programa cao nao-linear. Um otimizador numerico e entao empregado para obter solucoes localmente otimas. Este artigo tambem descreve sucintamente a funcionalidade e a implementacao de um pacote computacional de codigo aberto escrito em C++ chamado PSOPT. Tal pacote emprega metodos de discretizacao pseudo-spectrais para resolver problemas de controle otimo com multiplas fase. O PSOPT permite a utilizacao de metodos de Legendre ou Chebyshev, e possui caractersticas uteis tais como diferenciacao automatica, deteccao de esparsidade e escalonamento automatico. O uso de metodos pseudo-espectrais e ilustrado em dois problemas retirados da literatura de controle otimo computacional.

Um Estudo de técnicas de aceleração para algoritmos de análise de timing funcional baseados em geração automática de teste

Este trabalho tem como objetivo estudar e avaliar técnicas para a aceleração de algoritmos de análise de timing funcional (FTA - Functional Timing Analysis) baseados em geração automática de testes (ATPG – Automatic Test Generation). Para tanto, são abordados três algoritmos conhecidos : algoritmo-D, o PODEM e o FAN. Após a análise dos algoritmos e o estudo de algumas técnicas de aceleração, é proposto o algoritmo DETA (Delay Enumeration-Based Timing Analysis) que determina o atraso crítico de circuitos que contêm portas complexas. O DETA está definido como um algoritmo baseado em ATPG com sensibilização concorrente de caminhos. Na implementação do algoritmo, foi possível validar o modelo de computação de atrasos para circuitos que contêm portas complexas utilizando a abordagem de macro-expansão implícita. Além disso, alguns resultados parciais demonstram que, para alguns circuitos, o DETA apresenta uma pequena dependência do número de entradas quando comparado com a dependência no procedimento de simulação. Desta forma, é possível evitar uma pesquisa extensa antes de se encontrar o teste e assim, obter sucesso na aplicação de métodos para aceleração do algoritmo.

Fluxo de potência ótimo reativo via método da função lagrangiana barreira modificada

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Um método eficiente para resolução do problema de Despacho Ótimo de Reativos com controle discreto do TAP dos transformadores

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Revisitando o eletrocorticograma intra-operatório na epilepsia mesial do lobo temporal: relevância das oscilações de alta frequência

Epilepsies are neurological disorders characterized by recurrent and spontaneous seizures due to an abnormal electric activity in a brain network. The mesial temporal lobe epilepsy (MTLE) is the most prevalent type of epilepsy in adulthood, and it occurs frequently in association with hippocampal sclerosis. Unfortunately, not all patients benefit from pharmacological treatment (drug-resistant patients), and therefore become candidates for surgery, a procedure of high complexity and cost. Nowadays, the most common surgery is the anterior temporal lobectomy with selective amygdalohippocampectomy, a procedure standardized by anatomical markers. However, part of patients still present seizure after the procedure. Then, to increase the efficiency of this kind of procedure, it is fundamental to know the epileptic human brain in order to create new tools for auxiliary an individualized surgery procedure. The aim of this work was to identify and quantify the occurrence of epilepticform activity -such as interictal spikes (IS) and high frequency oscillations (HFO) - in electrocorticographic (ECoG) signals acutely recorded during the surgery procedure in drug-resistant patients with MTLE. The ECoG recording (32 channels at sample rate of 1 kHz) was performed in the surface of temporal lobe in three moments: without any cortical resection, after anterior temporal lobectomy and after amygdalohippocampectomy (mean duration of each record: 10 min; N = 17 patients; ethic approval #1038/03 in Research Ethic Committee of Federal University of São Paulo). The occurrence of IS and HFO was quantified automatically by MATLAB routines and validated manually. The events rate (number of events/channels) in each recording time was correlated with seizure control outcome. In 8 hours and 40 minutes of record, we identified 36,858 IS and 1.756 HFO. We observed that seizure-free outcome patients had more HFO rate before the resection than non-seizure free, however do not differentiate in relation of frequency, morphology and distribution of IS. The HFO rate in the first record was better than IS rate on prediction of seizure-free patients (IS: AUC = 57%, Sens = 70%, Spec = 71% vs HFO: AUC = 77%, Sens = 100%, Spec = 70%). We observed the same for the difference of the rate of pre and post-resection (IS: AUC = 54%, Sens = 60%, Spec = 71%; vs HFO: AUC = 84%, Sens = 100%, Spec = 80%). In this case, the algorithm identifies all seizure-free patients (N = 7) with two false positives. To conclude, we observed that the IS and HFO can be found in intra-operative ECoG record, despite the anesthesia and the short time of record. The possibility to classify the patients before any cortical resection suggest that ECoG can be important to decide the use of adjuvant pharmacological treatment or to change for tailored resection procedure. The mechanism responsible for this effect is still unknown, thus more studies are necessary to clarify the processes related to it