Heuristic Order Reduction of NARX-OBF models Applied to Nonlinear System Identification

Nonlinear system identification concerns the determination of the modelstructure and its parameters. Although the designers often seek the bestmodel for each system, it can be tricky to determine, at the same time, thebest structure and the parameters which optimize the model performance.This paper proposes the use of a Genetic Algorithm, GA, and the Levenberg-Marquardt, LM, method to obtain the model parameters, as well asperform the order reduction of the model. In order to validate the proposedmethodology, the identification of a magnetic levitator, operating in closedloop, was performed. The class NARX-OBF, Nonlinear Auto Regressivewith eXogenous input-Orthonormal Basis Function, was used. The use ofOBF functions aims to reduce the number of terms in NARX models. Oncethe model is found, the order reduction is performed using GA and LM, ina hybrid application, capable of determining the model parameters and reducing the original model order, simultaneously. The results show, considering the inherent trade-of between accuracy and computational effort, theproposed methodology provided an implementation with good mean squareerror, when compared with the full NARX-OBF model

Anthropic Principle Algorithm:A new Heuristic Optimization Meth

Heuristic optimization is an appealing method for solving some en- gineering problems, in which gradient information may not be available, or yet, when the problem presents many minima points. Thus, the goal of this paper is to present a new heuristic algorithm based on the Anthropic Prin- ciple, the Anthropic Principle Algorithm (APA). This algorithm is based on the following idea: the universe developed itself in the exact way to allow the existence of all current things, including life. This idea is very similar to the convergence in an optimization process. Arguing about the merit of the An- thropic Principle is not among the goals of this paper. This principle is treated only as an inspiration for heuristic optimization algorithms. In the final of the paper, some applications of the APA are presented. Classical problems such as Rosenbrock function minimization, system identification examples and min- imization of some benchmark functions are also presented. In order to vali- date the APA’s functionality, a comparison between the APA and the classic heuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimiza- tion (PSO) is made. In this comparison, the APA presented better results in majority of tested cases, proving that it has a great potential for application in optimization problems

Modelo de transistor mono-elétron utilizando identificação de sistemas

Orientador: Prof. Dr. Marlio José do Couto BonfimCoorientadora: Profa. Dra. Janaina Gonçalves GuimarãesTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 05/07/2019Inclui referências: p. 153-159Resumo: Diante da necessidade de dispositivos eletrônicos cada vez menores e com maior capacidade de processamento de dados, a nanoeletrônica surge como uma alternativa aos dispositivos tradicionais. Dentre os dispositivos mono-elétron já propostos, o transistor mono-elétron, SET, ocupa lugar de destaque. Entre os principais desafios que dificultam a ampla aplicação do SET na indústria eletrônica encontram-se a falta de técnicas de fabricação consolidadas e a dificuldade que estes dispositivos apresentam para operar em temperatura ambiente. Para que estes e outros desafios sejam vencidos, são necessárias ferramentas de simulação adequadas e modelos precisos. Sendo assim, o objetivo deste trabalho consiste em aplicar conhecimentos relativos à Identificação de Sistemas para efetuar a modelagem caixa preta do transistor mono-elétron. Modelos caixa preta baseiam-se exclusivamente em dados de entrada e saída coletados do sistema a ser modelado. Estes modelos são conhecidos por se adequar com bastante precisão à dinâmica do sistema. Modelos já propostos para o SET baseiam-se em modelagem analítica e requerem conhecimento prévio sobre o sistema. Neste trabalho, foram coletados dados de entrada e saída do transistor mono-elétron por meio de simulações efetuadas com o SIMON, uma das plataformas de simulação de circuitos nanoeletrônicos mais difundidas na literatura. Aplicou-se um sinal persistentemente excitante como tensão de porta do transistor e coletou-se a corrente entre dreno e fonte. De posse destes dados, foram testadas as seguintes classes de modelos: NARX, Hammerstein, Wiener e Hammerstein-Wiener. Como métricas para realizar a comparação entre essas classes, foram utilizados o Erro Médio Quadrático e o tempo médio de simulação, computado para 50 execuções do experimento de validação dos modelos. Além disso, a simplicidade da estrutura matemática foi determinante na escolha da classe de modelos. A classe de Hammerstein-Wiener obteve o melhor desempenho. Deste modo, foram construídos modelos de Hammerstein-Wiener para o SET operando em diferentes condições. Os resultados comprovam a adequação desta representação matemática para a modelagem do transistor. Palavras-chave: Modelagem Caixa Preta. SET. Eletrônica Mono-Elétron. Identificação de Sistemas. Modelos de Hammerstein-Wiener.Abstract: Given the need for smaller electronic devices with great data processing capability, nanoelectronics appears as an alternative to traditional devices. Among the singleelectron devices already proposed, the Single-Electron Transistor, SET, has a prominent place. Among the main challenges that prevent SET from being widely applied in the electronics industry are the lack of consolidated manufacturing techniques and the difficulty these devices present to operate at room temperature. In order to overcome these and other challenges, appropriate simulation tools and precise models are needed. Thus, the goal of this work is the black box modeling of the SET. Black box models are based exclusively on input and output data collected from the system being modeled. These models are known to fit very accurately to the dynamics of the system. Models already proposed for SET are based on analytical modeling and require prior knowledge about the system. In this work, the input and output data of the single-electron transistor were collected through simulations performed with SIMON, one of the most widespread nanoelectronic circuit simulation platforms. A persistently exciting signal was applied as the gate voltage of the transistor and the current was collected between drain and source. With these data, the following classes of models were tested: NARX, Hammerstein, Wiener and Hammerstein-Wiener. As metrics to perform the comparison between these classes of models, the MSE and the mean simulation time, computed for 50 runs of the validation experiment of the models, were used. In addition, the simplicity of the mathematical structure of the model was decisive in the choice of the mathematic representation. The Hammerstein-Wiener class achieved the best performance. In this way, Hammerstein-Wiener models were constructed for SET operating under different conditions. The results prove the adequacy of this mathematical representation for modeling the transistor. Keywords: Black Box Modeling. SET. Single-Electron Electronics. System Identification. Hammerstein-Wiener Models

Modelo de transistor mono-elétron utilizando identificação de sistemas

Orientador: Prof. Dr. Marlio José do Couto BonfimCoorientadora: Profa. Dra. Janaina Gonçalves GuimarãesTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 05/07/2019Inclui referências: p. 153-159Resumo: Diante da necessidade de dispositivos eletrônicos cada vez menores e com maior capacidade de processamento de dados, a nanoeletrônica surge como uma alternativa aos dispositivos tradicionais. Dentre os dispositivos mono-elétron já propostos, o transistor mono-elétron, SET, ocupa lugar de destaque. Entre os principais desafios que dificultam a ampla aplicação do SET na indústria eletrônica encontram-se a falta de técnicas de fabricação consolidadas e a dificuldade que estes dispositivos apresentam para operar em temperatura ambiente. Para que estes e outros desafios sejam vencidos, são necessárias ferramentas de simulação adequadas e modelos precisos. Sendo assim, o objetivo deste trabalho consiste em aplicar conhecimentos relativos à Identificação de Sistemas para efetuar a modelagem caixa preta do transistor mono-elétron. Modelos caixa preta baseiam-se exclusivamente em dados de entrada e saída coletados do sistema a ser modelado. Estes modelos são conhecidos por se adequar com bastante precisão à dinâmica do sistema. Modelos já propostos para o SET baseiam-se em modelagem analítica e requerem conhecimento prévio sobre o sistema. Neste trabalho, foram coletados dados de entrada e saída do transistor mono-elétron por meio de simulações efetuadas com o SIMON, uma das plataformas de simulação de circuitos nanoeletrônicos mais difundidas na literatura. Aplicou-se um sinal persistentemente excitante como tensão de porta do transistor e coletou-se a corrente entre dreno e fonte. De posse destes dados, foram testadas as seguintes classes de modelos: NARX, Hammerstein, Wiener e Hammerstein-Wiener. Como métricas para realizar a comparação entre essas classes, foram utilizados o Erro Médio Quadrático e o tempo médio de simulação, computado para 50 execuções do experimento de validação dos modelos. Além disso, a simplicidade da estrutura matemática foi determinante na escolha da classe de modelos. A classe de Hammerstein-Wiener obteve o melhor desempenho. Deste modo, foram construídos modelos de Hammerstein-Wiener para o SET operando em diferentes condições. Os resultados comprovam a adequação desta representação matemática para a modelagem do transistor. Palavras-chave: Modelagem Caixa Preta. SET. Eletrônica Mono-Elétron. Identificação de Sistemas. Modelos de Hammerstein-Wiener.Abstract: Given the need for smaller electronic devices with great data processing capability, nanoelectronics appears as an alternative to traditional devices. Among the singleelectron devices already proposed, the Single-Electron Transistor, SET, has a prominent place. Among the main challenges that prevent SET from being widely applied in the electronics industry are the lack of consolidated manufacturing techniques and the difficulty these devices present to operate at room temperature. In order to overcome these and other challenges, appropriate simulation tools and precise models are needed. Thus, the goal of this work is the black box modeling of the SET. Black box models are based exclusively on input and output data collected from the system being modeled. These models are known to fit very accurately to the dynamics of the system. Models already proposed for SET are based on analytical modeling and require prior knowledge about the system. In this work, the input and output data of the single-electron transistor were collected through simulations performed with SIMON, one of the most widespread nanoelectronic circuit simulation platforms. A persistently exciting signal was applied as the gate voltage of the transistor and the current was collected between drain and source. With these data, the following classes of models were tested: NARX, Hammerstein, Wiener and Hammerstein-Wiener. As metrics to perform the comparison between these classes of models, the MSE and the mean simulation time, computed for 50 runs of the validation experiment of the models, were used. In addition, the simplicity of the mathematical structure of the model was decisive in the choice of the mathematic representation. The Hammerstein-Wiener class achieved the best performance. In this way, Hammerstein-Wiener models were constructed for SET operating under different conditions. The results prove the adequacy of this mathematical representation for modeling the transistor. Keywords: Black Box Modeling. SET. Single-Electron Electronics. System Identification. Hammerstein-Wiener Models

A nanoelectronic building block for spiking neural networks

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2014.A habilidade de simular de forma mais realista o comportamento do cérebro humano fez com que as redes neurais pulsantes (SNNs, Spiking Neural Networks) se tornassem populares entre os pesquisadores. Estes circuitos, altamente densos, apresentam grande capacidade de processamento de dados. Inicialmente, acreditava-se que arquiteturas reconfiguráveis, como FPGAs, Field Programmable Gale Arrays, poderiam ser usadas como protótipos para a construção de SNNs. Entretanto, FPGAs não suportam os altos níveis de conectividade entre neurônios em uma SNN densa. Além disso, a implementação através de FPGAs não fornece melhorias quanto a dissipação de potência ou área ocupada. Por este motivo, os pesquisadores começaram a utilizar NoCs, Networks-on-Chip, para interconectar SNNs. O uso de NoCs é capaz de reduzir o número de interconexões e apresenta uma grande vantagem relativa à tolerância a falhas: redundância. Neste contexto, algumas configurações combinando neurônios e roteadores foram propostas. Estes componentes constituem o bloco básico, presente em cada no da NoC. Vários modelos de neurônios pulsantes e vários algoritmos de roteamento foram usados. Todas estas propostas buscam a implementação de redes cada vez mais densas, reduzindo a dissipação de potência e a área ocupada. No entanto, nenhum dos trabalhos anteriores usa um modelo nanoeletrônico para o neurônio pulsante. A implementação nanoeletrônica e bem conhecida pelos ganhos que apresenta justamente nesses dois parâmetros: dissipação de potencia e área ocupada. Assim, este trabalho propõe um bloco básico de construção para ser utilizado em uma NoC do tipo 2D mesh. Este bloco consiste de um neurônio pulsante nanoeletrônico conectado a um roteador, implementado através de uma LUT, Look-Up Table. Primeiramente, o modelo do neurônio foi redimensionado para funcionar a 300 K, a temperatura ambiente. Depois, o comportamento do neurônio foi testado através da implementação de várias portas lógicas, tais como inversora, OU, E e XOR. Um elemento roteador simples e, então, proposto a fim de construir o primeiro bloco para a NoC. Para testar a funcionalidade deste bloco, uma XOR com 2 entradas foi apresentada para a SNN construída com este bloco. Finalmente, um roteador capaz de comunicar neurônios em 4 direções foi proposto e um bloco de construção para a NoC com este roteador foi implementado. O problema da XOR, com 3 e com 5 entradas, foi usado para validar a funcionalidade deste bloco.The ability to emulate more realisticaly the behavior of the human brain made Spiking Neural Networks (SNNs) gain prominence between researchers. These highly dense circuits feature large capacity of data processing. Searching for reconfigurable devices, computer scientists and engineers used Field Programmable Gate Arrays (FPGAs) as prototypes for SNNs. However, FPGAs cannot support the highlevels of connectivity between neurons in a dense SNN. Besides, implementation with FPGA does not provide improvements re garding power dissipation or scale. Therefore, researchers began to use Networks-on-Chip (NoCs) to interconnect SNNs. The use of NoCs may reduce the number of interconnections and presents a big advantage regarding fault tolerance: redundancy. In this context, several configurations combining neurons and routers were proposed. These devices constitute the basic block, present in every node of the NoC. Various models of spiking neurons were used, combined with various routing algorithms. All these proposals aim the implementation of denser networks, reducing the power dissipation and the occupied area. However, none of the previous works uses a nanoelectronic model for the spiking neuron. Nanoelectronic im¬plementation is well known for the gains that it presents precisely in these two parameters: occupicd area and power dissipation. Thus, this work proposes a basic block for a 2D-mesh NoC, consisting of a nanoelectronic spiking neuron connected to a router, implemented with a Look-Up Table (LUT). First, the model for the nanoelectronic neuron is scaled in order to work at 300 K, the room temperature. Then, the behaviour of the neuron is tested through the implementation of various logic gates, such as NOT, AND, OR and XOR gates. A simple routing element is proposed to construct the first building block. In order to test the functionality of this block, a 2 inputs XOR problem is presented to a SNN implemented with this block. Finally, a full directional router is proposed and a building block using this router is implemented. The XOR problem, with 3 and with 5 inputs, is used to validate the functionality of this block

Physiological changes in silver catfish (Rhamdia quelen) transported with essential oil of Myrcia sylvatica

Trabajo presentado en el 10º Congreso de la Asociación Ibérica de Endocrinología Comparada, celebrado en Castellón del 23 al 25 de septiembre de 2015.Aquaculture practices include several procedures as capture, handling and transport, which cause stress in fish. Anesthetics or sedative substances have been used to reduce this stress. The aim of this study was to evaluate the effects of essential oil of Myrcia sylvatica (EOMS) in the water on stress system activation in the silver catfish Rhamdia quelen summited to transport. Fish were captured in the production ponds and transferred to a 250-L tanks (density of 54 kg/m3). After 24 hours, 10 fish were caught, euthanized by section of the spinal cord and sampled (basal group). The remaining fish were placed in plastic bags containing 5 L of water (density of 150 kg/m3) with different doses of EOMS (0, 25 or 35 μL/L diluted in 315 μL/L ethanol), in triplicate, and transported for 6 h. After transportation, 10 animals of each group were captured, euthanized and sampled. Cortisol and glucose levels in plasma, as well as hypothalamic corticotrophin-releasing hormone (CRH) and pituitary proopiomelanocortin (POMC) “a” and “b” mRNA expressions were determined. Cortisol levels and CRH expression enhanced after 24h of handling, decreasing during the transport with addition of EOMS. Expression of POMCa was higher in fish transported with 25 μL/L respect to the rest of groups. Therefore, it is suggested the use of EOMS for transporting fish in order to avoid the stress associated with this procedure.Financial Support: FAPERGS/PRONEX, CAPES, CNPq.Peer reviewe

Quercetin attenuates endocrine and metabolic responses to oxytetracycline in silver catfish (Rhamdia quelen)

This study aimed to verify whether dietary quercetin protects against the detrimental effects induced by oxytetracycline (OTC) administration in silver catfish (Rhamdia quelen). Fish were divided into different experimental groups that received OTC and/or quercetin, either during 14 or 21 days. To determine the endocrine system stress response, we have measured the brain mRNA expression levels of corticotropin-releasing hormone (crh), proopiomelanocortins (pomca and pomcb) and some of the pituitary hormones (growth hormone [gh], somatolactin [sl], and prolactin [prl]). We have also quantified the levels of cortisol as well as some metabolites (glucose, glycogen, lactate, and triglycerides) in the plasma. Moreover, the enzymatic activity of hexokinase, phosphorylase (active GPase), fructose-biphosphatase (FBP), glycerol-3-phosphate dehydrogenase, glucose-6-phosphate dehydrogenase, and glutamate dehydrogenase (GDH) and gill Na+/K+-ATPase were measured. The results demonstrated that OTC activates the silver catfish stress response by increasing the plasma cortisol and decreasing the glucose levels at 14 and 21 days. Additionally, OTC also altered the fish hepatic metabolic status as demonstrated by an increase in triglycerides levels and the enzymatic activity of both FBP and GDH after 14 days. OTC also stimulated Na+/K+-ATPase activity in the gill after 14 days and altered the hypophyseal expression of gh (at 14 and 21 days) and prl (at 14 days). The co-treatment with 1.5 g of quercetin could prevent most of the alterations caused by OTC, strongly suggesting quercetin as a beneficial compound when added to the fish diet.This work was funded by Spanish Ministry of Science and Innovation - MICINN (AGL2016-76069-C2-1-R) awarded to JMM. IJC was supported by a contract from the University of Cádiz (PIF UCA/REC02VIT/2014; 2018-011/PU/AY.PUENTE/CD). The authors (IJC and JMM) belong to the Fish Welfare and Stress Network (AGL2016-81808-REDT), which is supported by the Agencia Estatal de Investigación (MICINN, Spanish Government). The authors wish to thank the financial support received by Conselho Nacional de Pesquisa e Desenvolvimento Científico-CNPq (Ministry of Education of Brazil, Brazil) through the program CSF (Programa Ciência sem Fronteiras (CONCF) - Process: 207329/2015-0) awarded to Tanise da Silva Pês and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)