Contribuição para o estudo do embarque de uma rede neural artificial em field programmable gate array (FPGA)

This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing

Desenvolvimento de um ambiente para projeto de controladores fuzzy para dispositivos móveis

Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to small devices such as digital cameras and cell phones being used primarily for dealing with the uncertainties in the modeling of real systems. However, commercial implementations of Fuzzy systems are not general purpose and do not have portability to different hardware platforms. Thinking about these issues this work presents the implementation of an open source development environment that consists of a desktop system capable of generate Graphically a general purpose Fuzzy controller and export these parameters for an embedded system with a Fuzzy controller written in Java Platform Micro Edition To (J2ME), whose modular design makes it portable to any mobile device that supports J2ME. Thus, the proposed development platform is capable of generating all the parameters of a Fuzzy controller and export it in XML file, and the code responsible for the control logic that is embedded in the mobile device is able to read this file and start the controller. All the parameters of a Fuzzy controller are configurable using the desktop system, since the membership functions and rule base, even the universe of discourse of the linguistic terms of output variables. This system generates Fuzzy controllers for the interpolation model of Takagi-Sugeno. As the validation process and testing of the proposed solution the Fuzzy controller was embedded on the mobile device Sun SPOT ® and used to control a plant-level Quanser®, and to compare the Fuzzy controller generated by the system with other types of controllers was implemented and embedded in sun spot a PID controller to control the same level plant of Quanser®

Análise de um controlador baseado no Jacobiano estimado da planta através de uma rede neural

This work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Análise de desempenho da rede neural artificial do tipo multilayer perceptron na era multicore

Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections

Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)

Projeto e Implementação em Ambiente Foundation Fieldbus de Filtragem Estocástica Baseada em Análise de Componentes Independentes (M175)

This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

Estimação clássica e Bayesiana em modelos de sobrevida com fração de cura

In Survival Analysis, long duration models allow for the estimation of the healing fraction, which represents a portion of the population immune to the event of interest. Here we address classical and Bayesian estimation based on mixture models and promotion time models, using different distributions (exponential, Weibull and Pareto) to model failure time. The database used to illustrate the implementations is described in Kersey et al. (1987) and it consists of a group of leukemia patients who underwent a certain type of transplant. The specific implementations used were numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation (own implementation) and Gibbs sampling as implemented in Winbugs. We describe the main features of the models used, the estimation methods and the computational aspects. We also discuss how different prior information can affect the Bayesian estimates

A New Approach for Real Time Fault Diagnosis in Induction Motors Based on Vibration Measurement

Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

Estendendo CRefine para o suporte de táticas de refinamento

The use of increasingly complex software applications is demanding greater investment in the development of such systems to ensure applications with better quality. Therefore, new techniques are being used in Software Engineering, thus making the development process more effective. Among these new approaches, we highlight Formal Methods, which use formal languages that are strongly based on mathematics and have a well-defined semantics and syntax. One of these languages is Circus, which can be used to model concurrent systems. It was developed from the union of concepts from two other specification languages: Z, which specifies systems with complex data, and CSP, which is normally used to model concurrent systems. Circus has an associated refinement calculus, which can be used to develop software in a precise and stepwise fashion. Each step is justified by the application of a refinement law (possibly with the discharge of proof obligations). Sometimes, the same laws can be applied in the same manner in different developments or even in different parts of a single development. A strategy to optimize this calculus is to formalise these application as a refinement tactic, which can then be used as a single transformation rule. CRefine was developed to support the Circus refinement calculus. However, before the work presented here, it did not provide support for refinement tactics. The aim of this work is to provide tool support for refinement tactics. For that, we develop a new module in CRefine, which automates the process of defining and applying refinement tactics that are formalised in the tactic language ArcAngelC. Finally, we validate the extension by applying the new module in a case study, which used the refinement tactics in a refinement strategy for verification of SPARK Ada implementations of control systems. In this work, we apply our module in the first two phases of this strategy

Avaliação da execução de aplicações orientadas à dados na arquitetura de redes em chip IPNoSys

The increasing complexity of integrated circuits has boosted the development of communications architectures like Networks-on-Chip (NoCs), as an architecture; alternative for interconnection of Systems-on-Chip (SoC). Networks-on-Chip complain for component reuse, parallelism and scalability, enhancing reusability in projects of dedicated applications. In the literature, lots of proposals have been made, suggesting different configurations for networks-on-chip architectures. Among all networks-on-chip considered, the architecture of IPNoSys is a non conventional one, since it allows the execution of operations, while the communication process is performed. This study aims to evaluate the execution of data-flow based applications on IPNoSys, focusing on their adaptation against the design constraints. Data-flow based applications are characterized by the flowing of continuous stream of data, on which operations are executed. We expect that these type of applications can be improved when running on IPNoSys, because they have a programming model similar to the execution model of this network. By observing the behavior of these applications when running on IPNoSys, were performed changes in the execution model of the network IPNoSys, allowing the implementation of an instruction level parallelism. For these purposes, analysis of the implementations of dataflow applications were performed and compared

Métricas de sistemas de middleware orientado a aspectos e Aplicação em um sistema de monitoramento de Poços de Petróleo

Nowadays, there are many aspect-oriented middleware implementations that take advantage of the modularity provided by the aspect oriented paradigm. Although the works always present an assessment of the middleware according to some quality attribute, there is not a specific set of metrics to assess them in a comprehensive way, following various quality attributes. This work aims to propose a suite of metrics for the assessment of aspect-oriented middleware systems at different development stages: design, refactoring, implementation and runtime. The work presents the metrics and how they are applied at each development stage. The suite is composed of metrics associated to static properties (modularity, maintainability, reusability, exibility, complexity, stability, and size) and dynamic properties (performance and memory consumption). Such metrics are based on existing assessment approaches of object-oriented and aspect-oriented systems. The proposed metrics are used in the context of OiL (Orb in Lua), a middleware based on CORBA and implemented in Lua, and AO-OiL, the refactoring of OIL that follows a reference architecture for aspect-oriented middleware systems. The case study performed in OiL and AO-OiL is a system for monitoring of oil wells. This work also presents the CoMeTA-Lua tool to automate the collection of coupling and size metrics in Lua source code

A reafirmação do bairro:um estudo geo-histórico do bairro do Alecrim na cidade de Natal-RN

By the end of the 21st Century, economy globalization trends to show a velocity process through which market being expanded characterized by an intense going on of the internationalization of finance, after that marginalizing the periphery of the social spaces. It is clear to see that this process occurred in those less developed countries happens in an accentuated way just because income distribution that is so regressive and also because the insufficient enclosing of the social programs, we find this situation in a big part of Brazilian cities. The marginalizing social economical process observed in Natal, a city located in the east coast part of Northeast region in Brazil and that owns a population upper to 778 thousand in habitants is nearly linked to the extension of goods and services commerce. The installation of new urban activities in the city pointed out tourist activity as the greater impulsive thing in the phenomenon promotion, most of them aiming to promote Natal to the national and international scenery. It privilege strongly in the South zone with economical implementations such as shopping s centers, supermarkets, and home buildings condominiums leading to a loss of functionality of some traditional district located in central areas of the city. Notwithstanding, some spaces, for instance Alecrim district officially created in 1911, has notably resisted to the expansion of the urban process pointed out in Natal in the last years. So that this put Alecrim District as a district with originally characteristics reaffirmed along the historical process form old times. The predominance of some residential characteristics such as the incidence of some villages and a concentration of a big and confuse popular commerce distributed along streets puts Alecrim District as a resistant space in Natal. The same way analyze Alecrim District under the prism of Historic Geography because we understand this way it accomplishes a fundamental role in the theoretical methodological development of our work, just when we analyze the time as a variant in our object of study. It is still inside this theoretical field that we carry out a brief reviewing about quarter/district definition, under the optic from several registered and scientific resources taken into account along this work, because we understand that it was necessary to think this important spatial unit especially to know exactly what we are referring to as a district and so we can reaffirm Alecrim as an important and traditional district to Natal and it has been resisting to spatial transformation verified in the last years in Natal city. To give support to our reflection we used methodological tools related to inhabitants lifestyles knowledge and also the study of Alecrim District as a space that promote a certain centrality in Natal as some indicators to keep original characteristics in the district in Natal

Control and chaos for vibro-impact and non-ideal oscillators

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

Application of a meshless method in electromagnetics

An improved meshless method is presented with an emphasis on the detailed description of this new computational technique and its numerical implementations by investigating the usefulness of a commonly neglected parameter in this paper. Two approaches to enforce essential boundary conditions are also thoroughly investigated. Numerical tests on a mathematical function is carried out as a means of validating the proposed method. It will be seen that the proposed method is more robust than the conventional ones. Applications in solving electromagnetic problems are also presented.