An Adaptive Amplifier System for Wireless Sensor Network Applications

Lovay, Mónica; Peretti, Gabriela; Romero, Eduardo; Marques, Carlos Alberto

doi:10.1155/2012/762927

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Table shows the parameters adopted by the algorithm for each case of study and proposed scenario. These values are obtained from exploratory experiments, considering different population sizes (between 10 and 100 individuals) and crossover probabilities (0.7, 0.8, and 0.9), taking into account . For each case, it is chosen the combination of parameters that allows the algorithm to reach the best performance.…”

Section: Ga Settings and Behaviormentioning

confidence: 99%

Genetic algorithms applied to the design of robust biquadratic filters

Lovay

Romero

Peretti

2018

Int J Numerical Modelling

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This work presents a design methodology for discrete active RC biquadratic filters based on genetic algorithm (GA). The main difference with other methods is the consideration of the passive sensitivities during the optimization process.The GA delivers the values of resistors and capacitors (from E series) that comply with the desired specifications and minimize at the same time the sensitivities. This characteristic leads to filters that exhibit low deviations in their functional parameters, despite drifts in the values of passive components. Additionally, the method allows the designer to establish the gain in the passband. In this way, it overcomes the problem of low gain values observed in some of the solutions given by other authors. The paper presents an evaluation campaign that considers 12 designs for showing the robustness of the method. This study analyses the results delivered by the GA at transfer function level using MATLAB. Subsequent evaluations validate these results by using SPICE simulations. Following these procedures, it is observed a proper matching between the behaviors of the filters predicted by the GA and the simulated ones. The performance comparison with other heuristics (solving the same problem) shows that our proposal is well suited for the design of active filters. The stochastic nature of the GA allows obtaining different design alternatives in each run. This feature gives the designer the possibility to choose between several options that are more appropriate for a particular design problem. The paper also provides a simple guideline for dealing with the results from the iterative executions of the GA. The design method requires tools that are usual to find in the industry. Practitioners can straightforwardly implement it, even those that are nonspecialists in heuristics.

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Section: Ga Settings and Behaviormentioning

confidence: 99%

Genetic algorithms applied to the design of robust biquadratic filters

Lovay

Romero

Peretti

2018

Int J Numerical Modelling

Self Cite

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“…El esquema de adaptación se valida mediante procedimientos de inyección de fallas, los que están aceptados en la comunidad para el tratamiento de problemas similares [16], [17]. Para implementar un experimento que incluya inyección y simulación de fallas se requieren dos elementos: un modelo de simulación del sistema bajo test y un modelo de falla compatible.…”

Section: A Procedimiento De Simulación En Condiciones Normales Y Bajunclassified

Implementation of an Adaptive Filter using an Evolvable Hardware Strategy

Lovay¹,

Peretti²,

Romero³

2015

IEEE Latin Am. Trans.

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This paper explores the feasibility of an adaptive scheme to tolerate degradations in a high-order low-pass filter, taken as a case study. The adaptation is achieved through an evolvable hardware strategy that employs reconfigurable hardware and a genetic algorithm (GA). For establishing the filter reconfiguration, it is considered that it is tested periodically during in-field operation using Transient Analysis Method (TRAM). If TRAM founds that the filter does not fulfill the specifications, then the AG, which runs on an external computer, searches a new set of configurable parameters that allows the filter reaching the specifications. Then, the hardware is configured with these new parameters for continuing its normal operation. For the proposed scheme, simulation results show the TRAM feasibility when certain restrictions are taken for its implementation. The AG evaluation is performed through fault simulation, using four fault models that consider deviations in circuital parameters. The results show that AG founds, in all fault conditions simulated, solutions with errors smaller than the tolerable ones, demonstrating the feasibility of the proposed scheme.

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