L. Tobaldini Neto

  • Citations Per Year
Learn More
This paper shows further results on the EKF-RTRL (extended Kalman filter-real time recurrent learning) equalizer comparing its performance with the PSP-LMS (per survivor processing-least mean squares) equalizer for fast fading selective frequency channels using the WSS_US (wide sense stationary-uncorrelated scattering) model. The EKF-RTRL is a symbol by(More)
This paper investigates the application of partially recurrent artificial neural networks (ANN) in the flow estimation for Sao Francisco river that feeds the hydroelectric power plant of Sobradinho. An Elman neural network was used, suitably arranged to receive samples of the flow time series data available for Sao Francisco river shifted by one month. The(More)
The main goal of this paper is to measure the efficiency in converting energy use in peoplepsilas earnings for some Rio de Janeiro municipalities, Brazil. We used CCR and BCC classical data envelopment analysis (DEA) models, with one input (per capita energy use) and two outputs (average temperature and average monthly earnings). The results indicate that(More)
A novel, parallel, high-order, central essentially non-oscillatory (CENO), cell-centered, finite-volume scheme is developed and applied to large-eddy simulation (LES) of turbulent premixed flames. The high-order CENO finite-volume scheme is applied to the solution of the Favre-filtered Navier-Stokes equations governing turbulent flows of a(More)
  • 1