N.J. Bershad

Overview

Best Publications

• Random differential equations in science and engineering

  Unknown

  413
  Citations

• Analysis of the normalized LMS algorithm with Gaussian inputs

  Unknown

  272
  Citations

• Time delay estimation using the LMS adaptive filter--Dynamic behavior

  Unknown

  230
  Citations

• An Affine Combination of Two LMS Adaptive Filters—Transient Mean-Square Analysis

  N.J. Bershad;J.C.M. Bermudez;J.-Y. Tourneret

  197
  Citations

• Adaptive recovery of a chirped sinusoid in noise. II. Performance of the LMS algorithm

  N.J. Bershad;O.M. Macchi

  174
  Citations

• Mean weight behavior of the filtered-X LMS algorithm

  O.J. Tobias;J.C.M. Bermudez;N.J. Bershad

  161
  Citations

• Comments on and additions to "An adaptive recursive LMS filter"

  C.R. Johnson;M.G. Larimore;P.L. Feintuch;N.J. Bershad

  121
  Citations

• A statistical analysis of the affine projection algorithm for unity step size and autoregressive inputs

  S.J.M. de Almeida;J.C.M. Bermudez;N.J. Bershad;M.H. Costa

  120
  Citations

• A frequency domain model for 'filtered' LMS algorithms-stability analysis, design, and elimination of the training mode

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  117
  Citations

• Neural networks for modeling nonlinear memoryless communication channels

  Unknown

  97
  Citations

• Stochastic analysis of the filtered-X LMS algorithm in systems with nonlinear secondary paths

  M.H. Costa;J.C.M. Bermudez;N.J. Bershad

  94
  Citations

• Stochastic Analysis of a Stable Normalized Least Mean Fourth Algorithm for Adaptive Noise Canceling With a White Gaussian Reference

  E. Eweda;N. J. Bershad

  89
  Citations

• Analysis of stochastic gradient identification of Wiener-Hammerstein systems for nonlinearities with Hermite polynomial expansions

  N.J. Bershad;P. Celka;S. McLaughlin

  89
  Citations

• Neural network modeling and identification of nonlinear channels with memory: algorithms, applications, and analytic models

  Unknown

  86
  Citations

• On error-saturation nonlinearities in LMS adaptation

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  85
  Citations

• Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements

  N.J. Bershad;P. Celka;J.-M. Vesin

  84
  Citations

• Stochastic gradient identification of polynomial Wiener systems: analysis and application

  P. Celka;N.J. Bershad;J.-M. Vesin

  83
  Citations

• The complex LMS adaptive algorithm--Transient weight mean and covariance with applications to the ALE

  Unknown

  77
  Citations

• Stochastic Analysis of the LMS and NLMS Algorithms for Cyclostationary White Gaussian Inputs

  Unknown

  76
  Citations

• Tracking characteristics of the LMS adaptive line enhancer-response to a linear chirp signal in noise

  Unknown

  76
  Citations

• Statistical analysis of the single-layer backpropagation algorithm. II. MSE and classification performance

  N.J. Bershad;J.J. Shynk;P.L. Feintuch

  60
  Citations

• Statistical analysis of the single-layer backpropagation algorithm. I. mean weight behavior

  N.J. Bershad;J.J. Shynk;P.L. Feintuch

  50
  Citations

• A nonlinear analytical model for the quantized LMS algorithm-the arbitrary step size case

  J.C.M. Bermudez;N.J. Bershad

  40
  Citations

• Analytic behavior of the LMS adaptive line enhancer for sinusoids corrupted by multiplicative and additive noise

  M. Ghogho;M. Ibnkahla;N.J. Bershad

  35
  Citations

• Stochastic analysis of adaptive gradient identification of Wiener-Hammerstein systems for Gaussian inputs

  N.J. Bershad;S. Bouchired;F. Castanie

  32
  Citations

• Fast coupled adaptation for sparse impulse responses using a partial haar transform

  N.J. Bershad;A. Bist

  31
  Citations

• Stochastic analysis of the LMS algorithm with a saturation nonlinearity following the adaptive filter output

  M.H. Costa;J.C.M. Bermudez;N.J. Bershad

  30
  Citations

• Stochastic Analysis of the LMS Algorithm for System Identification With Subspace Inputs

  N.J. Bershad;J.C.M. Bermudez;J.-Y. Tourneret

  22
  Citations

• Performance comparison of RLS and LMS algorithms for tracking a first order Markov communications channel

  N.J. Bershad;S. McLaughlin;C.F.N. Cowan

  21
  Citations

• Mean weight behavior of the Filtered-X LMS algorithm

  O.J. Tobias;J.C.M. Bermudez;N.J. Bershad;R. Seara

  20
  Citations