# Azzedine Zerguine, Dhahran SA

## Azzedine Zerguine, Dhahran SA

Patent application number | Description | Published |
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20120106357 | VARIABLE STEP-SIZE LEAST MEAN SQUARE METHOD FOR ESTIMATION IN ADAPTIVE NETWORKS - The variable step-size least mean square method for estimation in adaptive networks uses a variable step-size to provide estimation for each node in the adaptive network, where the step-size at each node is determined by the error calculated for each node, as opposed to conventional least mean square algorithms used in adaptive filters and the like, where the choice of step-size reflects a tradeoff between misadjustment and the speed of adaptation. | 05-03-2012 |

20120109600 | VARIABLE STEP-SIZE LEAST MEAN SQUARE METHOD FOR ESTIMATION IN ADAPTIVE NETWORKS - The variable step-size least mean square method for estimation in adaptive networks uses a variable step-size to provide estimation for each node in the adaptive network, where the step-size at each node is determined by the error calculated for each node, as opposed to conventional least mean square algorithms used in adaptive filters and the like, where the choice of step-size reflects a tradeoff between misadjustment and the speed of adaptation. | 05-03-2012 |

20120135691 | NOISE-CONSTRAINED DIFFUSION LEAST MEAN SQUARE METHOD FOR ESTIMATION IN ADAPTIVE NETWORKS - The noise-constrained diffusion least mean square method for estimation in adaptive networks is based on the Least Mean Squares (LMS) algorithm. The method uses a variable step size in which the step-size variation rule results directly from the noise constraint. | 05-31-2012 |

20120257668 | TIME-VARYING LEAST-MEAN-FOURTH-BASED CHANNEL EQUALIZATION METHOD AND SYSTEM - The time-varying least-mean-fourth-based channel equalization method is an automated procedure that provides an adaptive equalizer in a CDMA receiver. Equalizer filter coefficients are estimated using a least-mean-fourth (LMF) error calculation based on a training set of symbols sent by the transmitter. When the LMF error calculation is combined with a power-of-two quantization (PTQ) process, superior receiver performance is achieved in a time-varying CDMA channel operating in non-Gaussian noise environments. | 10-11-2012 |

20130110478 | APPARATUS AND METHOD FOR BLIND BLOCK RECURSIVE ESTIMATION IN ADAPTIVE NETWORKS | 05-02-2013 |

20130254250 | SYSTEM AND METHOD FOR LEAST MEAN FOURTH ADAPTIVE FILTERING - The system and method for least mean fourth adaptive filtering is a system that uses a general purpose computer or a digital circuit (such as an ASIC, a field-programmable gate array, or a digital signal processor that is programmed to utilize a normalized least mean fourth algorithm. The normalization is performed by dividing a weight vector update term by the fourth power of the norm of the regressor. | 09-26-2013 |

20140310326 | ADAPTIVE FILTER FOR SYSTEM IDENTIFICATION - The adaptive filter for system identification is an adaptive filter that uses an algorithm in the feedback loop that is designed to provide better performance when the unknown system model has sparse input, i.e., when the filter has only a few non-zero coefficients, such as digital TV transmission channels and echo paths. In a first embodiment, the algorithm is the Normalized Least Mean Square (NLMS) algorithm in which the filter coefficients are updated at each iteration according to: | 10-16-2014 |

20150263701 | ADAPTIVE FILTER FOR SYSTEM IDENTIFICATION - The adaptive filter for sparse system identification is an adaptive filter that uses an algorithm in the feedback loop that is designed to provide better performance when the unknown system model is sparse, i.e., when the filter has only a few non-zero coefficients, such as digital TV transmission channels and echo paths. The algorithm is a least mean square algorithm with filter coefficients updated at each iteration, as well as a step size that is also updated at each iteration. The adaptive filter may be implemented on a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or by field-programmable gate arrays (FPGAs). | 09-17-2015 |