The filtered-x least mean square (FXLMS) algorithm is widely used for active noise control (ANC) systems. However, due to the fixed step-size of FXLMS algorithm being used, the FXLMS algorithm results in a compromise between noise reduction performance and convergence speed. Therefore, this ...
The filtered-x least mean square (FXLMS) algorithm is widely used for active noise control (ANC) systems. However, due to the fixed step-size of FXLMS algorithm being used, the FXLMS algorithm results in a compromise between noise reduction performance and convergence speed. Therefore, this pape...
The filtered-x least mean square algorithm (FxLMS) is a widely used technique in active noise control. In a conventional FxLMS algorithm, the value of convergence coefficient is kept constant which may not yield optimum performance if frequency of the primary noise changes. For some frequencies, ...
Further we work to modify these basic algorithms so as to obtain Normalized Least Mean Square algorithm, Fractional Least Mean Square algorithm, Differential Normalized Least Mean Square algorithm, Filtered-x Least Mean Square algorithm etc. In this paper we work to provide an improved approach for...
A novel variable step-size filtered-x least mean square algorithm for continually varying noisePuri, AmritaModak, Subodh V.Gupta, KshitijINTER-NOISE and NOISE-CON Congress and Conference Proceedings
fxlms = dsp.FilteredXLMSFilter(Name,Value) Description fxlms= dsp.FilteredXLMSFilterreturns a filtered-x least mean square FIR adaptive filter System object,fxlms. This System object is used to compute the filtered output and the filter error for a given input and desired signal. ...
A new active noise control algorithm is presented. It uses two cross-coupled filtered-X least mean square (LMS) adaptive filters to perform noise control and on-line error-path modeling simultaneously. A lattice structure is developed to decorrelate the reference input, which improves the convergenc...
The presence of a transfer function in the error path, as in the case of active noise control requires a filtered update of the LMS (least mean square) algorithm. To ensure convergence of the algorithm, the input to the error correlator ... Bjarnason,E. 被引量: 11发表: 1993年 加载更多...
An application of the Least Mean Square Algorithm for active noise cancellation is presented here. Potential applications of the algorithm are in audio noise reduction and wireless signal jamming. Simulation results based on the filtered x-LMS algorithm are presented with the regular LMS algorithm modi...
To ensure convergence of the algorithm, the filtered-x least mean square (FX-LMS) algorithm finds its application where input to the error correlator is filtered by a copy of the auxiliary error path transfer function, whereas the FX-LMS results in very slow convergence performance in case of...