In this paper, a new robust adaptive FIR filter algorithm with variable forgetting factor for time-varying parameters estimation in the presence of impulsive noise is discussed. The proposed algorithm is based on the robust recursive least square and parallel adaptation recursive least square algorithms combination. A scalar parameter controls the switching process between these two algorithms,...

Surface electromyograms (EMGs) are valuable in the pathophysiological study and clinical treatment for dystonia. These recordings are critically often contaminated by cardiac artefact. Our objective of this study was to evaluate the performance of an adaptive noise cancellation filter in removing electrocardiogram (ECG) interference from surface EMGs recorded from the trapezius muscles of patie...

This paper presents an adaptive filtering method to remove ocular artifacts in the electroencephalogram (EEG) records. The major concern in analyzing EEG signal is the presence of ocular artifacts in EEG records caused due to various factors. It is essential to design specific filters to remove the artifacts in EEG records. Here, we proposed an adaptive filtering method that uses RLS (Recursive...

In a number of adaptive filtering applications, non-Wiener effects have been observed for the (normalized) leastmean-square algorithm. These effects can lead to performance improvements over the fixed Wiener filter with the same model structure, and are characterized by dynamic behavior of the adaptive filter weights. Here we investigate whether such non-Wiener effects can also occur in the rec...

A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. This paper discusses the identification of the parameters at the antecedent and consequent parts of the fuzzy model. For the antecedent fuzzy parameters, genetic algorithm is used to tune ...

Channel State information can be determined by adaptive filtering algorithms for wireless channels. For slow fading channels, simplified channel estimators can be exploited such as Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE). But for fast fading channels, the matrix inversion required in case of LMMSE has to be taken recursively which increase the complexity. Under suc...

In combining principal and minor components analysis, a parallel extraction method based on recursive least square algorithm is suggested to extract the principal components of the input vectors. After the extraction, the error covariance matrix obtained in the learning process is used to perform minor components analysis. The minor components found are then pruned so as to achieve a higher com...

The on-line least square parameters (electrical and mechanical) identification method of the separately DC motor is presented in this paper. The parameters of the DC machine are time dependent; therefore, for the DC drive control the on-line parameters identification procedure is mandatory. By knowing accurately the DC motor parameters, the parameters of the DC speed and current cascade control...

In this paper, the parameter estimation of thermal dynamic discrete-time system for heating, ventilating and air conditioning (HVAC) is studied using recursive least square method. Parameters are estimated by using recursive least square method. Thermodynamic model of indoor test bed is formulated by outdoor temperature, HVAC power consumption, and thermal noise and estimated thermal dynamic pa...

This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation...