Active noise and vibration control (ANC) has become an important application area for adaptive filters. The most popular adaptive algorithm used for ANC is the Filtered-X LMS (FXLMS) algorithm [1,2]. This algorithm is a modification of the well known LMS algorithm. The reference signal is filtered so as to compensate for filters inherent in the electro-acoustic adaptation loop. These additional...

The aim of this study is to evaluate the method for compensation magnetic field interference from mains, which consists primarily components with a frequency 50 (60) Hz and its multiples. setup compensates interfering using three Helmholtz coils, sensors, digital processing unit, power amplifiers. unit implements an adaptive least-mean-square (LMS) algorithm calculate currents through coils tha...

An adaptive iterative receiver for layered spacetime coded (LSTC) systems is proposed. The proposed receiver, based on a joint adaptive iterative detection and decoding algorithm, adaptively suppresses and cancels co-channel interference. The LMS algorithm and maximum a posteriori (MAP) algorithm are utilized in the receiver structure. A partially filtered gradient LMS (PFGLMS) algorithm is als...

The least-mean-squares (LMS) algorithm is the most popular algorithm in adaptive filtering. Several variable step-size strategies have been suggested to improve the performance of the LMS algorithm. These strategies enhance the performance of the algorithm but a major drawback is the complexity in the theoretical analysis of the resultant algorithms. Researchers use several assumptions to find ...

This paper mainly studied the LMS adaptive filter algorithm to the Volterra system model. Through the construction of the second order Volterra system model, the application of respectively selecting the first order and second order variable step length de-correlation Volterra LMS algorithm in gaussian noise environment, when the input signals in different correlation coefficient, the iteration...

Adaptive estimation of the linear coefficient vector in truncated expansions is considered for the purpose of modeling noisy, recurrent signals. The block LMS (BLMS) algorithm, being the solution of the steepest descent strategy for minimizing the mean square error in a complete signal occurrence, is shown to be steady-state unbiased and with a lower variance than the LMS algorithm. It is demon...

The convergence speed of the conventional adaptive LMS algorithms for time delay estimation (TDE) is highly dependent on the spectral distribution of the desired random source signals of interest, thus the performance of TDE might be degraded, dramatically. To solve this problem, in this letter, a DCT-transform domain constrained adaptive normalized-LMS filtering scheme, referred to as the adap...

In the areas of acoustic research or applications that deal with not-precisely-known or variable conditions, a method of adaptation to the uncertainness or changes is usually necessary. When searching for an adaptation algorithm, it is hard to overlook the least mean squares (LMS) algorithm. Its simplicity, speed of computation, and robustness has won it a wide area of applications: from teleco...