Comparison of adaptive lattice filters to LMS transversal filters for sinusoidal cancellation

Adaptive tracking of linear time-variant systems by extended RLS algorithms

“…This value was used as a first approximation to the optimal value, and a more exact value was determined experimentally by minimizing the output prediction error with respect to the adaptation parameter. It is known that in the chirped case, the adaptive-algorithm-update behaves as a feedback path, which not only updates the filter weights (FIR filter) but also fluctuates the weights to create poles (IIR) in the filter transfer function [20], [21]. Therefore, the filters generally perform better than the linear theory predicts.…”

Performance Analysis of Adaptive Noise Canceller Employing NLMS Algorithm

“…Kalman filter theory was utilized in his work to devise a novel class of adaptive filtering schemes for achieving fast convergence of the transversal filter's tap weights to their optimum values [9]. A comparison of the performances of RLSL (Recursive Least Squares Lattice) and normalized step-size SGL (Stochastic Gradient Lattice) schemes to that of the LMS transversal scheme for cancelling sinusoidal interferences was made in [10]. The experimental results showed that the adaptive lattice filters is more advantageous than LMS transversal filter, which makes them more preferable adaptive noise canceller (ANC) filter structure if the increased computational cost can be accepted.…”

Strong Spurious Noise Suppression for an FMCW SAR

“…The rejection methods can be classified as those based upon adaptive filtering and those based upon transform domain processing structures. The adaptive filters, such as least mean square estimation (LMS) adaptive filters [11][12][13] and lattice adaptive filters [14], usually adopt iterative algorithms to reduce convergence time. The iterative algorithm relates to many operations, such as multiplications and trigonometry operations.…”