Acoustic echo cancellation represents one of the most challenging system identification
problems. The most used adaptive filter in this application is the popular normalized least …

This paper proposes an online parameter estimation method based on a discrete-time
dynamic model for the interior permanent-magnet synchronous motors (IPMSMs). The …

This paper proposes an online identification method that can accurately estimate the stator
resistance and dq-axis stator inductances for the effective model-based sensorless control of …

In this paper, a variable step-size widely linear complex-valued affine projection algorithm
(VSS-WLCAPA) is proposed for processing noncircular signals. The variable step-size …

The adaptive algorithms used for acoustic echo cancellation (AEC) have to provide (1) high
convergence rates and good tracking capabilities, since the acoustic environments imply …

The normalized subband adaptive filter (NSAF) presented by Lee and Gan can obtain faster
convergence rate than the normalized least-mean-square (NLMS) algorithm with colored …

In acoustic echo cancellation (AEC) applications, where the acoustic echo paths are
extremely long, the adaptive filter works most likely in an under-modeling situation. Most of …

The normalized least-mean-square (NLMS) adaptive filter is widely used in system
identification. In this paper, we develop an optimized NLMS algorithm, in the context of a …

A family of adaptive-filtering algorithms that uses a variable step size is proposed. A variable
step size is obtained by minimizing the energy of the noise-free a posteriori error signal …

Regularization plays a fundamental role in adaptive filtering. An adaptive filter that is not
properly regularized will perform very poorly. In spite of this, regularization in our opinion is …