Analogue adaptive filters represent an important niche in adaptive-filter theory and practice.
The paper provides an overview of the field. Important adaptive algorithms, filter structures …

An adaptive filter is a computational device that attempts to model the relationship between
two signals in real time in an iterative manner. Adaptive filters are often realized either as a …

Conventional gradient-type adaptive filters use the fixed convergence factor μ which is
normally chosen to be the same for all the filter parameters. In this paper, we propose to use …

Owing to the powerful digital signal processors and the development of advanced adaptive
algorithms there are a great number of different applications in which adaptive filters are …

It is proposed that the convergence factor mu in the adaptive filter can be made time-varying
according to the gradient of the performance surface. Computer simulations show that when …

This text emphasizes the intricate relationship between adaptive filtering and signal analysis-
highlighting stochastic processes, signal representations and properties, analytical tools …

Adaptive filters are systems that adjust themselves to a changing environment. They are
designed to meet certain performance specifications and are expected to perform …

This paper presents an approach for implementing continuous-time adaptive recursive
filters. The resulting filters should be capable of operating on much higher signal …

For an adaptive filter with N adjustable coefficients or weights, the" error surface" is a plot, in
N+ I dimensions, of the mean-squared error versus the N coefficient values. If the adaptive …

Most adaptive filters are inherently nonlinear and time-variant systems. The nonlinearities in
the update equations tend to lead to difficulties in the study of their steady-state performance …