The paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regression data to being Gaussian or white. The framework is based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Abstract: In this paper, the fault diagnosis of non linear systems based on a adaptive ¯lter is deve...
We study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perf...
This paper develops a unified approach to the analysis and design of adaptive filters with error non...
This article provides an overview of an energy-based approach to the study of the steady-state and t...
This paper introduces a new approach for the performance analysis of adaptive filter with error satu...
A unified approach to the steady-state mean square error (MSE) and tracking performance analyses for...
Most adaptive filters are inherently nonlinear and time variant systems. The nonlinearities in the u...
This paper uses averaging analysis to study the mean-square performance of adaptive filters, not onl...
This paper derives an expression for the optimal error nonlinearity in adaptive filter design. Usi...
Recently, a novel class of nonlinear adaptive filters, called spline adaptive filters (SAFs), has be...
In this paper, we consider the class of adaptive filters with error nonlinearities. In particular, w...
Employing a recently introduced unified adaptive filter theory, we show how the performance of a lar...
This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in th...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Abstract: In this paper, the fault diagnosis of non linear systems based on a adaptive ¯lter is deve...
We study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perf...
This paper develops a unified approach to the analysis and design of adaptive filters with error non...
This article provides an overview of an energy-based approach to the study of the steady-state and t...
This paper introduces a new approach for the performance analysis of adaptive filter with error satu...
A unified approach to the steady-state mean square error (MSE) and tracking performance analyses for...
Most adaptive filters are inherently nonlinear and time variant systems. The nonlinearities in the u...
This paper uses averaging analysis to study the mean-square performance of adaptive filters, not onl...
This paper derives an expression for the optimal error nonlinearity in adaptive filter design. Usi...
Recently, a novel class of nonlinear adaptive filters, called spline adaptive filters (SAFs), has be...
In this paper, we consider the class of adaptive filters with error nonlinearities. In particular, w...
Employing a recently introduced unified adaptive filter theory, we show how the performance of a lar...
This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in th...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Abstract: In this paper, the fault diagnosis of non linear systems based on a adaptive ¯lter is deve...
We study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perf...