Plant identification via adaptive combination of transversal filters
Signal Processing - Signal processing in UWB communications
Adaptive Processing over Distributed Networks
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Adaptive combination of proportionate filters for sparse echo cancellation
IEEE Transactions on Audio, Speech, and Language Processing
An output signal based combination of two NLMS adaptive algorithms
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Diffusion LMS strategies for distributed estimation
IEEE Transactions on Signal Processing
Improved adaptive filtering schemes via adaptive combination
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Steady-state MSE performance analysis of mixture approaches to adaptive filtering
IEEE Transactions on Signal Processing
Transient and steady-state analysis of the affine combination of two adaptive filters
IEEE Transactions on Signal Processing
Unbiased model combinations for adaptive filtering
IEEE Transactions on Signal Processing
Adaptively biasing the weights of adaptive filters
IEEE Transactions on Signal Processing
Diffusion least-mean squares with adaptive combiners: formulation and performance analysis
IEEE Transactions on Signal Processing
Adaptive combination of subband adaptive filters with selective partial updates
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
An adaptive approach for the identification of improper complex signals
Signal Processing
An adaptive sensor array using an affine combination of two filters
SITE'12 Proceedings of the 11th international conference on Telecommunications and Informatics, Proceedings of the 11th international conference on Signal Processing
A novel adaptive diversity achieving channel estimation scheme for LTE
Proceedings of the first ACM international workshop on Practical issues and applications in next generation wireless networks
Adaptive mixture methods based on Bregman divergences
Digital Signal Processing
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Combination approaches provide an interesting way to improve adaptive filter performance. In this paper, we study the mean-square performance of a convex combination of two transversal filters. The individual filters are independently adapted using their own error signals, while the combination is adapted by means of a stochastic gradient algorithm in order to minimize the error of the overall structure. General expressions are derived that show that the method is universal with respect to the component filters, i.e., in steady-state, it performs at least as well as the best component filter. Furthermore, when the correlation between the a priori errors of the components is low enough, their combination is able to outperform both of them. Using energy conservation relations, we specialize the results to a combination of least mean-square filters operating both in stationary and in nonstationary scenarios. We also show how the universality of the scheme can be exploited to design filters with improved tracking performance.