We provide a time domain analysis of the robustness and sta-bility performance for coupled adaptive algorithms of gradi-ent type. The considered coupling may occur inherently as well as by desire of the designer. The presented analyses fo-cus on system identification. Examples are presented to inves-tigate convergence and steady-state behaviour by simulations which are compared to theory. In particular, the presented ap-proach allows for a deeper understanding of cascaded adap-tive filters in terms of robustness and l2-stability. Index Terms — Adaptive filters, system identification, robust-ness, l2-stability, error bounds
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
In this paper, we propose an approach to the transient and steady-state analysis of the affine combi...
The goal is to present the theory of adaptive signal processing and cover several engineering applic...
We provide a time domain analysis of the robustness and sta-bility performance for coupled adaptive ...
This work is concerned with robustness, convergence, and stability of adaptive filtering (AF) type a...
This thesis examines the robustness properties of various adaptive systems for control, filtering, a...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Abstmct-We derive a broad range of theoretical results concerning the performance and limit.tioas of...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Abstract—We introduce a new family of algorithms to exploit sparsity in adaptive filters. It is base...
This work is concerned with robustness, convergence, and stability of adaptive filtering (AF) type a...
This article provides an overview of an energy-based approach to the study of the steady-state and t...
When a linear filter is faced with fluctuations of the environment, adaptive filtering (AF) is a mea...
Simplicity, flexibility, and reliability are three important aspects of practical adaptive filtering...
Most adaptive filters are inherently nonlinear and time variant systems. The nonlinearities in the u...
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
In this paper, we propose an approach to the transient and steady-state analysis of the affine combi...
The goal is to present the theory of adaptive signal processing and cover several engineering applic...
We provide a time domain analysis of the robustness and sta-bility performance for coupled adaptive ...
This work is concerned with robustness, convergence, and stability of adaptive filtering (AF) type a...
This thesis examines the robustness properties of various adaptive systems for control, filtering, a...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Abstmct-We derive a broad range of theoretical results concerning the performance and limit.tioas of...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Abstract—We introduce a new family of algorithms to exploit sparsity in adaptive filters. It is base...
This work is concerned with robustness, convergence, and stability of adaptive filtering (AF) type a...
This article provides an overview of an energy-based approach to the study of the steady-state and t...
When a linear filter is faced with fluctuations of the environment, adaptive filtering (AF) is a mea...
Simplicity, flexibility, and reliability are three important aspects of practical adaptive filtering...
Most adaptive filters are inherently nonlinear and time variant systems. The nonlinearities in the u...
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
In this paper, we propose an approach to the transient and steady-state analysis of the affine combi...
The goal is to present the theory of adaptive signal processing and cover several engineering applic...