A unified approach to the steady-state and tracking analyses of adaptive filters
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This paper develops a framework for the mean-square analysis of adaptive filters with general data and error nonlinearities. The approach relies on energy conservation arguments and is carried out without restrictions on the probability distribution of the ...
This paper presents a Model Predictive Control (MPC) scheme for nonlinear continuous-time systems where an economic stage cost, which is not a measure of the distance to a desired set point, is combined with a classic stabilizing stage cost. The associated ...
The random trip model was recently proposed as a generic mobility model that contains many particular mo-bility models, including the widely-known random waypoint and random walks, and accommodates more realistic sce-narios. The probability distribution of ...
Combination approaches can improve the performance of adaptive schemes. In this paper, we study the steady-state performance of an adaptive convex combination of transversal filters and show its universality in the sense that the combination performs, in s ...
The steady-state performance of adaptive filters can vary significantly when they are implemented in finite precision arithmetic, which makes it vital to analyse their performance in a quantized environment. Such analyses can become difficult for adaptive ...
This article provides an overview of an energy-based approach to the study of the steady-state and transient performances of adaptive filters. The analysis employs energy-conservation arguments and is based on studying the energy flow through each iteratio ...
This paper develops a unified approach to the analysis and design of adaptive filters with error nonlinearities. In particular, the paper performs stability and steady-state analysis of this class of filters under weaker conditions than what is usually enc ...
The author begins by discussing the fundamental energy relation, then goes on to consider steady state analysis and tracking analysis. Adaptive filtering is also mentioned in the study. ...
An alternative structure for adaptive linear prediction is proposed in which the adaptive filter is replaced by a cascade of inde- pendently adapting, low-order stages, and the prediction is generated by means of successive refinements. When the adaptation ...
Most adaptive filters are inherently nonlinear and time variant systems. The nonlinearities in the update equations of these filters usually lead to significant difficulties in the study of their performance. This paper develops a new feedback approach to ...
