The performances of various adaptive filtering algorithms are evaluated based on their convergence rate, computational requirements, misadjustment, and numerical robustness. Improvements to the performance of adaptive filters by using new adaptation algorithms and by the use of recursive structures are reported in the thesis.Master of Scienc
We revisit the classical algorithms for searching over sorted sets to introduce an algorithm refinem...
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
An adaptive filter is a digital filter that can adjust its coefficients to give the best match t An ...
In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S...
In this book, the authors provide insights into the basics of adaptive filtering, which are particul...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Abstract — This paper presents a comparative performance study between the recently proposed time-va...
Abstract: — The numerically stable version of fast recursive least squares (NS-FRLS) algorithms rep...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
The Recursive Least Squares algorithm (RLS) is utilized in digital signal processing as an adaptive ...
This thesis is designed to investigate adaptive filtering problem based on QR decomposition techniqu...
Abstract: In this paper, we present a new version of numerically stable fast recursive least squares...
Adaptive filtering is useful in any application where the signals or the modeled system vary over ti...
In this paper we offer a ”birds eye view” of the field of adaptive filtering with the aim of suggest...
DoctorThe objective of this thesis is to develop new algorithm forimproving the convergence performa...
We revisit the classical algorithms for searching over sorted sets to introduce an algorithm refinem...
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
An adaptive filter is a digital filter that can adjust its coefficients to give the best match t An ...
In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S...
In this book, the authors provide insights into the basics of adaptive filtering, which are particul...
Adaptive filtering can be used to characterize unknown systems in time-variant environments. The mai...
Abstract — This paper presents a comparative performance study between the recently proposed time-va...
Abstract: — The numerically stable version of fast recursive least squares (NS-FRLS) algorithms rep...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
The Recursive Least Squares algorithm (RLS) is utilized in digital signal processing as an adaptive ...
This thesis is designed to investigate adaptive filtering problem based on QR decomposition techniqu...
Abstract: In this paper, we present a new version of numerically stable fast recursive least squares...
Adaptive filtering is useful in any application where the signals or the modeled system vary over ti...
In this paper we offer a ”birds eye view” of the field of adaptive filtering with the aim of suggest...
DoctorThe objective of this thesis is to develop new algorithm forimproving the convergence performa...
We revisit the classical algorithms for searching over sorted sets to introduce an algorithm refinem...
Mechanisms for adapting models, filters, decisions, regulators and soon to changing properties of a ...
An adaptive filter is a digital filter that can adjust its coefficients to give the best match t An ...