recursive extended least-squares
Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering
... based least squares iterative (LSI) algorithm and recursive least squares (RLS) algorithm are derived for the combined estimation of the state and ...based recursive ...
17
Robust Self Tuning Regulator of Time Varying Linear Systems with Bounded External Disturbances
... modified recursive least squares estimation algorithm RLS with dead zone cannot estimate parameters of ...modified recursive extended least squares estimation algorithm ...
8
Completely Recursive Least Squares and Its Applications
... We aim at performing accurate parameter and state estimation in complex situations using synchrophasor data. An approach of joint state-and-parameter estimation, which is different from the state augmentation, is ...
152
Decision Directed Recursive Least Squares MIMO Channels Tracking
... RLS algorithm is a low complexity iterative algorithm commonly used in equalization and filtering applications which is independent on the channel model [23]. The only parameter in the RLS algorithm that depends on the ...
10
Robust adaptive filtering using recursive weighted least squares with combined scale and variable forgetting factors
... memory length and needs rather a relatively long time to estimate the unknown coefficients. However, these coefficients are estimated accurately in stationary situa- tions. Moreover, RLS with fixed value of FF (FFF) is ...
22
Derivation of the fast pole-zero (ARMA) recursive least squares algorithm using geometric projections
... In this paper, the geometric approach used in [ 7 , 8 ] and [2] is extended to the derivation of a fast pole-zero (ARMA) Recursive Least Squares algorithmo The work is also an extension [r] ...
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Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks
... diffusion least-mean squares (LMS) [8, 9], diffusion sparse LMS [10–12], variable step size diffusion LMS (VSS-DLMS) [13, 14], diffusion recur- sive least squares (RLS) [6, 7], distributed ...
23
Performance Analysis of Adaptive Beamforming Algorithms for Orthogonal Frequency Division Multiplexing System
... FFT taken at the receiver side allows frequency domain beamformer to be implemented separately for individual subcarriers. Having individual beamformers to process its own subcarriers is an advantage for suppressing the ...
5
Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space
... Classical PCR, PLS and RR techniques are well known shrinkage estimators designed to deal with multicollinearity (see, e.g., Frank and Friedman, 1993, Montgomery and Peck, 1992, Jolliffe, 1986). The multicollinearity or ...
27
Maneuvering target tracking using fuzzy logic based recursive least squares filter
... standard recursive least squares filter (RLSF) [17,18] is quite well received in linear models with the unknown random characteristics of observa- ...
9
A derivation of a general order, multichannel, fast transversal, recursive least squares filter algorithm
... (1.15) Note that the least squares estimate of an arbitrary vector is thus obtained by premulti- plying by a matrix that is a function of only the input data vectors] The operator Pt(n) [r] ...
18
The generalized frequency domain adaptive filtering algorithm as an approximation of the block recursive least squares algorithm
... Acoustic echo cancellation (AEC) is a well-known application of adaptive filters in communication acoustics. To implement AEC for multichannel reproduction systems, powerful adaptation algorithms like the generalized ...
15
RLS Wiener Predictor with Uncertain Observations in Linear Discrete Time Stochastic Systems
... a recursive least-squares algorithm for the predictor and filter design in systems with non-independent uncer- tain observations, using covariance ...
7
ON RECURSIVE PARAMETRIC IDENTIFICATION OF WIENER SYSTEMS
... able data in order to calculate the estimates of pa- rameters of regression functions, also to get the un- known parameters of slopes, as well as a threshold of nonlinearities using off-line approach is shown in [13, ...
8
EC E -5 2 0 C o n t r o l S y s t e m
... the recursive least squares algorithm in a somewhat general context, and then implement it in Matlab and try a few simple ...the recursive least squares algorithm may seem to be ...
5
Extended Locality Preserving Partial Least Squares with Class Information
... Another experiment was conducted on the banknote authentication dataset (Dheeru and Karra Taniskidou, 2017). This data was ex- tracted from images taken from genuine and forged banknote-like specimens. The images were ...
9
Identification of MIMO Hammerstein models using Singular Value Decomposition approach
... In this paper, we present a new approach to identify multivariable Hammerstein systems based on the Singular Value Decomposition (SVD) method. The technique allows for the determination of the memoryless static ...
9
A Least Squares Finite Element Method for the Extended Maxwell System
... The paper is organized as follows: First we will lay definitions and pose the extended Maxwell system. Following that we formulate the finite element system postponing most of the analysis to Appendix A. Next, we ...
15
International Journal of Emerging Technology and Advanced Engineering
... mean squares (LMS) algorithms are class of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal ...
5
Floating point error analysis of recursive least squares and least means squares adaptive filters
... This sequence is a zero mean white independent random process which has a variance related to signal statistics, the weight vector covariance, and the floating point errorso The calculat[r] ...
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