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Recursive Least Squares

Derivation of the fast pole-zero (ARMA) recursive least squares algorithm using geometric projections

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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Maneuvering target tracking using fuzzy logic based recursive least squares filter

Maneuvering target tracking using fuzzy logic based recursive least squares filter

... logic-based recursive least squares filter (FLRLSF) is presented for maneuvering target tracking (MTT) in situations of observations with unknown random ...standard recursive least ...

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Recursive least squares background prediction of univariate syndromic surveillance data

Recursive least squares background prediction of univariate syndromic surveillance data

... adaptive recursive least squares filter applied to time series derived from emergency department (ED) and OTC ...at least as low (in the sense of minmum squared error) as predictions using the ...

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Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography

Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography

... paper, Recursive Least Squares Dictionary Learning Algorithm (RLS-DLA) is used to learn the initial dictionary for dictionary learning of sparse EIT ...

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Model-Free Uncalibrated Visual Servoing Using Recursive Least Squares

Model-Free Uncalibrated Visual Servoing Using Recursive Least Squares

... Abstract— In this paper, a model free uncalibrated visual servoing algorithm based on recursive least squares is proposed and discussed in depth. No robot kinetics or dynamics, camera calibration or ...

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Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

... In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS ...

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Decision Directed Recursive Least Squares MIMO Channels Tracking

Decision Directed Recursive Least Squares MIMO Channels Tracking

... decision-directed recursive least squares (DD-RLS) ...weighted least squares cost func- tion it is minimized and eventually the RLS MIMO channel estimation algorithm is ...

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The generalized frequency domain adaptive filtering algorithm as an approximation of the block recursive least squares algorithm

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 ...

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A derivation of a general order, multichannel, fast transversal, recursive least squares filter algorithm

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] ...

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Signal quantization effects on recursive least squares adaptive filtering algorithms

Signal quantization effects on recursive least squares adaptive filtering algorithms

... desired signal results in an additive error term and does not effect the weight vector. coefficients[r] ...

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Roundoff error problems and solutions for conventional recursive least squares filters

Roundoff error problems and solutions for conventional recursive least squares filters

... agreement in the two normalized weight error trajectories. Thus, the stabilization techniques had little impact on least squares performance for this example... Comparison of normalized [r] ...

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Completely Recursive Least Squares and Its Applications

Completely Recursive Least Squares and Its Applications

... the recursive GLS inherits the recursion-oriented advantages of the conventional RLS ...the recursive GLS has much more reduced computational complexity than traditional LE-constrained GLS methods and is ...

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Floating point error analysis of recursive least squares and least means squares adaptive filters

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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Coefficient rounding and truncation effects on recursive least squares algorithms

Coefficient rounding and truncation effects on recursive least squares algorithms

... This section deals with the derivation of the statistical word length (SWL) required to quantize the Kalman gain vector elements in order to meet certain performance measures.. The metho[r] ...

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High sample rate Givens rotations for recursive least squares

High sample rate Givens rotations for recursive least squares

... a Addition of signed-binary and binary b Subtraction of binary from signed-binary Figure 2.4 Using full-adders to add a signed-binary and a binary number A single redundant input means t[r] ...

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Robust Self Tuning Regulator of Time Varying Linear Systems with Bounded External Disturbances

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 RELS with ...

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Identification of MIMO Hammerstein models using Singular Value Decomposition approach

Identification of MIMO Hammerstein models using Singular Value Decomposition approach

... on recursive least squares (RLS) approximation and allows to determine the memoryless static nonlinearity as well as the linear model parameters from a linear set of ...The recursive algorithm ...

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Kernel methods for short-term spatio-temporal wind prediction

Kernel methods for short-term spatio-temporal wind prediction

... the least mean squares (LMS) and recursive least squares (RLS) algorithms, are presented in their conventional linear and kernelised ...

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Robust adaptive filtering using recursive weighted least squares with combined scale and variable forgetting factors

Robust adaptive filtering using recursive weighted least squares with combined scale and variable forgetting factors

... tional recursive least squares (RLS) using VFF based on the standard EPE criterion, and the adaptive M robust- based algorithm with only scale factor ...

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On the sensitivity of transversal RLS algorithms to random perturbations in the filter coefficients

On the sensitivity of transversal RLS algorithms to random perturbations in the filter coefficients

... Transversal Recursive Least Squares (RLS) algorithms estimate filter coefficients which minimize the accumulated sum of the square of the error residuals termed the error power.. In this[r] ...

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