Least squares via Recursive Least-Squares (RLS) algorithm
Adaptive Beamforming Using the Recursive Least Squares Algorithm on an FPGA
... Results show that the QRD-RLS systolic array using 14 mantissa bits is sufficient as it performs equivalently to conventional RLS using double precision (53 mantissa bits). If only 11 mantissa bits are used, the output ...
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Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation
... RLS algorithm and its ...based algorithm is included; as well as the inclusion of the SOV-RLS algorithm and the Bilinear RLS algorithm to address the insta- bility when dealing with ...
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Echo state kernel recursive least squares algorithm for machine condition prediction
... One fascinating property of ESN is that a temporal task is converted into a non-temporal task of learning a static mapping, because the dynamic reservoir has a fixed recurrent topology and thus only the output weights ...
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The generalized frequency domain adaptive filtering algorithm as an approximation of the block recursive least squares algorithm
... RLS algorithm is briefly reviewed in Section 3 where it is shown that errors induced in the filter coefficients decay exponentially during adaptation using this ...LMS algorithm and a Tikhonov ...
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A New Formalism of the Sliding Window Recursive Least Squares Algorithm and Its Fast Version
... I-SWFRLS algorithm on the window size L s and for- getting factor ρ is depicted in ...I-SWFRLS algorithm provides the best performance for this ...I-SWFRLS algorithm, ρ and L s should be carefully ...
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A Recursive Restricted Total Least-squares Algorithm
... The RTLS problem can be solved off-line by the restricted singular value decomposition (RSVD) [9]. Our main contribu- tion is the development of iterative and recursive methods for solution of RTLS in Section ...
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Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks
... In Fig. 14, we test the performance of different algo- rithms considered in a non-stationary environment. Specifically, in order to simulate the non-stationary envi- ronment, we consider the scenario where the topology ...
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Recursive Least-Squares Learning with Eligibility Traces
... learning least squares algorithms of the literature (LSTD [5], LSPE [15], FPKF [7] and GPTD [8]/KTD [10]) to off-policy learning with eligibility ...their recursive implementation, discuss their ...
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The widely linear quaternion recursive total least squares
... squares algorithm based on the widely linear model (WL- QRLS) has also been developed [6]. Although these results provide the fundamental insight into quaternion-valued adap- tive signal processing, none of ...
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Decision Directed Recursive Least Squares MIMO Channels Tracking
... RLS algorithm is presented and then combined with the DDA algorithm with ML and MMSE detection to operate in the blind mode operation as ...proposed algorithm is simulated for half and full rank flat ...
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The Use of Recursive Least Squares Method for Vehicle Dynamics Analysis
... linear least squares method, subsequently the nonlinear and weighted least squares ...The least squares method was the first method for formulation of the optimal estimate from ...
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Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography
... REFERENCES 1. Wang, Q., et al., “Reconstruction of EIT images via patch based sparse representation over learned dictionaries,” Instrumentation & Measurement Technology Conference, IEEE, 2015. 2. Goharian, M., M. ...
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THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES
... LINEAR REGRESSION LINEAR REGRESSION is a powerfull tool for studying fundamental relationships between two (or more) RVs Y and X. The method is based on the method of least squares. Let’s discuss the ...
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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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Completely Recursive Least Squares and Its Applications
... better approximation can lead to a poorer numerical condition [Albert65]; it is also not always realistic to start the recursion with forgoing data having special observation functions for simple exact initializations ...
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The alternating least-squares algorithm for CDPCA
... the algorithm, the I objects of the data matrix are allocated into P clusters, and simultaneously displayed in a reduced space of Q disjoint ...the algorithm stops when there is a difference between ...
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Recursive Least Squares for a Manipulator which Learns by Demonstration
... In this work, a control system is developed to allow a manipulator to learn and plan trajectories from demonstrations given by the hand of an user. The input of data is acquired by a sensor, and its behavior is learned ...
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Stochastic Gradient versus Recursive Least Squares Learning
... gain, Recursive Least Squares and Stochastic Gradient learning, in a Phelps model of a monetary policy which has been extensively studied ...Stochastic Recursive Algorithm which ...
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Weighted least squares and adaptive least squares: further empirical evidence
... This paper makes two contributions. On the one hand, we have compared finite-sample perfor- mance of OLS, WLS, and ALS for multivariate regressions via a Monte Carlo study. On the other hand, we have compared OLS, ...
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