Least Squares (LS) algorithm
Continuous Iteratively Reweighted Least Squares Algorithm for Solving Linear Models by Convex Relaxation
... the algorithm calls continuous iteratively re- weighted least squares algorithm for solving REAPER (3), and under a weaker assumption on the data set, we can prove the algorithm is ...
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A multiple sequential orthogonal least squares algorithm for feature ranking and subset selection
... encountered in multiple regression and multivariate pattern recognition. It has been noted that in many cases not all the original variables are necessary for characterizing the overall features. More often only a subset ...
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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 ...
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The generalized frequency domain adaptive filtering algorithm as an approximation of the block recursive least squares algorithm
... GFDAF algorithm. Hence, the RLS algorithm given by (25) is compared to the three pre- sented variants of the GFDAF algorithm, given by (57), (62), and ...
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A general order multichannel, fast least squares algorithm with telecommunications applications
... It was derived using the recursive form of (2.6) and the matrix inversion lemma [52), which generates an explicit inverse formula for matrices of a certain type. The algorithm sequence i[r] ...
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Regularized orthogonal least squares algorithm for constructing radial basis function networks
... The proposed algorithm combines the advantages of both the orthogonal forward regression and regularization methods to provide an efficient and powerful procedure for constructing parsim[r] ...
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Analysis of partial least squares algorithm based on SBM DEA
... In the table 2 and 4, using the relative average error as reliability criterion and referring to 2 dependent variables, we figure out the relative average errors by utilizing the PLS optimized by SBM algorithm are ...
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Overview of total least squares methods
... alternating least squares ...total least squares problems and is globally convergent, with linear convergence ...The least squares nature of the problem is not exploited by the ...
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Object Detection and Tracking Using Uncalibrated Cameras
... nonlinear least squares algorithm the camera internal and external parameters are ...This algorithm gives good results when the location of feature points in 3D world coordinates and their ...
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The Dual of the Least Squares Method
... the least-squares ...the least-squares method, the paper gives a historical perspective of its ori- gin that sheds light on the thinking of Gauss, its ...The least-squares method ...
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International Journal of Emerging Technology and Advanced Engineering
... as least squares (LMS) algorithm and recursive least squares algorithm (RLS) is planned for multiple input multiple output (MIMO) orthogonal frequency division multiplexing ...
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Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering
... based least squares iterative and a recursive least squares algorithms are ...extended least squares algorithm is derived to obtain the estimates of the unknown ...
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NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... parallel algorithm in linear problem, Deren Wang puts forward some solutions to large linear problem parallel method according to matrix splitting technology, Zhong Chen analyzed the convergence of least ...
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On weighted structured total least squares
... is a solution technique for an overdetermined system of equations AX ≈ B, A ∈ IR m × n , B ∈ IR m × d . It is a natural generalization of the least squares approximation method when the data in both A and B ...
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Deformation analysis with Total Least Squares
... Recalling the transformed coordinates of the object points given in Table 6, the differences between the LS and TLS solution are in cm levels. Though, this level of difference is not very important for such a study area ...
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Consistent least squares fitting of ellipsoids
... For the first test example, see Fig. 1, left, the OR estimator is influenced by the initial approximation. Using the OLS estimate as initial approximation, the optimization algorithm converges to a local minimum. ...
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Performance Analysis of Adaptive Beamforming Algorithms for Orthogonal Frequency Division Multiplexing System
... implementing these methods arises from null side carriers. An approach that can work with transmitters inserting guard time in the symbols is presented in [7]. The drawback of this approach is that requires that 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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Adaptive reduction of interfering speaker noise using the least mean squares algorithm
... The desired signal (i.e., the main speaker) and the interfering signal (i.e., other speakers in the background) have similar statistical and spectral characteristics which is quite diffe[r] ...
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An Algorithm for Non Linear Data Fit by the Least Squares Method EUR 4959
... 16/11/49 DATE 72353 FORTRAN IV G LEVEL MINIMI SUBROUTINE MINIMI FUN,FM,X,G,H,N,M,IRIT,EPSF,EPSX,EPSG,I MAX,NIT, MINI 0001 liNVERT mm C MINI c MINI .MINI c MINI PROGRAM CALCULATES MINIMUM[r] ...
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