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least-mean-squares complexity

Synthesis of Adaptive Uniform Circular Array Using Normalized Fractional Least Mean Squares Algorithm

Synthesis of Adaptive Uniform Circular Array Using Normalized Fractional Least Mean Squares Algorithm

... The study of Stochastic-gradient algorithms led to the development of adaptive algorithms. Using some approximations and suitable changes in the gradient vectors, these methods are carried out. Different approximations ...

5

Performance Analysis of Adaptive Filters for Denoising of ECG Signals

Performance Analysis of Adaptive Filters for Denoising of ECG Signals

... of least squares for automatically adjusting the coefficient of a FIR filter without invoking assumptions on the statistics of input ECG ...of squares of instantaneous error values ...zero ...

12

Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery

Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery

... low complexity linear ...harmonic mean iteratively reweighted least squares (HM-IRLS), optimizes a non-convex Schatten-p quasi-norm penalization to promote low-rankness and carries three major ...

49

Two stage weighted least squares estimator of the conditional mean of observation driven time series models

Two stage weighted least squares estimator of the conditional mean of observation driven time series models

... Important classes of count time series models, in particular the Poisson INteger GARCH (INGARCH), the Negative Binomial INGARCH and the INteger AR (INAR), that will be considered in Section 3 below, have a conditional ...

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On weighted structured total least squares

On weighted structured total least squares

... The equivalent optimization problem (1) is a nonlinear least squares prob- lem, so that classical optimization methods can be used for its solution. The optimization methods require a cost function and first ...

8

Overview of total least squares methods

Overview of total least squares methods

... total least squares problems [12], the data matrix A B is ...total least squares problem formulation is ex- tended [31] with the additional constraint that the structure of the data matrix A B ...

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TO IMPLEMENT LEAST MEAN SQUARES USING INCREASING THE SECURITY OF BIG DATA

TO IMPLEMENT LEAST MEAN SQUARES USING INCREASING THE SECURITY OF BIG DATA

... Big data is a broad term for data sets, so Large (or)Complex that traditional data processing application extremely large data sets that may be analyzed computationally to Uncover patterns, trends and associations . ...

6

Consistent least squares fitting of ellipsoids

Consistent least squares fitting of ellipsoids

... ordinary least squares estima- tor is inconsistent, and due to the nonlinearity of the model, the orthogonal regression estimator is inconsistent as well, ...ordinary least squares ...

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Adaptive Filter using FPGA For Audio Enhancement

Adaptive Filter using FPGA For Audio Enhancement

... In the figure 2, our implementation flow is shown. Here our input data is audio signal and audio with noise signal. We are giving input audio signal that is wav file from Matlab to the filtering process which is ...

5

Distributed Learning with Regularized Least Squares

Distributed Learning with Regularized Least Squares

... the least squares regulariza- tion scheme in a RKHS can achieve the optimal learning rates in expectation, provided that m satisfies the restriction ...

31

Teaching Least Squares in Matrix Notation

Teaching Least Squares in Matrix Notation

... least squares (WLS), also called homoskedastic and heteroskedastic regressions, are the names used to distinguish the special case of equal values for all standard deviations from the case of different ...

13

Image magnification by least squares surfaces

Image magnification by least squares surfaces

... This paper continues as follows. In the second part, quadratic surfaces and the theory of least squares will be discussed. In the third part, the least square planes, suggested algorithms, and ...

15

FPGA Implementation of Adaptive Weight Calculation Using QRD   RLS Algorithm

FPGA Implementation of Adaptive Weight Calculation Using QRD RLS Algorithm

... Recursive least squares (RLS) adaptive filter is an algorithm which recursively finds the filter coefficients that minimize a weighted linear least squares cost function relating to the input ...

9

Optimal Dictionary for Least Squares Representation

Optimal Dictionary for Least Squares Representation

... The problem addressed in this article differs from the mainstream research of finding dictionaries offering sparse ( ` 0 -optimal) representations in the sense that our objective is to f[r] ...

28

RLScore: Regularized Least-Squares Learners

RLScore: Regularized Least-Squares Learners

... RLScore is a Python open source module for kernel based machine learning. The library provides implementations of several regularized least-squares (RLS) type of learners. RLS methods for regression and ...

5

Deformation analysis with Total Least Squares

Deformation analysis with Total Least Squares

... In classical approach, transformation parameters are es- timated by the LS adjustment of the observation equations where only the observations are considered as stochastic. However, in some cases, design matrix elements ...

7

Least squares approximations of power series

Least squares approximations of power series

... In this paper we obtain analogs to (1.4) and (1.6) for power series f defined on the open interval ( − 1, 1). Such functions f (especially without closed forms) arise, for ex- ample, in solutions to differential ...

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A novel interpretation of least squares solution

A novel interpretation of least squares solution

... We show that the well-known least squares LS solution of an overdetermined system of linear equations is a convex combination of all the non-trivial solutions weighed by the squares of t[r] ...

6

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES MANAGEMENT STUDIES OF BEAM FORMING ALGORITHMS FOR SMART ANTENNA SYSTEMS IN WIRELESS COMMUNICATION APPLICATION

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES MANAGEMENT STUDIES OF BEAM FORMING ALGORITHMS FOR SMART ANTENNA SYSTEMS IN WIRELESS COMMUNICATION APPLICATION

... computed at(n+1) iteration. ì is gradient step size that controls the convergence characteristics of the algorithm, that is how fast and close the estimated weights approach the optimal weights g(w(n)) is estimate of ...

5

Approximate Least Squares Accelerator

Approximate Least Squares Accelerator

... the least-significant ...near-zero mean when selecting k bits from the operands, 1 is always placed at the least-signifi- cant bit of the newly formed k-bit ...

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