least-squares estimation algorithm
International Journal of Emerging Technology and Advanced Engineering
... channel estimation techniques such as least squares (LMS) algorithm and recursive least squares algorithm (RLS) is planned for multiple input multiple output (MIMO) ...
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Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering
... improved least squares identification algorithm for multivariable Hammerstein output error moving average systems by using the Taylor expansion on a quadratic criterion function and defining the ...
17
Estimation of groundwater flow parameters using least squares
... the least squares ap- proach of estimating steady state ow parameters in a groundwater ...a least squares cost functional with a nite dierence scheme used to solve the steady state ow equation ...
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Implementation of the Least-Squares Lattice with Order and Forgetting Factor Estimation for FPGA
... The algorithm is integrated into the Xilinx EDK environment as a Microblaze accelerator, resulting in a versatile, easy-to-use and compact RLS lattice coprocessor, which can easily be accessed by the standard C ...
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Particle swarm optimization and least squares estimation of NARMAX
... parameter estimation, model ...Linear Least Squares solution methods (LLS) (Normal Equation (NE), QR decomposition (QR) and Singular Value Decomposition (SVD)) for parameter estimation using ...
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Asymptotic properties of weighted least squares estimation in weak parma models
... parameter estimation and diagnostic ...on estimation of PARMA models. Pagano (1978) dealt with moment estimation of periodic autoregressive (PAR) ...moment estimation of low order PARMA ...
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Absolute surface metrology by shear rotation with position error correction
... the estimation algorithm adopts least-squares technique to eliminate azimuthal errors caused by rotation inaccuracy and the errors of angular orders are compensated with the help of Zernike ...
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Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable
... weighted least squares method for an outlier condition, making weighted with degree of membership and lean on an interaction with the ...the least squares of analyzed iterative ...
17
Using Least Squares Support Vector Machines for Frequency Estimation
... frequency estimation algorithms with different N pro- posed in [1] are also shown for ...frequency estimation algorithm outper- form the traditional ML estimator at low SNR (< ...
5
Probabilistic partial least squares model: Identifiability, estimation and application
... Partial Least Squares (PLS) method can be used for this dimension reduction ...an algorithm, while epidemiological study designs are often outcome-dependent and methods to analyze such data require a ...
20
Least squares estimation of hydraulic conductivity from field data
... Filtering Algorithm for Optimiza- tion of Functions with Many Local Min- ima," Technical Report CRSC-TR92-22, Center for Research in Scientic Compu- tation, North Carolina State University, Raleigh; to appear ...
7
Optimal Step Size for the Adaptive Least-Mean Squares Algorithm Applied in the Fractional Fourier Transform Domain for Efficient Signal Estimation in Interference and Noise
... Fractional Fourier Transform (FrFT) domain. We show that the choice of optimum step size results in the LMS algorithm weight vector converging to the MMSE solution, and that the optimum step size itself approaches ...
6
A Method for Assessing Customer Harmonic Emission Level Based on the Iterative Algorithm for Least Square Estimation
... the least squares estimation (LSE) iterative algorithm and obtained the real-time estimates of regres- sion coefficients, and then calculated the level of the harmonic impedance and emission ...
8
A Least-squares Approach to Direct Importance Estimation
... importance estimation that can avoid solving a substantially more difficult task of density ...importance estimation problem as least-squares function fitting and casted the optimization ...
55
Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
... the least square problem, one tries to fit an experimental data with a model f(t,z) by estimating z so that the residuals are ...the algorithm is simple, it is popular, and it works well on many problems ...
10
Estimation of a system of national accounts: implementation with mathematica
... Bayesian estimation, restricted and unrestricted least-squares estimation and best linear unbiased estima- ...the estimation of unrealized or unavailable national accounts data and for ...
16
NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... fitting least squares serial algorithm, based on the least square principle we found an parallel least squares curve and surface fitting method; Second, further reform the ...
7
Burr type III Software Reliability Growth Model with Interval Domain Data
... parameter estimation of SRGMs are the maximum likelihood estimation (MLE) and the least squares estimation ...ML Estimation method is used for finding unknown parameters in the ...
7
Asymptotic properties of least squares estimation for a new fuzzy autoregressive model
... In particular, Ozawa [] proposed a fuzzy auto-regressive (AR) model to forecast the data of living expenditure of workers’ household in Japan, where the identification and the estimation of its model and the ...
10
Rapid detection of total nitrogen content in soy sauce using NIR spectroscopy
... A method for the rapid and nondestructive determination of total nitrogen content in soy sauce was explored. Pre- diction models were established using near-infrared spectroscopy combined with each of the following ...
6