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The hardware implementation of the square root operation is achieved by different means.
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We propose to use square-root cubature and quadrature Kalman filters/smoothers (named SCKF/S and SQKF/S, respectively) [38, 43] as the core implementation of the new square-root MSPGF/S.
aThe minimization procedure can be carried out by commercially available routines, e.g., the implementation of the nonnegative least square problem minimization algorithm available in Matlab.
The calculation of the mean velocities followed by the implementation of the ordinary least square regression method in order to determine the optimum regression curve between radius and velocity that fitted better the distribution of the collected data.
The ultimate target was the determination of the optimum regression curve between the curve radius' and the corresponding velocities in a form of a power law of the form U = arb, which accomplished with the implementation of the ordinary least square method.
A parallel architecture for an on-line implementation of the recursive least squares (RLS) identification algorithm on a field programmable gate array (FPGA) is presented.
In a frequency-domain implementation of the least-mean-square (LMS) algorithm, the limiting constraints can be placed directly in the frequency domain, allowing the adaptive filter response to be reduced in the frequency regions of constraint violation, with minimal effect at other frequencies [2].
The main block involved in the implementation of reversible square root using modified non-restoring technique is Reversible Controlled-Subtract-Multiplex.
Our hybrid implementation first calculates the eigenvalues of the square of the covariance matrix R by analytically solving for the roots of the cubic characteristic polynomial [ Equation (3)].
The design, with minor modifications, can be used for the implementation of the RSA algorithm by realizing the square-and-multiply algorithm.
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