Some aspects of implementing a cubic spline interpolation algorithm on a DSP

Mâţiu-Iovan, Liliana

doi:10.1109/isetc.2012.6408096

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…The spline interpolation method is a method that draws a curve of all points in the form of variable splines [19][20][21]. Every two adjacent points can determine the polynomial of each segment; so, the spline interpolation is composed of a series of polynomials.…”

Section: Cubic Spline Interpolationmentioning

confidence: 99%

A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers

et al. 2021

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For most high-precision power analyzers, the measurement accuracy may be affected due to the nonlinear relationship between the input and output signal. Therefore, calibration before measurement is important to ensure accuracy. However, the traditional calibration methods usually have complicated structures, cumbersome calibration process, and difficult selection of calibration points, which is not suitable for situations with many measurement points. To solve these issues, a nonlinear calibration method based on sinusoidal excitation and DFT transformation is proposed in this paper. By obtaining the effective value data of the current sinusoidal excitation from the calibration source, the accurate calibration process can be done, and the calibration efficiency can be improved effectively. Firstly, through Fourier transform, the phase value at the initial moment of the fundamental frequency is calculated. Then, the mapping relationship between the sampling value and the theoretical calculation value is established according to the obtained theoretical discrete expression, and a cubic spline interpolation method is used to further reduce the calibration error. Simulations and experiments show that the calibration method presented in this paper achieves high calibration accuracy, and the results are compensation value after calibration with a deviation of ± 3 × 10 − 4 .

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Section: Cubic Spline Interpolationmentioning

confidence: 99%

A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers

et al. 2021

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“…Therefore, many researchers have been using interpolation methods to analyze data of different applications. Some of the interpolation methods are as following: B-spline interpolation using linear approximations for setting up viewing and projection matrices and describing complex objects were studied in reference [1], implementing a cubic spline interpolation algorithm on DSP was studied in reference [2], an iterative linear interpolation based on fuzzy gradient model for low-cost VLSI implementation was introduced by reference [3], a polynomial interpolation for space-efficient verifiable secret sharing was given in reference [4], an interpolation method to investigate the improvement in image quality for ground penetrating radar (GPR) acquisition was highlighted in reference [5], gauss interpolation algorithms for nonlinear rational parameters were presented in reference [6], four image interpolation methods for 2-D AR modeling were given in reference [7], a polynomial approach to evaluate the fragmented function approach for two secure two-party computation (STPC) was introduced in reference [8], a bivariate splines in piecewise constant tension as the solution for a functional minimization problem was given in reference [9], a cubic spline interpolation algorithm for smoothness interpolation model of non-circular curve mechanical mold was studied in reference [10], a spline interpolation functions for solution of a non-linear equation was given in reference [11], a view interpolation method from defocused stereo images using linear filtering was introduced in reference [12], a linear interpolation effects on signal transferring was highlighted in reference [13], a novel and fast cubic B-splines algorithm for cancellation of random valued impulse noise was given in reference [14], a real time implementation of cubic B-spline algorithm for electro optical tracking system was studied in reference [15], a cubic B-spline curves based research of the approximate algorithm was given in reference [16], and a fast algorithm for quadratic and cubic spline wavelets was provided in reference [17]. Among these, the spline curve makes it easy to build an interface that will allow designing and controlling the shape of complex curves and surfaces by using low-degree polynomials in each of the intervals and by choosing the polynomial pieces such that they fit smoothly together.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2019

Adv. Electr. Comp. Eng.

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Peak detection of any time serial signals can be done using different methods. However, exact positions of the peaks cannot be achieved, if the method does not have a high sensitivity detection capability. It is known that various errors appear between the real peak value and the measured value; therefore, a true peak value can be obtained from the measured value by using a highly sensitive detection method. For this reason, spline interpolation is used to estimate the peak points from measured values. In this paper, highly sensitive peak detection of high-frequency signals based on FPGA is proposed using spline algorithm, which is capable of calculating the middle points using the first and last points on the signal. To evaluate the system, the histograms, the mean, and the variance of the peak values before and after spline interpolation are compared. Simulation results show that calculated peak points using splines and real peak values of a signal are very close to each other since the spline algorithm has very high calculation sensitivity. In addition, spline results show us how much error the existing peak values have.

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TRAVERSE-Voice Commanded Self Navigating Indoor Robot

Vybhavi¹,

kumar²,

Vaibhavi³

et al. 2019

SSRN Journal

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When a human is taken to a new place, a new location, the individual first tries to perceive it, then gets to the geography of it and finally maps it. By mapping the whole location, the human goes around the place without any difficulty. In this project, the implementation will be done in such a way that the robot also consumes the parameters of the area in the same way as the human, by first perceiving the location entirely, followed by mapping the whole place and then going around it, thereby marking the location to absolute precision and making it flawless for navigation. To accomplish this performance, a self-navigating algorithm using SLAM (Simultaneous Localization and Mapping) is written and executed. The robot, by using ultrasonic sensors will measure the distances of the surrounding objects.

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Some aspects of implementing a cubic spline interpolation algorithm on a DSP

Cited by 3 publications

References 3 publications

A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers

A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers

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TRAVERSE-Voice Commanded Self Navigating Indoor Robot

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