International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 8, No. 10, 8 Oct. 2016
Cover page and Table of Contents: PDF (size: 618KB)
Rate of Convergence of the Sine Imprecise Functions
Full Text (PDF, 618KB), PP.31-43
Views: 0 Downloads: 0
Author(s)
Index Terms
Rate of Convergence, Imprecise Function, Conversion Point, Imprecise Number, Diversion Point, Imprecise Polynomials
Abstract
We convert polynomial function of degree nth into imprecise form to obtain an important point called conversion point. For some particular region, we collect the finite number of data points to obtain the most economical function called imprecise function. Conversion point of the functions is shown with the help of MUPAD graph. Further we study the area of the imprecise function occurred by the multiplication of sine function to know how much variation of the imprecise functions are obtained for the respective intervals. For different imprecise polynomial we study level of the rate of convergence.
Cite This Paper
Kangujam Priyokumar Singh, Sahalad Borgoyary, "Rate of Convergence of the Sine Imprecise Functions", International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.10, pp.31-43, 2016. DOI:10.5815/ijisa.2016.10.04
Reference
[1]J. L. Krahula and J. F. Polhemus, Use of Fourier Series in the Finite Element Method, AIAA Journal, Vol. 6, No. 4 (1968), 726-728.
[2]E.O. Attinger, A. Anné and D.A. McDonald, Use of Fourier Series for the Analysis of Biological Systems, The Biophysical Society. Published by Elsevier Inc., Vol. 6, No.3 (1966), 291–304.
[3]H. Akima, A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures, Journal of the ACM, Vol. 17, No. 4 (1970), 589-602.
[4]C. Zhu and F. W. Paul, A Fourier Series Neural Network and Its Application to System Identification, J. Dyn. Sys., Meas., Control Vol.117, No.3 (1995), 253-261.
[5]C. H. Cheng, A new Approach to Ranking Fuzzy Numbers by Distance Method, Fuzzy Sets and Systems, Vol. 95 (1998), 307-317.
[6]E.J. Ekpenyong, C.O. Omekara, Application of Fourier Series Analysis To Temperature Data, Global Journal of Mathematical Sciences Vol. 7, No.1( 2008), 5-14.
[7]F. Toutounian and A. Ataei, A New Method for Computing Moore-Penrose Inverse Matrices, Journal of Computational and Applied Mathematics, Vol. 228, No. 1 (2009), 412-417.
[8]M. Kahm, grofitt: Fitting Biological Growth Curves with R, Journal of Statistical Software, Vol. 33, No.7 (2010).
[9]H.K. Baruah, Theory of Fuzzy Sets: Beliefs and Realities, I.J. Energy Information and Communications. Vol.2, No.2 (2011), 1-22.
[10]H.K. Baruah, Construction of Membership Function of a Fuzzy Number, ICIC Express Letters, Vol. 5, No.2 (2011), 545-549.
[11]M. Abbasian, H. S. Yazdi, ans A. V. Mazloom, Kernel Machine Based Fourier Series, I. J. of Advanced Science and Technology Vol. 33 (2011).
[12]H.K .Baruah, An introduction to the theory of imprecise Sets: The Mathematics of Partial Presence, J. Math. Computer Science, Vol. 2, No.2 (2012), 110-124.
[13]T. J. Neog and D. K. Sut, An Introduction to the Theory of Imprecise Soft Sets, I.J. Intelligent Systems and Applications, Vol.11 (2012), 75-83.
[14]S. Narayanamoorthy, S. Saranya, and S. Maheswari, A Method for Solving Fuzzy Transportation Problem (FTP) using Fuzzy Russell's Method, I.J. Intelligent Systems and Applications, Vol. 2 (2013), 71-75.
[15]S. Borgoyary, A Few Applications of Imprecise Numbers, I.J. Intelligent Systems and Applications, Vol. 7, No.8 (2015), 9-17.
[16]S. Borgoyary, An Introduction of Two and Three Dimensional Imprecise Numbers, I.J. Information Engineering and Electronic Business, Vol.7, No.5 (2015), 27-38.