Methods of multidimensional signal processing under toroidal coordinate systems
DOI:
https://doi.org/10.20535/RADAP.2019.77.5-12Keywords:
optimum toroidal coordinate system, multidimensional signal, optimal vector monolithic and group code, “star” multidimensional configuration, code size, optimum vector information technologies, non-redundant multidimensional code, multidimensional self-checking codeAbstract
Methods of multidimensional signal processing under spatial toroidal coordinate systems configured on a set of combining sums over vector "Glory to Ukraine Star" combinatorial configurations. Base vectors are discussed, and the two theoretically grounded approaches to formation such coordinate systems in order for optimum encoding and conversion of vector signals using its unique properties, both optimum monolithic and group vector codes, and non-redundant codes are proposed. On the particular examples described the benefits of each method of coding of multidimensional signals pointing to corresponding theorems, calculations and illustrative material. Extension of the “star” combinatorial configurations opens new possibilities for the application of methods of optimized coding and processing of multidimensional signals under toroidal coordinate systems for designing modern systems of communication and development of optimized vector information technologies. The remarkable technical merits of the vector configurations, which properties hold for the same set of an optimum encoded design in varieties permutations of its terms is demonstrated, and methods for processing of two- or multidimensional vector signals based on both the optimum binary monolithic and non-redundant codes are presented. Proposed methods of multidimensional signal processing under toroidal coordinate systems provide, essentially, a new approach to generalize them to great class of optimized problems in radio-telecommunications, navigation and information technology. Moreover, the optimization embedded in the underlying combinatorial configurations. The favorable qualities of the "stars" provide breakthrough opportunities to apply them to numerous branches of science and advanced technology, with direct applications to vector data telecommunications, vector encoded design, and optimal vector information technology.
References
Zhuk K.D.,Tunik A.A. and Chynaiev P.I. (1973) Bahatovymirni systemy avtomatychnoho keruvannia [Multidimensional systems of automatized control. Encyclopedia of cybernetics], Vol. 1, Kyiv, pp. 140-142.
Bose N.K. (2017) Multidimensional Sampling. Applied Multidimensional Systems Theory, pp. 57-80. DOI: 10.1007/978-3-319-46825-9_3
Bacchelli B., Bozzini M., Rabut C. and Varas M. (2005) Decomposition and reconstruction of multidimensional signals using polyharmonic pre-wavelets. Applied and Computational Harmonic Analysis, Vol. 18, Iss. 3, pp. 282-299. DOI: 10.1016/j.acha.2004.11.007
Bacchelli B., Bozzini M. and Rabut C. (2003) A fast wavelet algorithm for multidimensional signal using polyharmonic splines, in: Cohen A., Merrien J.L., Schumaker L.L. (Eds.) Curves and Surfaces Fitting: Saint-Malo 2002, Nashboro Press, pp. 21-30.
Wu Z., Feng J., Qiao F. and Tan Z. (2016) Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 374, Iss. 2065, pp. 20150197. DOI: 10.1098/rsta.2015.0197
Rué J. (2013) On polynomial representation functions for multivariate linear forms. European Journal of Combinatorics, Vol. 34, Iss. 8, pp. 1429-1435. DOI: 10.1016/j.ejc.2013.05.017
Dudgeon D.E. and Mersereau R.M. (1983) Multidimensional Digital Signal Processing, Prentice-Hall, pp. 61, 112.
Mersereau R. and Speake T. (1983) The processing of periodically sampled multidimensional signals. IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 31, Iss. 1, pp. 188-194. DOI: 10.1109/tassp.1983.1164018
Mersereau R., Mecklenbrauker W. and Quatieri T. (1976) McClellan transformations for two-dimensional digital filtering-Part I: Design. IEEE Transactions on Circuits and Systems, Vol. 23, Iss. 7, pp. 405-414. DOI: 10.1109/tcs.1976.1084236
Madych W.R. (1990) Polyharmonic Splines, Multiscale Analysis, and Entire Functions. International Series of Numerical Mathematics / Internationale Schriftenreihe zur Numerischen Mathematik / Série Internationale d’Analyse Numérique, pp. 205-216. DOI: 10.1007/978-3-0348-5685-0_15
Madych W.R. (1999) Spline type summability for multivariate sampling. Analysis of Divergence, , pp. 477-512. DOI: 10.1007/978-1-4612-2236-1_27
Nikos E. Mastorakis N.E. (1996) Singular value decomposition in multidimensional arrays. International Journal of Systems Science, Vol. 27, Iss. 7, pp. 647-650. DOI: 10.1080/00207729608929261
Weng X. and Shen J. (2008) Classification of multivariate time series using two-dimensional singular value decomposition. Knowledge-Based Systems, Vol. 21, Iss. 7, pp. 535-539. DOI: 10.1016/j.knosys.2008.03.014
Hall M.Jr. (1998) Combinatorial Theory, 2nd Edition, Wiley-Interscience, 464 р.
Hughes D.R., Piper F.C. (1985) Design theory, Cambridge University Press. DOI: 10.1016/0012-365x(90)90123-y
Moore E.H. and Pollastek H.S. (2013) Difference Sets: Connecting Algebra, Combinatorics, and Geometry. AMS.
Singer J. (1966) Division of mathematics: perfect difference sets. Transactions of the New York Academy of Sciences, Vol. 28, Iss. 7 Series II, pp. 883-888. DOI: 10.1111/j.2164-0947.1966.tb02392.x
Vajda S., Hughes D.R. and Piper F.C. (1974) Projective Planes.. Journal of the Royal Statistical Society. Series A (General), Vol. 137, Iss. 2, pp. 269. DOI: 10.2307/2344563
Rotman J. (1998) Galois Extensions. Universitext, pp. 79-82. DOI: 10.1007/978-1-4612-0617-0_15
Woods J.W. (2012) Multidimensional Signal, Image, and Video Processing and Coding, pp. 616. DOI: 10.1016/C2009-0-62200-5
Riznyk V.V. (1989) Syntez optymalnykh kombinatornykh system [Synthesis of optimum combinatorial systems], Lviv : Vyshcha shkola, 168 p.
Riznyk V. (1998) Multi-dimensional systems based on perfect combinatorial models. IEE Colloquium on Multidimensional Systems: Problems and Solutions. DOI: 10.1049/ic:19980164
Riznyk V.V. (2015) Multidimensional Systems Optimization Developed from Perfect Torus Groups. International Journal of Applied Mathematics and Informatics, Vol. 9, pp.50-54.
Leeper D.G. (1978) Thinned Aperiodic Antenna Arrays with Improved Peak Sidelobe Level Control. Pat. USA No 4071848.
Michio Kaku (1995) Hyperspace: A Scientific Odyssey Through Parallel Universes, Time Warps, and the 10th Dimension, Oxford University Press.
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