Polynomial–Exponential Decomposition From Moments
We analyze the decomposition problem of multivariate polynomial–exponential functions from their truncated series and present new algorithms to compute their decomposition. Using the duality between polynomials and formal power series, we first show how the elements in the dual of an Artinian algebr...
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| Vydáno v: | Foundations of computational mathematics Ročník 18; číslo 6; s. 1435 - 1492 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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01.12.2018
Springer Nature B.V Springer Verlag |
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| ISSN: | 1615-3375, 1615-3383 |
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| Abstract | We analyze the decomposition problem of multivariate polynomial–exponential functions from their truncated series and present new algorithms to compute their decomposition. Using the duality between polynomials and formal power series, we first show how the elements in the dual of an Artinian algebra correspond to polynomial–exponential functions. They are also the solutions of systems of partial differential equations with constant coefficients. We relate their representation to the inverse system of the isolated points of the characteristic variety. Using the properties of Hankel operators, we establish a correspondence between polynomial–exponential series and Artinian Gorenstein algebras. We generalize Kronecker theorem to the multivariate case, by showing that the symbol of a Hankel operator of finite rank is a polynomial–exponential series and by connecting the rank of the Hankel operator with the decomposition of the symbol. A generalization of Prony’s approach to multivariate decomposition problems is presented, exploiting eigenvector methods for solving polynomial equations. We show how to compute the frequencies and weights of a minimal polynomial–exponential decomposition, using the first coefficients of the series. A key ingredient of the approach is the flat extension criteria, which leads to a multivariate generalization of a rank condition for a Carathéodory–Fejér decomposition of multivariate Hankel matrices. A new algorithm is given to compute a basis of the Artinian Gorenstein algebra, based on a Gram–Schmidt orthogonalization process and to decompose polynomial–exponential series. A general framework for the applications of this approach is described and illustrated in different problems. We provide Kronecker-type theorems for convolution operators, showing that a convolution operator (or a cross-correlation operator) is of finite rank, if and only if, its symbol is a polynomial–exponential function, and we relate its rank to the decomposition of its symbol. We also present Kronecker-type theorems for the reconstruction of measures as weighted sums of Dirac measures from moments and for the decomposition of polynomial–exponential functions from values. Finally, we describe an application of this method for the sparse interpolation of polylog functions from values. |
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| AbstractList | We analyze the decomposition problem of multivariate polynomial-exponential functions from truncated series and present new algorithms to compute their decomposition. Using the duality between polynomials and formal power series, we first show how the elements in the dual of an Artinian algebra correspond to polynomial-exponential functions. They are also the solutions of systems of partial differential equations with constant coefficients. We relate their representation to the inverse system of the roots of the characteristic variety. Using the properties of Hankel operators, we establish a correspondence between polynomial exponential series and Artinian Gorenstein algebras. We generalize Kronecker theorem to the multivariate case, by showing that the symbol of a Hankel operator of finite rank is a polynomial-exponential series and by connecting the rank of the Hankel operator with the decomposition of the symbol. A generalization of Prony's approach to multivariate decomposition problems is presented , exploiting eigenvector methods for solving polynomial equations. We show how to compute the frequencies and weights of a minimal polynomial-exponential decomposition , using the first coefficients of the series. A key ingredient of the approach is the flat extension criteria, which leads to a multivariate generalization of a rank condition for a Carathéodory-Fejér decomposition of multivariate Hankel matrices. A new algorithm is given to compute a basis of the Artinian Gorenstein algebra, based on a Gram-Schmidt orthogonalization process and to decompose polynomial-exponential series. A general framework for the applications of this approach is described and illustrated in different problems. We provide Kronecker-type theorems for convolution operators, showing that a convolution operator (or a cross-correlation operator) is of finite rank, if and only if, its symbol is a polynomial-exponential function, and we relate its rank to the decomposition of its symbol. We also present Kronecker-type theorems for the reconstruction of measures as weighted sums of Dirac measures from moments and for the decomposition of polynomial-exponential functions from values. Finally, we describe an application of this method for the sparse interpolation of polylog functions from values. We analyze the decomposition problem of multivariate polynomial–exponential functions from their truncated series and present new algorithms to compute their decomposition. Using the duality between polynomials and formal power series, we first show how the elements in the dual of an Artinian algebra correspond to polynomial–exponential functions. They are also the solutions of systems of partial differential equations with constant coefficients. We relate their representation to the inverse system of the isolated points of the characteristic variety. Using the properties of Hankel operators, we establish a correspondence between polynomial–exponential series and Artinian Gorenstein algebras. We generalize Kronecker theorem to the multivariate case, by showing that the symbol of a Hankel operator of finite rank is a polynomial–exponential series and by connecting the rank of the Hankel operator with the decomposition of the symbol. A generalization of Prony’s approach to multivariate decomposition problems is presented, exploiting eigenvector methods for solving polynomial equations. We show how to compute the frequencies and weights of a minimal polynomial–exponential decomposition, using the first coefficients of the series. A key ingredient of the approach is the flat extension criteria, which leads to a multivariate generalization of a rank condition for a Carathéodory–Fejér decomposition of multivariate Hankel matrices. A new algorithm is given to compute a basis of the Artinian Gorenstein algebra, based on a Gram–Schmidt orthogonalization process and to decompose polynomial–exponential series. A general framework for the applications of this approach is described and illustrated in different problems. We provide Kronecker-type theorems for convolution operators, showing that a convolution operator (or a cross-correlation operator) is of finite rank, if and only if, its symbol is a polynomial–exponential function, and we relate its rank to the decomposition of its symbol. We also present Kronecker-type theorems for the reconstruction of measures as weighted sums of Dirac measures from moments and for the decomposition of polynomial–exponential functions from values. Finally, we describe an application of this method for the sparse interpolation of polylog functions from values. |
| Author | Mourrain, Bernard |
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| Keywords | Polynomial–exponential series 68W30 Prony Differential equation 14Q20 15B05 Artinian Hankel matrix Interpolation Gorenstein Moment 47B35 Sparse representation AMS classification: 14Q20 15B05 1 |
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KunisStefanPeterThomasRömerTimvon der OheUlrichA mul Charles Riquier (9372_CR61) 1910 David A Cox (9372_CR19) 1992 9372_CR49 Michel Fliess (9372_CR28) 1970; 94 9372_CR44 Dmitry Batenkov (9372_CR8) 2013; 73 Ernst Fischer (9372_CR26) 1911; 32 9372_CR41 Bernard Mourrain (9372_CR50) 2000; 16 Patrick Fitzpatrick (9372_CR27) 1990; 36 Monique Laurent (9372_CR42) 2009; 93 9372_CR1 9372_CR2 9372_CR4 Bernard Malgrange (9372_CR46) 1956; 6 9372_CR6 Lek-Heng Lim (9372_CR43) 2014; 60 9372_CR38 Fredrik Andersson (9372_CR5) 2010; 29 9372_CR32 9372_CR33 Bernard Mourrain (9372_CR48) 1996; 117&118 Daniel Potts (9372_CR58) 2010; 90 9372_CR31 Laurent Schwartz (9372_CR66) 1966 Mark Giesbrecht (9372_CR29) 2009; 44 Anthony Iarrobino (9372_CR37) 1999 Elwyn R Berlekamp (9372_CR12) 1968; 14 Jacques Emsalem (9372_CR25) 1978; 106 9372_CR71 Ulrich Oberst (9372_CR52) 2001; 12 Gene Golub (9372_CR30) 2003; 19 Paul S Pedersen (9372_CR53) 1999; 141 Stefan Kunis (9372_CR39) 2016; 490 Laurent Barachart (9372_CR7) 1984; 301 Tomas Sauer (9372_CR65) 2017; 136 Emmanuel J Candès (9372_CR17) 2006; 59 Vladimir V Peller (9372_CR54) 1998; 33 Jérome Brachat (9372_CR16) 2010; 433 9372_CR68 9372_CR63 Bernhard Beckermann (9372_CR10) 1994; 15 Gregory Beylkin (9372_CR15) 2005; 19 Jean-Bernard Lasserre (9372_CR40) 2013; 51 Jessie F MacWilliams (9372_CR45) 1977 Shojiro Sakata (9372_CR64) 1988; 5 Stephen C Power (9372_CR60) 1982; 48 Richard Rochberg (9372_CR62) 1987; 10 Bernhard Beckermann (9372_CR9) 2007; 106 Zai Yang (9372_CR70) 2016; 62 9372_CR18 Annie Cuyt (9372_CR21) 1999; 105 Alessandra Bernardi (9372_CR13) 2013; 52 9372_CR14 Raul E Curto (9372_CR20) 1996 9372_CR11 David Eisunbud (9372_CR23) 1994 9372_CR55 Lars Hormander (9372_CR36) 1990 9372_CR51 Gerlind Plonka (9372_CR57) 2014; 37 Thomas Peter (9372_CR56) 2013; 29 Joachim von zur Gathen (9372_CR69) 2013 James Massey (9372_CR47) 1969; 15 Baron Gaspard Riche de Prony (9372_CR22) 1795; 1 Gu Caixing (9372_CR34) 1999; 288 Fredrik Andersson (9372_CR3) 2015; 82 Mohamed Elkadi (9372_CR24) 2007 Hakop A Hakopian (9372_CR35) 2004; 10 The MUSIC Algorithm (9372_CR67) 1992; 40 Daniel Potts (9372_CR59) 2013; 40 |
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| SubjectTerms | Algebra Algebraic Geometry Algorithms Applications of Mathematics Computer Science Convolution Decomposition Economics Eigenvectors Exponential functions Hankel matrices Interpolation Linear and Multilinear Algebras Math Applications in Computer Science Mathematics Mathematics and Statistics Matrix Theory Numerical Analysis Operators (mathematics) Partial differential equations Polynomials Power series Theorems |
| Title | Polynomial–Exponential Decomposition From Moments |
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