Author | Estrada, Ricardo. author |
---|---|

Title | Asymptotic Analysis [electronic resource] : A Distributional Approach / by Ricardo Estrada, Ram P. Kanwal |

Imprint | Boston, MA : Birkhรคuser Boston, 1994 |

Connect to | http://dx.doi.org/10.1007/978-1-4684-0029-8 |

Descript | IX, 258 p. online resource |

SUMMARY

Asymptotic analysis is an old subject that has found applications in variยญ ous fields of pure and applied mathematics, physics and engineering. For instance, asymptotic techniques are used to approximate very complicated integral expressions that result from transform analysis. Similarly, the soยญ lutions of differential equations can often be computed with great accuracy by taking the sum of a few terms of the divergent series obtained by the asymptotic calculus. In view of the importance of these methods, many excellent books on this subject are available [19], [21], [27], [67], [90], [91], [102], [113]. An important feature of the theory of asymptotic expansions is that experience and intuition play an important part in it because particular problems are rather individual in nature. Our aim is to present a sysยญ tematic and simplified approach to this theory by the use of distributions (generalized functions). The theory of distributions is another important area of applied mathematics, that has also found many applications in mathematics, physics and engineering. It is only recently, however, that the close ties between asymptotic analysis and the theory of distributions have been studied in detail [15], [43], [44], [84], [92], [112]. As it turns out, generalized functions provide a very appropriate framework for asymptotic analysis, where many analytical operations can be performed, and also proยญ vide a systematic procedure to assign values to the divergent integrals that often appear in the literature

CONTENT

1 Basic Results in Asymptotics -- 1.1 Introduction -- 1.2 Order Symbols -- 1.3 Asymptotic Series -- 1.4 Algebraic and Analytic Operations -- 1.5 Existence of Functions with a Given Asymptotic Expansion -- 1.6 Asymptotic Power Series in a Complex Variable -- 1.7 Asymptotic Approximation of Partial Sums -- 1.8 The Euler-Maclaurin Summation Formula -- 2 Introduction to the Theory of Distributions -- 2.1 Introduction -- 2.2 The Space of Distributions $$\mathcal{D}'$$ -- 2.3 Algebraic and Analytic Operations -- 2.4 Regularization, Pseudofunction and Hadamard Finite Part -- 2.5 Support and Order -- 2.6 Homogeneous Distributions -- 2.7 Distributional Derivatives of Discontinuous Functions -- 2.8 Tempered Distributions and the Fourier Transform -- 2.9 Distributions of Rapid Decay -- 2.10 Spaces of Distributions Associated with an Asymptotic Sequence -- 3 A Distributional Theory of Asymptotic Expansions -- 3.1 Introduction -- 3.2 The Taylor Expansion of Distributions -- 3.3 The Moment Asymptotic Expansion -- 3.4 Expansions in the Space $$\mathcal{P}'$$ -- 3.5 Laplaceโ{128}{153}s Asymptotic Formula -- 3.6 The Method of Steepest Descent -- 3.7 Expansion of Oscillatory Kernels -- 3.8 The Expansion of f(?x) as ? โ{128}{148}> ? in Other Cases -- 3.9 Asymptotic Separation of Variables -- 4 The Asymptotic Expansion of Multidimensional Generalized Functions -- 4.1 Introduction -- 4.2 Taylor Expansion in Several Variables -- 4.3 The Multidimensional Moment Asymptotic Expansion -- 4.4 Laplaceโ{128}{153}s Formula -- 4.5 Fourier Type Integrals -- 4.6 Further Examples -- 4.7 Tensor Products and Partial Asymptotic Expansions -- 4.8 An Application in Quantum Mechanics -- 5 The Asymptotic Expansion of Certain Series Considered by Ramanujan -- 5.1 Introduction -- 5.2 Basic Formulas -- 5.3 Lambert Type Series -- 5.4 Distributionally Small Sequences -- 5.5 Multiple Series -- 6 Series of Dirac Delta Functions -- 6.1 Introduction -- 6.2 Basic Notions -- 6.3 Several Problems That Lead to Series of Deltas -- 6.4 Dual Taylor Series as Asymptotics of Solutions of Differential Equations -- 6.5 Singular Perturbations -- References

Mathematics
Approximation theory
Probabilities
Mathematics
Approximations and Expansions
Probability Theory and Stochastic Processes