Fractional Calculus and Fractional Differential Equations. 1st ed. 2019

種類:

電子ブック

責任表示:

edited by Varsha Daftardar-Gejji

出版情報:

Singapore : Springer Nature Singapore : Imprint: Birkhäuser, 2019

著者名:

• Daftardar-Gejji, Varsha.
• SpringerLink (Online service)

シリーズ名:

Trends in Mathematics ;

ISBN:

9789811392276 [9811392277]    

注記:

Chapter 1. Numerics of Fractional Differential Equations -- Chapter 2. Adomian Decomposition Method and Fractional Poisson Processes: A Survey -- Chapter 3. On Mittag-Leffler Kernel Dependent Fractional Operators with Variable-Order -- Chapter 4. Analysis of 2-Term Fractional Order Delay Differential Equations -- Chapter 5. Stability Analysis of Two-Dimensional Incommensurate Systems of Fractional Order Differential Equations -- Chapter 6. Artificial Neural Network Approximation of Fractional-order Derivative Operators: Analysis and DSP Implementation -- Chapter 7. Theory of Fractional Differential Equations Using Inequalities and Comparison Theorems: A Survey -- Chapter 8. Exact Solutions of Fractional Partial Differential Equations by Sumudu Transform Iterative Method.
This book provides a broad overview of the latest developments in fractional calculus and fractional differential equations (FDEs) with an aim to motivate the readers to venture into these areas. It also presents original research describing the fractional operators of variable order, fractional-order delay differential equations, chaos and related phenomena in detail. Selected results on the stability of solutions of nonlinear dynamical systems of the non-commensurate fractional order have also been included. Furthermore, artificial neural network and fractional differential equations are elaborated on; and new transform methods (for example, Sumudu methods) and how they can be employed to solve fractional partial differential equations are discussed. The book covers the latest research on a variety of topics, including: comparison of various numerical methods for solving FDEs, the Adomian decomposition method and its applications to fractional versions of the classical Poisson processes, variable-order frac

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