Differential Equations and Inverse Problems
Materialtyp:
ArtikelUtgivningsinformation: MDPI - Multidisciplinary Digital Publishing Institute 2025Beskrivning: 1 electronic resource (202 p.)Innehållstyp: - text
- computer
- online resource
- 9783725830671
- 9783725830688
- Economics, Finance, Business and Management
- Industry & industrial studies
- Media, entertainment, information and communication industries
- Information technology industries
- BNf-stable
- Banach space
- Hilbert space
- Laplace transform
- Lobatto IIIC method
- Malliavin calculus
- Markovian switching
- Monge–Ampère equations
- Newton-type method
- Rayleigh–Stokes equation with a fractional derivative
- Runge–Kutta method
- Sinc collocation method
- Tikhonov regularization method
- WSGD operator
- activation function
- anti-noise property
- array signal processing
- backward problem
- boundary value problem
- collocation methods
- common function
- convergence
- convergence estimate
- convolution neural network
- curve fitting method
- direction-of-arrival estimation
- double integral
- dynamic complex matrix inversion
- feature learning
- fixed point theorem
- fixed-point theorem
- fractional differential equation
- fractional partial integro-differential equation
- general theoretical solution
- generalized inverse
- implicit Euler method
- impulsive delay differential equations
- inflection point method
- linear noise
- numerical scheme
- one-dimensional heat conduction
- outer inverse
- periodic boundary condition
- pure jumps
- residual fluctuations
- sign-c
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The present reprint contains 12 articles that have been accepted and published in the Special Issue "Differential Equations and Inverse Problems" in MDPI's Axioms journal. The articles cover a wide range of topics with respect to the theory and applications of differential equations and inverse problems. The key topics covered in this Special Issue include impulsive delay differential equations, fractional differential equations, the Rayleigh–Stokes equation with a fractional derivative, the Monge–Ampère equation, one-dimensional heat conduction, dynamic complex matrix inversion, collocation methods, the Runge–Kutta method, the Tikhonov regularization method, convolution neural networks, supervised contrastive learning, zeroing neural networks, etc. Differential equations and inverse problems have become a rapidly growing topic because of the new techniques developed recently and the amazing achievements in computational sciences. With the progress of science and technology, differential equations and inverse problems have quickly developed, and new waves have been successively set off in a broad range of disciplines, such as mathematics, physics, engineering, business, economics, earth science, biology, etc. We hope that the reprint will be interesting and useful for those working in the areas of differential equations, inverse problems, and artificial intelligence, in addition to those who have a mathematical background and want to familiarize themselves with recent advances in differential equations and inverse problems, which have been widely applied in many fields of science and engineering.
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eng
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