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Advanced Numerical Methods in Applied Sciences

Advanced Numerical Methods in Applied Sciences

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The use of scientific computing tools is currently customary for solving problems at several complexity levels in Applied Sciences. The great need for reliable software in the scientific community conveys a continuous stimulus to develop new and better performing numerical methods that are able to grasp the particular features of the problem at hand. This has been the case for many different settings of numerical analysis, and this Special Issue aims at covering some important developments in various areas of application.

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Keywords

  • adaptive methods
  • analytical solution
  • asymptotic stability
  • B-spline
  • B-splines
  • barrier options
  • boundary element method
  • BS methods
  • Cholesky factorization
  • collocation method
  • collocation methods
  • conservative problems
  • constrained Hamiltonian problems
  • continuous geometric average
  • Convergence
  • curl–curl operator
  • discontinuous Galerkin methods
  • discretization of systems of differential equations
  • displacement rank
  • edge-histogram
  • edge-preserving smoothing
  • elementary differential
  • energy-conserving methods
  • finite difference method
  • Finite difference methods
  • floating strike Asian options
  • fractional derivative
  • Galerkin method
  • generalized locally Toeplitz sequences
  • generalized Schur algorithm
  • gradient system
  • Hamiltonian Boundary Value Methods
  • Hamiltonian PDEs
  • Hamiltonian problems
  • HBVMs
  • Hermite–Obreshkov methods
  • hierarchical splines
  • high order discontinuous Galerkin finite element schemes
  • High performance computing
  • higher-order finite element methods
  • highly oscillatory problems
  • histogram specification
  • hyperbolic partial differential equations
  • initial value problems
  • isogeometric analysis
  • limited memory
  • line integral methods
  • Linear systems
  • local refinement
  • low rank completion
  • Mathematics & science
  • matrix ODEs
  • mean-square stability
  • mixed-index problems
  • multistep methods
  • null-space
  • Numerical analysis
  • Numerical methods
  • one-step methods
  • optimal basis
  • Order
  • ordinary differential equations
  • Poisson problems
  • preconditioners
  • Runge–Kutta
  • scientific computing
  • shock waves and discontinuities
  • spectral (eigenvalue) and singular value distributions
  • stochastic differential equations
  • stochastic multistep methods
  • stochastic Volterra integral equations
  • structured matrices
  • stump
  • symplecticity
  • THB-splines
  • time fractional differential equations
  • time harmonic Maxwell’s equations and magnetostatic problems
  • tree
  • vectorization and parallelization
  • Volterra integral equations
  • Volterra integro–differential equations

Links

DOI: 10.3390/books978-3-03897-667-7

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