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97:01
L.S. Johnson, A. Kaulgud and R.C. Sharpley
- A 3D user
environment for partial differential equations
- 97:02
Z. Gao, A. Andreev and R.C. Sharpley
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Data compression and elementary encoding of wavelet coefficients
- 97:03
A.S. Fokas, L.-Y. Sung and D. Tsoubelis
- The inverse spectral method for colliding gravitational waves
- (Math. Phys. Anal. Geom. 1 (1999), 313-330)
- 97:04
S.C. Brenner and L.-Y. Sung
- Balancing domain decomposition for nonconforming plate elements
- (Numer. Math. 83 (1999), 25--52)
- 97:05
S.C. Brenner
- The condition number of the Schur complement in domain decomposition
- (Numer. Math. 83 (1999), 187-203)
- 97:06
A. Cohen, R. DeVore and R. Hochmut
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Restricted nonlinear approximation
- 97:07
A. Cohen, R. DeVore, P. Petrushev and H. Xu
-
Nonlinear approximation and the space BV(R2)
- 97:08
K. Oskolkov
-
Schrödinger equation and oscillatory Hilbert transforms of second
degree
- 97:09
K. Oskolkov
-
Ridge approximation, Chebyshev-Fourier analysis and optimal quadrature
formulas
- 97:10
V. Temlyakov
-
The best $m$-term approximation and greedy algorithms
- 97:11
V. Temlyakov
-
Greedy algorithms and $m$-term approximation with regard to redundant
dictionaries
- 97:12
V. Temlyakov
-
Nonlinear Kolmogorov's widths
- 97:13
V. Temlyakov
-
Nonlinear $m$-term approximation with regard to the multivariate Haar
system
-
97:14
H. Wang, H.K. Dahle, R.E. Ewing, M.S. Espedal, R.C. Sharpley and S. Man
- An Eulerian-Lagrangian localized adjoint method for
advection-dispersion equations in two dimensions and its comparison
to other schemes
- 97:15
M. Al-Lawatia, R.C. Sharpley and H. Wang
- Second-order characteristic methods for advection-diffusion equations and comparison to other schemes
- 97:16
H. Wang and B.G. Ersland
-
A characteristic domain
decomposition technique for two-phase
flows with interfaces
- 97:17
H. Wang, M. Al-Lawatia and R.C. Sharpley
-
A characteristic domain
decomposition and space-time local refinement
method for first-order
linear hyperbolic equations with interfaces
- 97:18
P.P. Petrushev
-
Approximation by ridge functions and neural networks
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