Determination of finite-difference weights using scaled binomial windows

Chunlei Chu, Paul L. Stoffa

Research output: Contribution to journalArticlepeer-review

104 Scopus citations


The finite-difference method evaluates a derivative through a weighted summation of function values from neighboring grid nodes. Conventional finite-difference weights can be calculated either from Taylor series expansions or by Lagrange interpolation polynomials. The finite-difference method can be interpreted as a truncated convolutional counterpart of the pseudospectral method in the space domain. For this reason, we also can derive finite-difference operators by truncating the convolution series of the pseudospectral method. Various truncation windows can be employed for this purpose and they result in finite-difference operators with different dispersion properties. We found that there exists two families of scaled binomial windows that can be used to derive conventional finite-difference operators analytically. With a minor change, these scaled binomial windows can also be used to derive optimized finite-difference operators with enhanced dispersion properties. © 2012 Society of Exploration Geophysicists.
Original languageEnglish (US)
Pages (from-to)W17-W26
Number of pages1
Issue number3
StatePublished - May 2012
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Stoffa would like to acknowledge the King Abdullah Universityof Science and Technology for their support of his research. We aregrateful to associate editor Stig Hestholm and the reviewers for theirconstructive comments which helped improve the original manuscript.We thank ConocoPhillips for permission to publishthis work.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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