2004
DOI: 10.1137/1.9780898717952
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Numerical Computing with Matlab

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Cited by 510 publications
(293 citation statements)
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“…Considering that water properties mix much more efficiently along isopycnals than across them, and considering that isopycnals in the top ϳ2,000 m of the ocean are found at depths differing by several hundreds of meters on either side of the Gulf Stream as a consequence of geostrophy and the tendency of surface currents to decrease with depth (Knauss 1978), we opted for an isopycnal-based rather than a depth-based analysis of the temperature-salinity-oxygen data. Vertical profiles of temperature, salinity, and oxygen at discrete depths were interpolated onto potential density surfaces by using the Matlab (The Mathworks Inc., Natick, Massachusetts) interp1 function with a shape-preserving, piecewise cubic Hermite interpolating polynomial (pchip) method that ensures continuous first derivatives at the data points while generally avoiding overshooting (Moler 2004).…”
Section: Methodsmentioning
confidence: 99%
“…Considering that water properties mix much more efficiently along isopycnals than across them, and considering that isopycnals in the top ϳ2,000 m of the ocean are found at depths differing by several hundreds of meters on either side of the Gulf Stream as a consequence of geostrophy and the tendency of surface currents to decrease with depth (Knauss 1978), we opted for an isopycnal-based rather than a depth-based analysis of the temperature-salinity-oxygen data. Vertical profiles of temperature, salinity, and oxygen at discrete depths were interpolated onto potential density surfaces by using the Matlab (The Mathworks Inc., Natick, Massachusetts) interp1 function with a shape-preserving, piecewise cubic Hermite interpolating polynomial (pchip) method that ensures continuous first derivatives at the data points while generally avoiding overshooting (Moler 2004).…”
Section: Methodsmentioning
confidence: 99%
“…To evaluate the effectiveness of our approach, we set up experiments using benchmarks collected from disparate sources, including those from [10,22,23]. Table 1 gives a short description of the benchmarks together with a summary of the results of our analyses, which we discuss in more detail in the following subsections.…”
Section: Resultsmentioning
confidence: 99%
“…The second example, tridisolve is a Matlab function from [10]. The forward analysis information is shown in Fig.…”
Section: Using the Analysesmentioning
confidence: 99%
“…where y H is the hermitian transpose of y [55,56,42]. At exceptional points the left and right eigenvectors are perpendicular, and the scalar product y H x vanishes, leading to divergence of the eigenvalue condition number.…”
Section: Appendix B1 Condition Number Of An Eigenvaluementioning
confidence: 99%