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Numerical algorithms for problems in analysis and algebra, scientific computation

2 votes

Smoothing out Noisy Data

Convolve the data (simplest thing is to use a box) and renormalize. Use the conv command in MATLAB. EDIT: You might also consider splines. Keep the dicontinuity of higher derivatives in mind if you d …
Steve Huntsman's user avatar
9 votes
Accepted

Rigorous numerical integration

Interval arithmetic methods will permit rigorous bounds. You might try INTLAB. There are various books on rigorous numerics, e.g., Warwick Tucker's Validated Numerics, and the journal Reliable Computi …
Steve Huntsman's user avatar
1 vote

Convergence of iterative algorithm.

Your system of equations is of the form $Az = b$, where $z_{i(\alpha)} = x^\alpha$ and $i(\alpha)$ is the grlex index of $\alpha \in$ $ X_{n,k} \equiv$ {$\beta \in \mathbb{Z}^n: \sum_j \beta_j = k$} …
Steve Huntsman's user avatar
6 votes

Minimal number of operations of a discrete Fourier transform

Considering a "flop" as a real arithmetic operation and ignoring precision, and apropos of @skbmoore's reference, the paper [Johnson, S. G. and Frigo, M. "A Modified Split-Radix FFT With Fewer Arithme …
Steve Huntsman's user avatar
5 votes

The application of Lanczos Algorithm on sparse matrix

More generally, black-box linear algebra is an entire subfield of linear algebra, in which the matrix-vector multiplication is treated as an oracle. Generally if this oracle has subquadratic complexit …
Steve Huntsman's user avatar
2 votes

approximate matrix diagonalization algorithm

You might consider iterative and black-box methods, and particularly Arnoldi.
Steve Huntsman's user avatar
4 votes

Rigorous numerics for maxima and minima (one variable)

There is an interval algorithm for finding global extrema. See, e.g. section 5.5 of Jaulin et al. or 5.2 of Tucker for overviews, with some C++ source code.
Steve Huntsman's user avatar
0 votes

Approximate Algorithms for Poisson's Equation (PDE)

How about the fast multipole method? (Or does that count as multigrid?)
Steve Huntsman's user avatar
5 votes

Automatic vs numerical differentiation of a function known from samples

If your $f$ is a probability distribution, then you can use a kernel density estimate to estimate the derivative. For a bit more detail and relevant references, see section 2.2 of A Tutorial on Kernel …
Steve Huntsman's user avatar
2 votes
Accepted

Linear system with sum of Kronecker products

The recent state of the art is described in section 7.2 of Simoncini, V. "Computational methods for linear matrix equations." SIAM Rev. 58, 377 (2016), https://doi.org/10.1137/130912839. Your equation …
Steve Huntsman's user avatar
4 votes

Scaling a set of reals to be nearly integers

Let $R = \{x_1,\dots,x_n\}$. An integer relation between $x_j$ and $-1$ is a pair $(a_j,a_{j*}) \in \mathbb{Z}^2$ satisfying $a_j x_j = a_{j*}$. Suppose there are such integer relations for all $j \in …
Steve Huntsman's user avatar
19 votes

What is the time complexity of computing sin(x) to t bits of precision?

$\pi$ can be computed with the hexadecimal BBP series, though apparently there are faster known ways to compute all of the bits to some level. Knuth attributes to Brent JACM 23, 242 (1976) the result …
Steve Huntsman's user avatar
3 votes
Accepted

Using Fourier Transform to speed up calculation of forces following an inverse square law

The FFT is an important part of the fast multipole method, which is probably what you would want to use.
Steve Huntsman's user avatar