Fast Fourier transform and Numerical analysis

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Fast Fourier transform and Numerical analysis

Fast Fourier transform vs. Numerical analysis

A fast Fourier transform (FFT) is an algorithm that samples a signal over a period of time (or space) and divides it into its frequency components. Numerical analysis is the study of algorithms that use numerical approximation (as opposed to general symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics).

Similarities between Fast Fourier transform and Numerical analysis

Fast Fourier transform and Numerical analysis have 6 things in common (in Unionpedia): Algorithm, Floating-point arithmetic, Matrix decomposition, Numerical stability, Partial differential equation, Round-off error.

Algorithm

In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.

Algorithm and Fast Fourier transform · Algorithm and Numerical analysis · See more »

Floating-point arithmetic

In computing, floating-point arithmetic is arithmetic using formulaic representation of real numbers as an approximation so as to support a trade-off between range and precision.

Fast Fourier transform and Floating-point arithmetic · Floating-point arithmetic and Numerical analysis · See more »

Matrix decomposition

In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices.

Fast Fourier transform and Matrix decomposition · Matrix decomposition and Numerical analysis · See more »

Numerical stability

In the mathematical subfield of numerical analysis, numerical stability is a generally desirable property of numerical algorithms.

Fast Fourier transform and Numerical stability · Numerical analysis and Numerical stability · See more »

Partial differential equation

In mathematics, a partial differential equation (PDE) is a differential equation that contains unknown multivariable functions and their partial derivatives.

Fast Fourier transform and Partial differential equation · Numerical analysis and Partial differential equation · See more »

Round-off error

A round-off error, also called rounding error, is the difference between the calculated approximation of a number and its exact mathematical value due to rounding.

Fast Fourier transform and Round-off error · Numerical analysis and Round-off error · See more »

The list above answers the following questions

What Fast Fourier transform and Numerical analysis have in common
What are the similarities between Fast Fourier transform and Numerical analysis

Fast Fourier transform and Numerical analysis Comparison

Fast Fourier transform has 154 relations, while Numerical analysis has 145. As they have in common 6, the Jaccard index is 2.01% = 6 / (154 + 145).

References

This article shows the relationship between Fast Fourier transform and Numerical analysis. To access each article from which the information was extracted, please visit:

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