Inverse problem

Process of calculating from a set of observations the causal factors that produced them, or deducing the causes or parameters that we cannot directly observe from their effects

Nº Q1567213 ★★

Uncommon · Knowledge

Inverse problem

Process of calculating from a set of observations the causal factors that produced them, or deducing the causes or parameters that we cannot directly observe from their effects

An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in X-ray computed tomography, source reconstruction in acoustics, or calculating the density of the Earth from measurements of its gravity field. It is called an inverse problem because it starts with the effects and then calculates the causes.

Last price

—

Floor price

—

7-day median

—

30-day sales

0

30-day range

—

In circulation

0

Price history

Show table
Datemedian LowHighsales

Sales history

Last sale
—
30-day average
—
30-day low
—
30-day high
—
Sales 7d
0
Sales 30d
0

No sales yet.

Anonymous sales: no buyer or seller shown. Figures count player-to-player sales only.

From Wikipedia

An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in X-ray computed tomography, source reconstruction in acoustics, or calculating the density of the Earth from measurements of its gravity field. It is called an inverse problem because it starts with the effects and then calculates the causes. It is the inverse of a forward problem, which starts with the causes and then calculates the effects. Inverse problems are some of the most important mathematical problems in science and mathematics because they tell us about parameters that we cannot directly observe. They can be found in system identification, optics, radar, acoustics, communication theory, signal processing, medical imaging, computer vision, geophysics, oceanography, meteorology, astronomy, remote sensing, natural language processing, machine learning, nondestructive testing, slope stability analysis and many other fields.

Text: Wikipédia, CC BY-SA 4.0. · Image: Grzegorz Knor (Public domain) ·

Related cards

Confirmation