observation matrix - définition. Qu'est-ce que observation matrix
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Qu'est-ce (qui) est observation matrix - définition

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
Geophysical inverse theory; Inverse theory; Observation function; Inverse modeling; Inverse modelling; Forward operator; Observation operator; Observation matrix; Inverse problems; Forward problem; Model inversion; Linear inverse problem; Inverse model; Inversion problem; Non-linear inverse problems; Linear inverse problems; Doppler tomography

MATRIX MATH         
  • The vectors represented by a 2-by-2 matrix correspond to the sides of a unit square transformed into a parallelogram.
  • orientation]], since it turns the counterclockwise orientation of the vectors to a clockwise one.
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  • An example of a matrix in Jordan normal form. The grey blocks are called Jordan blocks.
  • An undirected graph with adjacency matrix:
<math display="block">\begin{bmatrix}
1 & 1 & 0 \\
1 & 0 & 1 \\
0 & 1 & 0
\end{bmatrix}.</math>
  • Two different Markov chains. The chart depicts the number of particles (of a total of 1000) in state "2". Both limiting values can be determined from the transition matrices, which are given by <math>
\begin{bmatrix}
 0.7 & 0\\
 0.3 & 1
\end{bmatrix}</math> (red) and <math>
\begin{bmatrix}
 0.7 & 0.2\\
 0.3 & 0.8
\end{bmatrix}</math> (black).
  • Schematic depiction of the matrix product '''AB''' of two matrices '''A''' and '''B'''.
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  • indefinite]].
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RECTANGULAR ARRAY OF NUMBERS, SYMBOLS, OR EXPRESSIONS, ARRANGED IN ROWS AND COLUMNS
Matrix (Mathematics); Matrix (math); Submatrix; Matrix theory; Matrix (maths); Submatrices; Matrix Theory and Linear Algebra; Infinite matrix; Square (matrix); Matrix operation; Square submatrix; Matrix(mathematics); Real matrix; Matrix math; Matrix index; Equal matrix; Matrix equation; Matrix (computer science); Matrix notation; Empty matrix; Real matrices; Principal submatrix; Array (mathematics); Matrix power; Complex matrix; Complex matrices; Applications of matrices; Rectangular matrix; Uniform matrix
<language> An early system on the UNIVAC I or II. [Listed in CACM 2(5):1959-05-16]. (1997-02-27)
Logical matrix         
  • Multiplication of two logical matrices using [[boolean algebra]].
MATRIX WITH ENTRIES FROM THE BOOLEAN DOMAIN B = {0, 1}
Binary matrix; (0,1) matrix; (0,1)-matrix; (0,1)-matrices; 0,1-matrix; 0-1 matrix; Matrix logic; Zero-One matrix; Logical vector; Logical matrices
A logical matrix, binary matrix, relation matrix, Boolean matrix, or (0, 1) matrix is a matrix with entries from the Boolean domain Such a matrix can be used to represent a binary relation between a pair of finite sets.
Bonilla observation         
FIRST SIGHTING OF UNIDENTIFIED FLYING OBJECTS
Jose Bonilla Observation; José Bonilla Observation
On August 12, 1883, the astronomer José Bonilla reported that he saw more than 300 dark, unidentified objects crossing before the Sun while observing sunspot activity at Zacatecas Observatory in Mexico. He was able to take several photographs, exposing wet plates at 1/100 second.

Wikipédia

Inverse problem

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 have wide application in system identification, optics, radar, acoustics, communication theory, signal processing, medical imaging, computer vision, geophysics, oceanography, astronomy, remote sensing, natural language processing, machine learning, nondestructive testing, slope stability analysis and many other fields.