Examples of using Two vectors in English and their translations into Vietnamese
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Colloquial
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Ecclesiastic
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Computer
Two vectors are equal.
Angle between the two vectors.
There are two vectors of perseverance.
Distance between two vectors¶.
Two vectors are considered equal if they have the same magnitude and direction.
When are two vectors equal?
The Distance Between Two Vectors.
When are two vectors equal?
What is the angle between two vectors?
The dot product of two vectors a and b is given by.
Finding the angle between two vectors.
As a result, these two vectors affect the cost of the object and its service life.
The distance between the two vectors.
The dot product of two vectors A=[A1, A2,…, An] and B=[B1, B2,…, Bn] is defined as:[1].
Let θ be the angle between two vectors and.
Any two vectors ei, ej where i≠j are orthogonal, and all vectors are clearly of unit length.
For instance,the function plot can be utilized to generate a graph from two vectors x and y.
When the bilinear form applied to two vectors results in zero, then they are orthogonal.
Given two vectors a and b separated by angle θ(see image right), they form a triangle with a third side c= a- b.
The first operation, vector addition, takes any two vectors v and w and outputs a third vector v+ w.
The resultant of two vectors can be found using either the parallelogram method or the triangle method.
This definition can be formalized in Cartesian space by defining the dot product andspecifying that two vectors in the plane are orthogonal if their dot product is zero.
In the Cartesian plane, two vectors are said to be perpendicular if the angle between them is 90°(i.e. if they form a right angle).
In mathematics, Chebyshev distance(or Tchebychev distance), maximum metric, or L∞ metric[1]is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
In linear algebra, two vectors in an inner product space are orthonormal if they are orthogonal(or perpendicular along a line) unit vectors. .
If we view the DFT as just a coordinate transformation which simply specifies the components of a vector in a new coordinate system,then the above is just the statement that the dot product of two vectors is preserved under a unitary DFT transformation.
The absolute value oftheir dot product of the two vectors-- and remember, this is just a scalar quantity-- is less than or equal to the product of their lengths.
Two vectors of Rn are in the same congruence class modulo the subspace if and only if they are identical in the last n- m coordinates.
If the system is controllable then these two vectors can span the entire plane and can be done so for time. The assumption made that the initial state is zero is merely for convenience.
Recalling that two vectors are perpendicular if and only if their dot product is zero, it follows that the desired plane can be described as the set of all points such that.