The answer will depend on orthogonal to WHAT!
What are difference between scalars and vectors
In a plane, each vector has only one orthogonal vector (well, two, if you count the negative of one of them). Are you sure you don't mean the normal vector which is orthogonal but outside the plane (in fact, orthogonal to the plane itself)?
Given one vector a, any vector that satisfies a.b=0 is orthogonal to it. That is a set of vectors defining a plane orthogonal to the original vector.The set of vectors defines a plane to which the original vector a is the 'normal'.
The zero vector is not perpendicular to all vectors, but it is orthogonal to all vectors.
The answer will depend on orthogonal to WHAT!
Vectors that go in different directions are called orthogonal vectors. This means that the vectors are perpendicular to each other, with a 90 degree angle between them.
What are difference between scalars and vectors
In a plane, each vector has only one orthogonal vector (well, two, if you count the negative of one of them). Are you sure you don't mean the normal vector which is orthogonal but outside the plane (in fact, orthogonal to the plane itself)?
Given one vector a, any vector that satisfies a.b=0 is orthogonal to it. That is a set of vectors defining a plane orthogonal to the original vector.The set of vectors defines a plane to which the original vector a is the 'normal'.
When they are at right angles to one another.
The zero vector is not perpendicular to all vectors, but it is orthogonal to all vectors.
Orthogonal and perpendicular are essentially the same thing: When two lines, planes, etc. intersect at a right angle, or 90 degrees, they are orthogonal/perpendicular.Orthogonal is simply a term used more commonly for vectors, when they have a scalar/inner/dot product of 0, as:vector u X vector v = (length of vector u) X (length of vector v) X cos @ ,@ being the angle between the two vectors.When the scalar product is 0, that is because @ is 90 degrees, and cos 90 = 0. Therefore, the vectors u and v are orthogonal.
Without the difference between scalars and vectors the Universe doesn't work !
shut up now
Orthogonal signal space is defined as the set of orthogonal functions, which are complete. In orthogonal vector space any vector can be represented by orthogonal vectors provided they are complete.Thus, in similar manner any signal can be represented by a set of orthogonal functions which are complete.
Vectors are said to be orthogonal if their dot product is zero.Vectors in Rn are perpendicular if they are nonzero and orthogonal.