Orthogonal frequency-division multiplexing
No. They are orthogonal.
orthogonal cutting is a 2D cutting having 2 forces i.e cutting force and feed force where as oblique cutting is a 3D cutting having additional force i.e radial or passive force.
OCDMA: Its nothing but Optical code division multiple access or Orthogonal code divsion multiple access..
the difrrence is that one starts with an s and the other starts with an oalso they are spelt diffrentlyso does this answer your question Kane
a family of curves whose family of orthogonal trajectories is the same as the given family, is called self orthogonal trajectories.
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.
The answer will depend on orthogonal to WHAT!
it is planning of orthogonal planning
it is planning of orthogonal planning
Orthogonal - novel - was created in 2011.
Orthogonal is a term referring to something containing right angles. An example sentence would be: That big rectangle is orthogonal.
Richard Askey has written: 'Three notes on orthogonal polynomials' -- subject(s): Orthogonal polynomials 'Recurrence relations, continued fractions, and orthogonal polynomials' -- subject(s): Continued fractions, Distribution (Probability theory), Orthogonal polynomials 'Orthogonal polynomials and special functions' -- subject(s): Orthogonal polynomials, Special Functions
A matrix A is orthogonal if itstranspose is equal to it inverse. So AT is the transpose of A and A-1 is the inverse. We have AT=A-1 So we have : AAT= I, the identity matrix Since it is MUCH easier to find a transpose than an inverse, these matrices are easy to compute with. Furthermore, rotation matrices are orthogonal. The inverse of an orthogonal matrix is also orthogonal which can be easily proved directly from the definition.
Three of them are "orthogonal", "orthodontist", and "orthopedic", and "orthogonal" is a very important word in mathematics. For one example, two vectors are orthogonal whenever their dot product is zero. "Orthogonal" also comes into play in calculus, such as in Fourier Series.
Orthogonal view is basically seeing something in 2 dimensions that is actually 3 dimensions. The projection lines in these views are orthogonal to the projection plane which causes it to be 2 dimensions.
Orthogonal view is basically seeing something in 2 dimensions that is actually 3 dimensions. The projection lines in these views are orthogonal to the projection plane which causes it to be 2 dimensions.