According to the theory of scalar diffraction, first, the equipollence of spatial distribution of the plane-wave interferential field and parallel projective sine grating is discussed.
By using the result of the scalarization of the weak efficient solutions set, a result of the connectedness of the weak efficient solution sets is obtained in topological vector space.
It's a little awkward to work with at 1st, because that left hand side represents matrix factor multiplication, but the right hand side here is scalar vector multiplication.
Now, the more linear, algebra oriented way to describe coordinates is to think of each of these numbers as a scaler, a thing that stretches or squishes vectors.
So in the conception of vectors as lists of numbers, multiplying a given vector by a scaler means multiplying each one of those components by that scaler.
Our concept of the character is actually a composition of multiple Unicode scalar values, and decomposing these correctly is critical to getting that fidelity with Unicode, the characters, and the string API.
我们对于字符的概念实际上是由多个统一码标量值构成的,正确地把它解构对于统一码的精确以及字符和字符串 API 的精确都至关重要。
Now, if you let both scalers range freely and consider every possible vector that you can get, there are two things that can happen for most pairs of vectors.
But some special vectors do remain on their own span, meaning the effect that the matrix has on such a vector is just to stretch it or squish it like a scalar.
You'll see in the following videos what I mean when I say that linear algebra topics tend to revolve around these two fundamental operations vector edition and scalar multiplication.
Take a moment to think about all the different vectors that you can get by choosing two scalers, using each one to scale one of the vectors, than adding together, what you get.
You'll choose three different scalers, scale each of those vectors, and then add them all together, and again, the span of these vectors is the set of all possible linear combination.
You can kind of imagine turning two different knobs to change the two scalers, defining the linear combination, adding the scaled vectors, and following the tip of the resulting vector.
Another way to think about it is that you're making full use of the three freely changing scalers that you have at your own disposal to access the full three dimensions of space.