The phrase "a singular value of" is correct and usable in written English.
It can be used in contexts involving mathematics, statistics, or discussions about unique characteristics or properties of a set.
Example: "In this analysis, we will focus on a singular value of the dataset that represents the average temperature."
Alternatives: "a unique value of" or "one specific value of".
By Theorem 2 in [2], we know that (lambda_{0}) is a singular value of (mathcal{A}).
We call lambda_{0}=maxbigl{ vert lambda vert :lambda mbox{ is a singular value of }mathcal {A}bigr} the largest singular value [2].
Here, lambda_{0}=maxbigl{ |lambda|:lambda text{ is a singular value of } mathcal{A}bigr} is called the largest singular value [6].
If (lambdainmathbb{C}), (xinmathbb{C}^{m}backslash{0}), and (yin mathbb{C}^{n}backslash{0}) are solutions of textstylebegin{cases} mathcal{A}x^{p-1}y^{q}=lambda x^{[l-1]}, mathcal{A}x^{p}y^{q-1}=lambda y^{[l-1]}, end{cases} then we say that λ is a singular value of (mathcal{A}), x and y are a left and a right eigenvectors of (mathcal{A}), associated with λ.
Indeed, the implementation they propose relies on a singular value decomposition of the Laplacian of the network, which is intensive to compute and cannot be stored in memory.
Bi-natural orbitals, which are obtained for a pair of wave functions by a singular value decomposition of a reduced transition density matrix were recently proposed [24].
The reduced basis is made of the leading eigenvectors computed by a Singular Value Decomposition of the snapshot span basis.
A reduced dimensional subspace is then obtained after a singular value decomposition of the information matrix, leading to the use of basis functions (spatial patterns) in the original parameter space.
A convenient way to determine the scores and weights in (3) is via a singular value decomposition of the matrix formed by the two-way table of G × E effects.
For SVDI (Troyanskaya et al. 2001), a singular value decomposition of genotype matrix M was used to obtain a set of the k most significant Eigen-vectors of the markers.
For each participant, the dimensionality of spectra was reduced to 4 frequency modes derived from a singular value decomposition of the spectra (Chen et al. 2009).
