But limited to the array manifold and the spatial dimension of
subspace, DPD methods in ULA can only realize the positioning whose target number is smaller than the number of physical sensors, which is defined as overdetermined condition.
As a byproduct, Theorem 3 shows that in the case of a reducible i/o equation the
subspace, determining the state coordinates, admits a basis with a certain structure, explicitly related to the reduced i/o equation.
They circumvent one drawback of solvers based on Krylov
subspaces, namely that the
subspace dimension grows with each iteration of the method, at least if no restarts are used.
Over several decades, this topic has been extensively studied and varieties of techniques including multiple signal classification (MUSIC) [7], minimum norm (MN) [8], estimation of the signal parameters via rotational invariance techniques (ESPRIT) [9],
subspace fitting (SF) [10], and maximum likelihood (ML) [11] have been developed.
In the past twenty years, the
subspace model identification (SMI) has received great attention, not only because of its excellent convergence and simple numerical calculation, but also the suitability for the application in the estimation, prediction, and control algorithm.
Furthermore, authors have shown that CLBS is closely related to the invariant
subspace; namely, exact solutions defined on invariant
subspaces for equations or their variant forms can be obtained by using the CLBS method [12-24].
The range M of an orthogonal projection R in a Krein space K is a closed
subspace of K and the space K can be decomposed as
We determine what Tychonoff spaces Y are such that L(Y) can be embedded as a topological vector
subspace in L(G) and L(Q), respectively.
The first step of the PCA-based restoration is to create an image
subspace which is generated by repeatedly blurring a query face.