Sentence examples for approximation subspace from inspiring English sources

In this paper, the projection approximation subspace tracking (PAST) recursive algorithm is applied as an alternative method to identify the time-varying modal parameters.

Projection approximation subspace tracking.

In [20], the SOI steering vector is estimated with the orthonormal projection approximation subspace tracking and subspace projection.

A blind bidirectional channel tracking algorithm, based on the projection approximation subspace tracking (PAST) algorithm, is applied in both terminals.

Yang et al. propose a fast space-time adaptive processing (STAP) method based on projection approximation subspace tracking with sparse constraint [31].

This algorithm, referred to as the constrained projection approximation subspace tracking (CPAST) algorithm, guarantees the orthonormality of the estimated signal subspace basis at each iteration.

Methods which do not require approximation subspaces to conform to the smoothness requirements dictated by the PDE are very attractive for such problems.

Define the sequence of finite-dimensional approximation subspaces ({V^{h}_{0}(Omega ) }_{h>0}) of (H^{1}_{0}(Omega)) by V^{h}_{0}(Omega):= bigl{ phiin H^{1}_{0}( Omega) mid phi _{|_{Omega_{i}}} inwp_{r}(Omega_{i}), forall i=1,2,ldots, n bigr}, (27) where (wp_{r}(Omega_{i})) is a Lagrange interpolation space of polynomials with degree at most r over the element (Omega_{i}) for each (i=1,2,ldots,n).

To efficiently calculate large matrix exponentials, Krylov subspace approximation is directly applied to the implicit integration factor (IIF) methods.

HOPLS regression is used to explore the multi-linear subspace approximation for both the selected parameters and the HRTF tensor.

The following discussions focus on how to determine the dimensions D′ and F′ of the ICT and the performance of the HRTF tensor subspace approximation: 1.