Sentence examples for matrix at time from inspiring English sources
(H_k) is the measurement matrix at time (t_k).
where (widehat {mathbf {x}}_{k-1|k-1}) and P k−1|k−1 are the estimated global state vector and error covariance matrix at time k−1.
So, given a set ({mathcal {U}}) of U sparsifying basis matrices, the minimal coherence basis matrix at time t can be selected by solving the following optimization problem, {hat{boldsymbol{Psi}}}_{t} = {underset{{{boldsymbol{Psi}}}_{t}}{text{arg min}}} mu ({mathbf{J}}_{t}{boldsymbol{Psi}}_{t}),,, {mathrm{s.t.}} {boldsymbol{Psi}}_{t} in {mathcal{U}}.
By differentiating Eq. (2) with respect to u, we obtain the tangential contact stiffness matrix at time T + ΔT : (3) where the symbol ⊗ denotes the outer product of two vectors, and we assume that the contact surfaces do not deform very much, so that the differential of the contact normal T+ΔTn with respect to du can be ignored.
(U t)=(mu_{kj}(t))in R^{Ntimes N}) is the zero-row-sum outer coupling matrix at time t denoting the network topology and defined as follows: if node j has influence on node k ((kneq j)) at time t, then (mu_{kj}(t)neq 0); otherwise, (mu_{kj}(t)=0).
where n m (n) is the additive white Gaussian noise (AWGN) and Hm,k(n) is an Nc × Nc circulant time domain (TD) channel matrix at time instant n, which is formed by the channel response vector hm,k(n) for the link between transmit antenna k and receive antenna m.
From the simulation results of a dynamic imbibition process study, it was found that the transverse pressure gradients between the fracture and matrix at times pushed the surfactant further into the matrix (Asl et al. 2010).
where [M], [C], and [K]t+Δt are the system mass, damping, and tangent stiffness matrices at time t + Δt, respectively; u ¨ Open image in new window, u ˙ Open image in new window and Δu are the accelerations, velocities, and incremental displacement vectors at time t + Δt, respectively.
Thus, much of the 3-OHBA detected in the matrix fraction at time 0 presumably originated in the liver.
By solving this equation (see Additional file 1 for details) the state sensitivity matrix can be written as (4) S = ∫ t 0 t V τ ∂ f ∂ p dτ where V is a matrix computed at time τ.
From the previous discussion, and assuming a pinhole camera model, the camera projection matrices at times k1 and k2 are, respectively, Figure 3 Relative pose of the camera at two different time points k 1 and k 2. The world coordinate system has its origin at the position of the camera center at k1. P 1 = K [ I | 0 ] P 2 = K R x R y [ I | - C 2 ] (20).
