Confirming the observations of [7], [8] we found between-individual Shotgun UniFrac distances to be significantly greater than within-individual distances (Figure 3b; p = 3×10−23, one-tailed t-test; p<0.001, Monte Carlo t-test with 1000 iterations), suggesting stability in distal gut phage community membership over time.
Based on lifting technique and Youla-parametrization, the 2-DOF controller design, i.e., the design of ILC and IFT, is formulated into one constrained optimization problem where an optimal combination of the learning matrix and feedback controller is found in each iteration with guaranteed stability.
This λ should not penalize too strong so that in each iteration of the stability selection the true non-zero coefficients are selected with high probability.
The controller design is based on skewed-¨ DK-iteration and the stability of the closed-loop nonlinear system is analyzed.
As a corollary, a refinement to Ostrowski's sufficient condition for local convergence in finite spaces is obtained, which applies to many models, e.g. in economics, ecology or game theory, where one has an interest in fixed point iterations and local stability of discrete dynamic processes.
The incompressible Navier Stokes equations are solved with a fractional-step scheme which is second-order-accurate in space and time, while the fluid solid coupling is achieved with a partitioned approach including multiple sub-iterations to increase stability for light, rigid bodies.
The number of iterations for the stability selection was set to 500 and the weakness parameter was set to κ = 0.2.
Hence, all eigenvalues λ i (P n ) are upper bounded by the constant c, independent of the number of iterations n, ensuring the stability of the iterative process.
For the i-th iteration, k=λ1∗i and the stability S i is computed by the mean of all stabilities between F i and F j (j=1,2,…i−1), where F i and F j represent the i-th and the j-th selected feature subset, respectively.
This paper presents some generalizations of results concerning the stability of iterations in the sense that the iteration scheme subject to error sequences converges asymptotically to its nominal fixed point provided that the iteration error converges asymptotically to zero.
