Compression is ubiquitous in this class of systems.
We investigate a class of dynamical systems that have affine invariant subspaces and give a necessary and sufficient condition on the dimensionality of the invariant affine subspaces for the robustness of HCs in this class of systems.
In this class of systems all links of one BS share a limited power budget and are impaired by the power assigned to other users in the air interface.
Secondary changes in seismic properties related to poroelastic phenomenon, including so-called double porosity effects [34], may also be present in this class of systems due to heterogeneous precipitation or micro-porosity within the precipitate phase.
We show that nonlinearity is neither necessary nor sufficient for breaking reciprocity in this class of systems; rather, it depends on the boundary conditions, the symmetries of the governing linear and nonlinear operators, and the choice of the spatial points where the non-reciprocity criterion is tested.
In order to control this class of systems, the systems are decomposed by using the mean value theory, the unknown functions are approximated by using the neural networks, and Barrier Lyapunov function is introduced.
In order to stabilize this class of systems, distributed dynamic output feedback controllers are considered, and tractable linear matrix inequality (LMI -based aLMI -basedfor the derivalgorithmsistributed controllers are presented.
Despite this ubiquitous parametric uncertainty, key temporal outputs are typically robust to large changes in most parameters for this class of systems biology models, a property called "sloppiness" that, to some extent, mitigates the problem that unidentifiable parameters cause, with respect to reproducing biologically relevant behavior.
In contrast, very few results are known for degenerate inverse problems, even though this class of systems occurs in many interesting problems in engineering and applied mathematics.
