The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

this paper presents h∞ control problem for input-delayed systems. a neutral system approach is considered to the design of pd controller for input delay systems in presence of uncertain time-invariant delay. using this approach, the resulting closed-loop system turns into a specific time-delay system of neutral type. the significant specification of this neutral system is that its delayed coeff...

In contrast to the determinant, no algorithm is known for exact determination of permanent a square matrix that runs in time polynomial its dimension. Consequently, non interacting fermions are classically efficiently simulatable while non-interacting bosons not, underpinning quantum supremacy arguments sampling output distribution photon interferometer arrays. This work introduces graph-theore...