A new approach to robust ltering, prediction and smoothing of discrete-time signal vectors is presented. Linear time-invariant lters are designed to be insensitive to spectral uncertainty in signal models. The goal is to obtain a simple design method, leading to lters which are not overly conservative. Modelling errors are described by sets of models, parameterized by random variables with know...

reliability wiener number is a modification of the original wiener number in which probabilities are assigned to edges yielding a natural model in which there are some (or all) bonds in the molecule that are not static. various probabilities naturally allow modelling different types of chemical bonds because chemical bonds are of different types and it is well-known that under certain condition...

let g and h be two graphs. the corona product g o h is obtained by taking one copy of gand |v(g)| copies of h; and by joining each vertex of the i-th copy of h to the i-th vertex of g,i = 1, 2, …, |v(g)|. in this paper, we compute pi and hyper–wiener indices of the coronaproduct of graphs.

Let X be a real separable Hilbert space. Q linear, bounded, positive and compact operator on let A : Dom ( ) ⊆ → self-adjoint generating strongly continuous semigroup . F (smooth enough) function { W t } ≥ 0 -valued cylindrical Wiener process. For any α , we are interested in the mild solution x of semilinear stochastic partial differential equation d = + > ; ∈ its associated transition (0.1) P...

Wiener index is a topological index based on distance between every pair of vertices in a graph G. It was introduced in 1947 by one of the pioneer of this area e.g, Harold Wiener. In the present paper, by using a new method introduced by klavžar we compute the Wiener and Szeged indices of some nanostar dendrimers.

iener theory, formulated by Norbert Wiener, forms the foundation of data-dependent linear least square error filters. Wiener filters play a central role in a wide range of applications such as linear prediction, echo cancellation, signal restoration, channel equalisation and system identification. The coefficients of a Wiener filter are calculated to minimise the average squared distance betwee...

We study path integration on a quantum computer that performs quantum summation. We assume that the measure of path integration is Gaussian, with the eigenvalues of its covariance operator of order j−k with k > 1. For the Wiener measure occurring in many applications we have k = 2. We want to compute an ε-approximation to path integrals whose integrands are at least Lipschitz. We prove: • Path ...

We study path integration on a quantum computer that performs quantum summa-tion. We assume that the measure of path integration is Gaussian, with the eigenvalues of its covariance operator of order j −k with k > 1. For the Wiener measure occurring in many applications we have k = 2. We want to compute an ε-approximation to path integrals whose integrands are at least Lipschitz. We prove: • Pat...