In this paper safety culture and worker’s are considered, all together, as a complex system and statistically represented in the form of correlation network among their characteristics. We show that the current practice, based on a minimal spanning tree (MST), to filter the information contained in the network is not robust. A robust filter based on the forest of all possible MSTs is then propo...

We present a matrix theoretic derivation of the Kalman filter—motivated by the statistical technique of minimum variance estimation—in order to make its theoretical underpinnings accessible to a broader audience. Standard derivations of the filter utilize probabilistic arguments that are less familiar to the matrix analyst and computational mathematician.

This paper is concerned with the problem of H∞ fuzzy filtering of nonlinear systems with intermittent measurements. The nonlinear plant is represented by a Takagi–Sugeno (T–S) fuzzy model. The measurements transmission from the plant to the filter is assumed to be imperfect, and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the phenomenon of the ...

This paper presents new non-fragile H∞ filter design methods for linear discrete-time systems. The filter to be designed is assumed to be with additive gain variations, which reflect the FWL effects in filter digital implementations. A notion of structured vertex separator is proposed to approach the problem, and exploited to develop sufficient conditions for the non-fragile H∞ filter design in...

This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

In this paper we propose a new state estimation algorithm called the extended information filter on Lie groups. The proposed filter is inspired by the extended Kalman filter on Lie groups and exhibits the advantages of the information filter with regard to multisensor update and decentralization, while keeping the accuracy of stochastic inference on Lie groups. We present the theoretical develo...

The LDI matrix is introduced in its full and shortened forms. As an analogy of the Pascal matrix for the bilinear transform, the LDI matrix serves to transform the coefficients of the transfer functions of continuousand discrete-time linear circuits which are connected by the LDI (Lossless Discrete Integration) transform. The basic properties of the LDI matrix are presented and a procedure of i...