The evaluation of the Fisher information matrix for the probability density of trajectories generated by the over-damped Langevin dynamics at equilibrium is presented. The framework we developed is general and applicable to any arbitrary potential of mean force where the parameter set is now the full space dependent function. Leveraging an innovative Hermitian form of the corresponding Fokker-P...

An optimal experimental design for yield coefficients estimation in an unstructured growth model of fed-batch fermentation of E. coli is presented. The feed profile is designed by optimisation of a scalar function based on the Fischer Information Matrix. A genetic algorithm is proposed as the optimisation method due to its efficiency and independence on the initial values. Copyright 2004 IFAC K...

Residuals in fault detection and diagnosis are usually designed with directional or structured properties to facilitate fault isolation. With directional residuals, best isolation is achieved if the residual directions are orthogonal. In the presence of noise, the residuals are subjected to statistical testing. Testing conditions are ideal if the Fisher information matrix of the residuals is di...

Let Dv,b,k denote the family of all connected block designs with v treatments and b blocks of size k. Let d ∈ Dv,b,k. The replication of a treatment is the number of times it appears in the blocks of d. The matrix C(d) = R(d) − 1 kN(d)N(d) > is called the information matrix of d where N(d) is the incidence matrix of d and R(d) is a diagonal matrix of the replications. Since d is connected, C(d)...

Abstract This paper is concerned with the analysis of optimization procedures for optimal experiment design locally affine Takagi-Sugeno (TS) fuzzy models based on Fisher Information Matrix (FIM). The FIM used to estimate covariance matrix a parameter estimate. It depends model parameters as well regression variables. Due dependency good initial are required. Since matrix, scalar measure optimi...

An analogue of the classical link between the relative entropy and Fisher information entropy is presented in the context of free probability theory. Several generalizations of the relative entropy in terms of density matrices are also discussed.

Csisz ar's f -divergence of two probability distributions was extended to the quantum case by the author in 1985. In the quantum setting positive semide nite matrices are in the place of probability distributions and the quantum generalization is called quasi-entropy which is related to some other important concepts as covariance, quadratic costs, Fisher information, Cram er-Rao inequality and ...