In this study, an observer for estimating the state and unknown inputs is proposed monitoring anaerobic digestion processes. This estimator based on a dynamic model considering acidogenesis methanogenesis, consists of three sub-observers: (a) gramian-based fixed-time convergent inlet chemical oxygen demand (COD) acidogenic bacteria population, (b) asymptotic methanogenic (c) super-twisting syst...

Homotopy Perturbation Method is an effective method to find a solution of a nonlinear differential equation, subjected to a set of boundary condition. In this method a nonlinear and complex differential equation is transformed to series of linear and nonlinear and almost simpler differential equations. These set of equations are then solved secularly. Finally a linear combination of the solutio...

We introduce a class of Multigrid based temporal difference algorithms for reinforcement learning with linear function approximation. Multigrid methods are commonly used to accelerate convergence of iterative numerical computation algorithms. The proposed Multigrid-enhanced TD(λ) algorithms allows to accelerate the convergence of the basic TD(λ) algorithm while keeping essentially the same per-...

This paper presents results from a project on phonetic convergence in German spontaneous speech. We used linear mixed models to examine 22 unimodal and 24 multimodal dialogs for articulation rate. We show that speakers’ local articulation rates are influenced by the preceding rates of their interlocutors, and that the direction of this influence (i.e., divergence or convergence) depends on soci...

Performance of the linear models, widely used within the framework of adaptive line enhancement (ALE), deteriorates dramatically in the presence of non-Gaussian noises. On the other hand, adaptive implementation of nonlinear models, e.g. the Volterra filters, suffers from the severe problems of large number of parameters and slow convergence. Nonetheless, kernel methods are emerging solutions t...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

This research presents a novel design approach to achieve an optimal structure established upon multiple objective functions by simultaneous utilization of the Enhanced Time Evolutionary Optimization method and Fuzzy Logic (FLETEO). For this purpose, at first, modeling of the structure design problem in this space is performed using fuzzy logic concepts. Thus, a new problem creates with functio...