New trajectories of the Hungarian regional development: balanced and rush growth of territorial capital

The basic assumption of the paper is that numerous similarities exist between the patterns of economic growth and territorial capital growth. The rush economic growth and rush growth of territorial capital are compared empirically at Hungarian micro-regional level from 2004 until 2010. After normalizing the dataset, a very novel spatial econometric method is applied, called a penalty for bottleneck. The results show that the constant rush growth of territorial capital is as harmful as economic recession. On the other hand, the decrease of infrastructural and social capital caused the rush growth of territorial capital in this period. Moreover, the key findings of two case studies suggest that the balanced growth of territorial capital will be created by the falling social inequalities and increasing infrastructural capita

Analysing Model Validation Methods for Errors-in-Variables Estimation

When identifying a dynamic system the model has to be validated as well. For an errors-in-variables situation where both input and output measurements are noise corrupted, this is a nontrivial task, seldom treated in the literature. Some different approaches for model validation are introduced and evaluated by theoretical analysis as well as application to simulated data

Analysing Model Validation Methods for Errors-in-Variables Estimation

When identifying a dynamic system the model has to be validated as well. For an errors-in-variables situation where both input and output measurements are noise corrupted, this is a nontrivial task, seldom treated in the literature. Some different approaches for model validation are introduced and evaluated by theoretical analysis as well as application to simulated data

Repeated poles in feedback over a class of signal-to-noise ratio constrained channels

In the present paper we obtain a closed form expression for the squared H₂⊥ norm of a partial fraction expansion with repeated unstable poles. We also obtain a closed form expression for the squared H₂ norm of a partial fraction expansion with repeated stable poles. As an application we use the H₂⊥ result to extend the closed form solution of the discrete-time linear time invariant (LTI) signal-to-noise ratio (SNR) constrained problem to the case of repeated unstable poles in the plant model

Recursive online IV method for identification of continuous-time slowly time-varying models in closed loop

Model estimation of industrial processes is often done in closed loop due, for instance, to production constraints or safety reasons. On the other hand, many processes are time-varying because of aging effects or changes in the environmental conditions. In this study, a recursive estimation algorithm for linear, continuous-time, slowly time-varying systems operating in closed loop, is developed. The proposed method consists in coupling linear filter approaches to handle the time-derivative, with closed-loop instrumental variable (IV) techniques to deal with measurement noise. Simulations show the advantages of using this IV-based method

Identification of continuous-time state-space models from non-uniform fast-sampled data

In this study, we apply the expectation-maximisation (EM) algorithm to identify continuous-time state-space models from non-uniformly fast-sampled data. The sampling intervals are assumed to be small and uniformly bounded. The authors use a parameterisation of the sampled-data model in incremental form in order to modify the standard formulation of the EM algorithm for discrete-time models. The parameters of the incremental model converge to the parameter of the continuous-time system description as the sampling period goes to zero. The benefits of the proposed algorithm are successfully demonstrated via simulation studies