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

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

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

Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value =0.02, F=4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value =0.04, F=3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation