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The purpose of this paper is to develop a methodology for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

The authors perform drive-response concept and time-delay feedback control techniques to investigate a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations. New sufficient criterion is established without strict conditions imposed on the activation functions.

It turns out that the approach results in new sufficient criterion easy to be verified but without the usual assumption of the differentiability and monotonicity of the activation functions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in removing the usual assumption of the differentiability and monotonicity of the activation functions, and the use of the Lyapunov functional method, Jensen integral inequality, a novel Gu’s lemma, reciprocal convex and linear convex combination technique for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

The purpose of this paper is to develop a methodology for the stochastically asymptotic stability of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay in mean square.

The authors perform Briat Lemma, multiple integral approach and linear convex combination technique to investigate a class of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay. New sufficient criterion is established by linear matrix inequalities conditions.

It turns out that the obtained methods are easy to be verified and result in less conservative conditions than the existing literature. Two examples show the effectiveness of the proposed results.

The novelty of the proposed approach lies in establishing a new Wirtinger-based integral inequality and the use of the Lyapunov functional method, Briat Lemma, multiple integral approach and linear convex combination technique for stochastically asymptotic stability of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay in mean square.

This study aims to analyze whether tax compliance is the basis for the short-run dynamics of the development of welfare and happiness. The strengthening of tax compliance of corporates and citizens is not only important to achieve the goals assumed by fiscal policy but also is part of the values that can generate a higher level of welfare and happiness in Europe.

This study uses a dynamic factor model to offer new indexes that allow to monitor tax compliance, public spending and happiness trajectories and to evaluate their short-run relationships. Next, an analysis of the cyclical characteristics in terms of duration, amplitude and intensity is provided using the Harding and Pagan method (2002).

The empirical findings show that the European countries were able to reinforce tax compliance during the expansionary periods of the economy, and this has made it possible to increase public spending, and indirectly, happiness. Otherwise, this paper shows that the contractions of public resources during the global crisis, such as the case in the COVID-19, reduced the possibilities of well-being in Europe and made it more difficult to increase public spending and happiness.

This study tries to analyze the transmission channels and relationships of three very complex variables: tax compliance, public spending and happiness. Incorporating these three variables into this research, with a short-run perspective, the authors have opened a new line of research that enriched the previous analysis. Therefore, the authors’ results should be considered the first step, that this study is going to continue to unravel the complexity of these relationships.

The design of policies aimed at improving individual, corporate and the well-being of nations needs them to incorporate elements of tax compliance as an objective that has economic and social implications. Individuals and corporates contribute to a fairer and more equitable society through compliance with tax obligations.

To the best of the authors’ knowledge, this is the first paper that offers evidence on the short-run dynamics of tax revenue, public spending and happiness for a better understanding of their relationships and behavior during the different periods of the economy.

The purpose of this paper is to provide the results of investigation of multi‐moment statistical characteristics of chaos and apply them to improve the accuracy of nonlinear algorithms for chaos filtering for real‐time applications.

The approach to find multi‐moment statistical properties of chaos‐multi‐moment cumulant (covariance) functions of higher order is a generalization of the previously proposed (by the authors) “degenerated cumulant equations” method. Those multi‐moment cumulants functions are applied in the generalization of the Stratonovich‐Kushner equations (SKE) for the optimum algorithm of nonlinear filtering of chaos as well as for synthesis of the quasi‐optimum algorithms.

Results are presented to investigate the multi‐moment statistical properties of chaos and formulate the theoretical background for synthesis of multi‐moment optimum and quasi‐optimum algorithms for nonlinear filtering of chaos with the improved accuracy in the presence of additive white noise.

The paper presents new theoretical results of the statistical description of chaos, previously partially reported only from experimental studies. A novel approach for chaos filtering is also presented. The proposed approach is dedicated to further improvement of the filtering accuracy for the case of low (less than one) SNR scenarios and is important for implementation in real‐time processing. As an important practical example, the new modified EKF algorithm is proposed with the rather opportunistic characteristics of the filtering fidelity together with algorithm complexity – practically the same as the “classic” one‐moment EKF algorithm.

This paper is concerned with non-fragile robust H_∞ control problems for nonlinear networked control systems (NCSs) with time-varying delay and unknown actuator failures. The paper aims to discuss these issues.

The system parameters are allowed to have time-varying uncertainties and the actuator faults are unknown but whose upper and lower bounds are known. By using some lemmas, uncertainties can be replaces with the known values. By taking the exogenous disturbance and network transmission delay into consideration, a delay nonlinear system model is constructed.

Based on Lyapunov stability theory, linear matrix inequalities (LMIs) and free weighting matrix methods, the sufficient conditions for the existence of the non-fragile robust H_∞ controller gain are derived and which can obtained by solving the LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed methods.

The introduced approach is interesting for NCSs with time-varying delay and unknown actuator failures.

The human mind possesses the unique capability of “mapping” the external (as well as part of the organism's internal) world i.e. it “compresses” long and complex strings of impinging environmental stimuli (“observations”) and then uses these “minimal length algorithms” in order to simulate physical phenomena‐thereby revealing the “laws of nature”. In this paper we theorize that this process of “Self”‐organization and category formation is implimented via a set of coexisting (strange) attractors in the cognizant apparatus each one of which attracts (and therefore compresses) whole subsets of “initial conditions” the sum‐total of which constitute the set of external stimuli. This set of the initial conditions forms the “Basin” of the attractors and the processes of partition and category formation in the mind involves the topology of the separatrixes amongst the individual subsets of the Basin. We examine in particular how the information processing is mediated by the thalamocortical pacemaker of the brain and, therefore, what might be the role of E.E.G (which is measurable on a routine basis) in Cognition.

This paper aims to propose that a Neave-Worthington Match Test for Ordered Alternatives is a simple, non-parametric test that can be used to consider Gibrat’s law. Whether the law, that states that the proportional rate of growth is independent of absolute size, is supported by regional house price growth rates is considered. The Match Test is further used to test the applicability of beta-convergence and dual economy models to a house price context.

The Match Test relates an actual rank order with an expected one. Gibrat’s law implies house price growth rates are independent of the absolute price levels. Beta-convergence posits that growth rates are inversely related to the initial price level. With a divergent system, there is a direct relationship between size-order and growth rates. As such, the Match Test is used to test alternative models of size-growth relationship.

Rather than convergence, there is a tendency to diverge across the UK, but not in Eire. That said, the size of growth shocks is related to price level on the upswing of a price cycle, but not in the down. Assigning the high-priced regions of the two islands into core and the rest into a periphery, total matching is dominated by the capital cities’ growth. The sigma-convergence observed in British house prices is likely to be associated with slower beta-divergence, not a convergent system. The law of Gibrat is not found to apply in a regional house price context.

This work only covers two countries and nineteen regions. Gibrat’s law in regional house prices may be better examined using a multi-country analysis.

As the law of Gibrat is not found to apply in a regional house price context and core-regions appearing to dislocated, this has interesting implications for growth trend analysis and the claim of cointegration, which should be explored further. In particular, the level-growth relationship in the cyclical price upswing points to a ratcheting of differentials between high and low house price regions. The common trends in the long run may result from corrective periodic crashes. Not an ideal mechanism for policymakers.

To the best of the author’s knowledge, this paper makes a novel use of the Neave-Worthington test in the realm of regional convergence-divergence and in the first consideration of the law of Gibrat in a house price context across two countries.