Self-control is a complex and multifaceted construct that can be regarded as an individual trait that follows its own developmental trajectory. In the presented study we used NAS-50 for the assessment of self-control in adolescents and young adults. Since the questionnaire has not been used before in underage participants we tested its reliability in adolescent and adult samples. We also investigated possible age and gender differences in self-control abilities as well as relations between NAS-50 and behavioral measures of cognitive control and impulsivity. Although the sample was quite small, the reliability of the questionnaire was similar to the results achieved by its authors. According to the predictions in the literature we did not find relations between NAS-50 and behavioral measures of cognitive control and impulsivity. We also did not observe significant age differences in the assessment of self-control abilities. The theoretical relevance of our results is discussed.
In recent years, with the rapid development of digital components, digital electronic computers, especially microprocessors, digital controllers have replaced analog controllers on many occasions. The application of digital controller makes the performance analysis of impulsive system more and more important. This paper considers global exponential stability (GES) of impulsive delayed nonlinear hybrid differential systems (IDNHDS).Through the application of the Lyapunov method and the Razumikhin technique, a series of uncomplicated and useful guiding principles have been obtained. The results of a numerical simulation are presented to demonstrate that the method is correct and effective.
To overcome the detrimental influence of α impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.