We discuss epistemological and methodological aspects of the Bayesian approach in astrophysics and cosmology. The introduction to the Bayesian framework is given for a further discussion concerning the Bayesian inference in physics. The interplay between the modern cosmology, Bayesian statistics, and philosophy of science is presented. We consider paradoxes of confi rmation, like Goodman’s paradox, appearing in the Bayesian theory of confirmation. As in Goodman’s paradox the Bayesian inference is susceptible to some epistemic limitations in the logic of induction. However, Goodman’s paradox applied to cosmological hypotheses seems to be resolved due to the evolutionary character of cosmology and the accumulation of new empirical evidence. We argue that the Bayesian framework is useful in the context of falsifiability of quantum cosmological models, as well as contemporary dark energy and dark matter problem.
An electric power steering system (EPS) is a new type of steering system developed after a mechanical hydraulic power system (MHPS) and electric-hydraulic power steering system (EHPS). In order to coordinate and solve the portability and sensitivity of the steering system optimally, taking an induction power steering system as the research object, the control algorithm of induction motor control under the EPS is studied in this paper. In order to eliminate the feed-forward performance degradation caused by the change of feed-forward parameters, an on-line identification algorithm of feed-forward parameters is proposed. It can improve the control performance of online identification among three feed-forward parameters in the T-axle motor, it improves on the robustness of feed-forward control performance, at the same time it also gives simulation and test results. This method can improve the control performance of the three feed-forward parameter online identification of the T-axis motor and improve the robustness of feed-forward control performance. At the same time, simulation and test results are given. The simulation results show that the algorithm can significantly improve the response speed and control accuracy of EPS system control.
The aim of this paper is to present a new approach to the problem of silicon integrated spiral inductors modeling. First, an overview of models and modeling techniques is presented. Based on 3D simulations and published measurement results, a list of physical phenomena to be taken into account in the model is created and based on it, the spiral inductor modeling by frequency sampling method is presented. To verify the proposed method a test circuit, containing 6 spiral inductors was designed and integrated in a silicon technology. The parameters of the spiral inductors from the test circuit were next measured and compared with simulations results. The comparison for one of those six spiral inductors is presented in the article.
This paper presents active inductor based VCO design for wireless applications based on analysis of active inductor models (Weng-Kuo Cascode active inductor & Liang Regular Cascode active inductor) with feedback resistor technique. Embedment of feedback resistor results in the increment of inductance as well as the quality factor whereas the values are email@example.comGHz (Liang) and firstname.lastname@example.orgGHz (Weng-Kuo). The Weng-Kuo active inductor based VCO shows a tuning frequency of 1.765GHz ~2.430GHz (31.7%), while consuming a power of 2.60 mW and phase noise of -84.15 dBc/Hz@1MHz offset. On the other hand, Liang active inductor based VCO shows a frequency range of 1.897GHz ~2.522GHz (28.28%), while consuming a power of 1.40 mW and phase noise of -80.79 dBc/Hz@1MHz offset. Comparing Figure-of-Merit (FoM), power consumption, output power and stability in performance, designed active inductor based VCOs outperform with the stateof- the-art.