APPLICATION OF TWO-BIT DITHERED DISCRETE FOURIER BASIS FUNCTIONS IN ELECTRICITY MEASUREMENT

Paper defines an algorithm for generating two - bit dithered discrete Fourier basis functions (2BDDFBF) used in a Stochastic Digital Discret Fourier Transformation (SDDFT) processor. Based on the theoretical criterion of marginal precision, and norm and orthogonality, the orthonormality of DFT with 32 harmonics was confirmed by simulation and experimentally. The experiment was detailed and comprehensive, both for standardization and for both types of orthogonality. It was performed in 236800000 points in each of the three variants of orthonormalization. The matching of theoretical and experimental precision is very acceptable and it can be said with great reliability that the proposed algorithm for generating DDFBF is correct. 2BDDFBF play key role in electricity measurement what is emphasized in the paper. .

Reinforcement learning vs. rule-based adaptive traffic signal control: A Fourier basis linear function approximation for traffic signal control

Reinforcement learning is an efficient, widely used machine learning technique that performs well when the state and action spaces have a reasonable size. This is rarely the case regarding control-related problems, as for instance controlling traffic signals. Here, the state space can be very large. In order to deal with the curse of dimensionality, a rough discretization of such space can be employed. However, this is effective just up to a certain point. A way to mitigate this is to use techniques that generalize the state space such as function approximation. In this paper, a linear function approximation is used. Specifically, SARSA ( λ ) with Fourier basis features is implemented to control traffic signals in the agent-based transport simulation MATSim. The results are compared not only to trivial controllers such as fixed-time, but also to state-of-the-art rule-based adaptive methods. It is concluded that SARSA ( λ ) with Fourier basis features is able to outperform such methods, especially in scenarios with varying traffic demands or unexpected events.

The status of Chandler wobble

<p>The Chandler wobble (CW) and Annual wobble (AW) are the main components of the Earth’s Polar motion, which play an important role in our understanding of their excitations. The Fourier Basis Pursuit Band-Pass Filtering (FBPBPF) method, which can effectively suppress the edge effect, are applied to extract the CW and AW in Earth's polar motion during 1900-2016. Through analyze the variation of CW extracted by the FBPBPF method, we find that the amplitude of the CW has been diminishing since 1995. However, the amplitude of the CW had stopped decline in the last year, and start to increase at now.</p>