Generally, the dimension of the Kernel matrices of the kernel Support Vector Machines (SVM) increases as the number of training samples increases. However high dimensional features often bring redundant computation and decline of the generalization ability. Also kernel functions have several hyper-parameters which are fixed to the same values for all training samples. By considering the kernel matrix of Radial Basis Function (RBF) as a new high dimensional nonlinear feature for SVM, there is no limitation of which those hyper-parameters have to be a single fixed number. In this paper, we develop a nonlinear feature extraction method based on the selection of kernel seeds and the fine tuning of the kernel parameters, called randomized and dimension Reduced Radial Basis Features (RRBF).
This paper revisits the Markovian state vector of a Single Machine Infinite Bus (SMIB) system in non-linear filtering framework. In power system dynamics, the non-linear stochastic swing equation was the subject of investigations in the Fokker-Planck setting. The Fokker-Planck setting accounts for the process noise correction term and ignores the observation noise correction term to analyse stochastic systems. In contrast to the Fokker-Planck setting, this paper introduces the notion of the `Kushner-Stratonovich setting', which accounts for the process noise as well as observation noise correction terms in the conditional moment evolution equation. The Kushner-Stratonovich setting is the cornerstone formalism of non-linear filtering problems of stochastic control systems.
In this paper, we propose methods of detecting Doppler outliers which cause positioning errors at Doppler-aided GNSS (Global Navigation Satellite System) positioning, and correcting the errors. We apply the existing detection method based on the innovation process in Kalman filtering to Doppler outlier problems, and we propose a novel detection method based on the measurements by the difference between C/A code pseudoranges and Doppler shift range-rates. Both methods are based on chi-squared tests. We apply two correction methods which are Doppler bias exclusion,or the estimation for detected anomalies. The efficient detection of anomalous observables can be developed to RAIM (Receiver Autonomous Integrity Monitoring), and useful to achieve higher accuracy positioning for increasing satellite signals by multi-frequencies and multi-GNSSs. Doppler shift observables are utilized on a priority basis even in urban areas because of immunity to cycleslip and continuous availability, however unexpected Doppler outliers prone to cause positioning errors. The experimental results of positioning by using real receiver data show the feasibility of the proposed detection and correction methods.
In this work, an industrial Wireless Local Area Network (iWLAN) system used to control industrial robots (iRBs) in factory automation (FA) environments is addressed. For fast and safe communications, we first propose a synchronous multi-user round-robin transmission protocol. To reduce the overhead caused by the conventional multi-user downlink transmission technique, we then propose a low overhead Packet Division Multiple Access (PDMA) transmission technique. The numerical and simulation results indicate that our approaches increase speed of 100% and 300% throughput compared to the conventional industrial Point Coordination Function (iPCF) and Space Division Multiple Access (SDMA) approaches, respectively. Besides, our approaches also provide lower system error rate (SER) than conventional ones. In particular, the control duration per iRB in our iWLAN system is faster than 100μsec. Therefore, our proposed schemes can achieve fast and safe performance for FA communication systems.
In this paper, a simple dynamic model for an OTEC plant using Rankine cycle is constructed. The proposed dynamic model consists of steady state calculation of state quantity based on mass balance and energy balance, and transient calculation of the heat exchanger dynamics. The proposed dynamic model can express both the steady state and the transient state of the OTEC plant. Moreover,evaluation indexes of the OTEC plant are obtained. Accuracy of the proposed dynamic model is evaluated by comparing with experimental results of an OTEC pilot plant.