Convergence Analysis of a Kind of Deterministic Discrete-Time PCA Algorithm

We proposed a generalized adaptive learning rate (GALR) PCA algorithm, which could be guaranteed that the algorithm’s convergence process would not be affected by the selection of the initial value. Using the deterministic discrete time (DDT) method, we gave the upper and lower bounds of the algorithm and proved the global convergence. Numerical experiments had also verified our theory, and the algorithm is effective for both online and offline data. We found that choosing different initial vectors will affect the convergence speed, and the initial vector could converge to the second or third eigenvectors by satisfying some exceptional conditions.

Research on Face Recognition Algorithm Based on Robust 2DPCA

As a new dimension reduction method, the two-dimensional principal component (2DPCA) can be well applied in face recognition, but it is susceptible to outliers. Therefore, this paper proposes a new 2DPCA algorithm based on angel-2DPCA. To reduce the reconstruction error and maximize the variance simultaneously, we choose F norm as the measure and propose the Fp-2DPCA algorithm. Considering that the image has two dimensions, we offer the Fp-2DPCA algorithm based on bilateral. Experiments show that, compared with other algorithms, the Fp-2DPCA algorithm has a better dimensionality reduction effect and better robustness to outliers.

Synergistic regulation of temperature resistance and thermal insulation performance of zirconia-based ceramic fibers

ZrO_(2) fiber is a promising high-temperature resistant and heat-insulating fiber material.However,the decrease in mechanical properties caused by grain growth at high temperatures seriously affects its application.How to achieve the synergy of its temperature resistance and the thermal insulation performance is still the focus of the current industry.In this work,we started with doping inequivalent elements and studied the phase composition,temperature resistance,and thermal insulation properties of Y_(2)O_(3)-ZrO_(2) ceramic fibers by adjusting the Y/Zr molar ratio.The results showed that Y_(2)O_(3) could enter the crystal lattice of ZrO_(2) and form a solid solution.With the increase in Y_(2)O_(3) content,the structure of fibers changed from a tetragonal phase to a cubic phase,and the configurational entropy of the system increased.The larger configuration entropy in the sample could produce a robust steric hindrance effect,inhibiting grain growth.After heat treatment at 1300℃,the grain size of Y_(2)Zr_(2)O_(7)(Y5Z5)fibers was only 61.8%that of Y_(0.1)Zr_(0.9)O_(1.95)(Y1Z9)fibers.The smaller grain size made the Y5Z5 fibers still have excellent flexibility and deformation recovery performance after heat treatment at 1300℃and could still return to the original state after 85%compression or folded in half.In addition,due to the larger configurational entropy,the mean free path of phonon scattering was shortened,thereby improving the thermal insulation performance of the fiber.In short,this work achieves the synergistic effect of temperature resistance and thermal insulation properties of zirconia-based fiber materials only through simple inequivalent element doping.

Modification of YSZ fiber composites by Al_(2)TiO_(5) fibers for high thermal shock resistance

Yttria-stabilized zirconia(YSZ)fiber composites are highly efficient thermal insulating materials;however,the poor thermal shock resistance limits their versatile applications.In the present study,YSZ fiber was mixed directly with Al_(2)TiO_(5)fiber,which had an extremely low thermal expansion coefficient,to prepare YSZ–Al_(2)TiO_(5)(ZAT)fiber composites by compression molding and heat treatment.The minimum thermal expansion coefficient of the prepared ZAT fiber composites was measured to be 7.74×10^(−6)K^(−1),which was 26%lower than that of the YSZ fiber composites(10.42×10^(−6)K^(−1)).It was shown that the prepared ZAT fiber composites maintain the integrity after undergoing 51 thermal shock cycles between 1100℃and room temperature.Whereas,YSZ fiber composites burst immediately after only one thermal shock cycle under the same condition.In addition,the ZAT fiber composites also exhibit considerable mechanical and thermal insulating performance.

Distributed Secondary Control Strategy Based on Q-learning and Pinning Control for Droop-controlled Microgrids

A distributed secondary control(DSC) strategy that combines Q-learning and pinning control is originally proposed to achieve a fully optimal DSC for droop-controlled microgrids(MGs). It takes advantages of cross-fusion of the two algorithms to realize the high efficiency and self-adaptive control in MGs. It has the following advantages. Firstly, it adopts the advantages of reinforcement learning in autonomous learning control and intelligent decision-making, driving the action value of pinning control for feedback adaptive correction. Secondly, only a small part of points selected as pinned points needs to be controlled and pre-learned, hence the actual control problem is transformed into a synchronous tracking problem and the installation number of controllers is further reduced.Thirdly, the pinning matrix can be modified to adapt to plugand-play operation under the distributed control architecture.Finally, the effectiveness and versatility of the proposed strategy are demonstrated with a typical droop-controlled MG model.