Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Learning Sheared EPI Structure for Light Field Reconstruction

Abstract: Research in light field reconstruction focuses on synthesizing novel views with the assistance of depth information. In this paper, we present a learning-based light field reconstruction approach by fusing a set of sheared epipolar plane images (EPIs). We start by showing that a patch in a sheared EPI will exhibit a clear structure when the sheared value equals the depth of that patch. By taking advantage of this pattern, a convolutional neural network (CNN) is then trained to evaluate the sheared EPIs, and output a reference score for fusing the sheared EPIs. The proposed CNN is elaborately designed to learn the similarity degree between the input sheared EPI and the ground truth EPI. Therefore, no depth information is required for network training and reasoning. We demonstrate the high performance of the proposed method through evaluations on synthetic scenes, real-world scenes, and challenging microscope light fields. We also show a further application of our proposed network for depth inference.

Performance-Based Adaptive Fuzzy Tracking Control for Networked Industrial Processes

Abstract: In this paper, the performance-based control design problem for double-layer networked industrial processes is investigated. At the device layer, the prescribed performance functions are first given to describe the output tracking performance, and then by using backstepping technique, new adaptive fuzzy controllers are designed to guarantee the tracking performance under the effects of input dead-zone and the constraint of prescribed tracking performance functions. At operation layer, by considering the stochastic disturbance, actual index value, target index value, and index prediction simultaneously, an adaptive inverse optimal controller in discrete-time form is designed to optimize the overall performance and stabilize the overall nonlinear system. Finally, a simulation example of continuous stirred tank reactor system is presented to show the effectiveness of the proposed control method.