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Improving the reconstruction efficiency of sparsity adaptive matching pursuit based on the Wilkinsonmatrix None

Rasha SHOITAN, Zaki NOSSAIR, I. I. IBRAHIM, Ahmed TOBAL

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4, Pages 503-512 doi: 10.1631/FITEE.1601588

Abstract: Sparsity adaptive matching pursuit (SAMP) is a greedy reconstruction algorithm for compressive sensing

Keywords： Block compressive sensing Sparsity adaptive matching pursuit Greedy algorithm Wilkinson matrix

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Combinational Evaluation Method Based on Projection Pursuit Algorithm

Wang Shuo, Yang Shanlin, Hu Xiaoxuan

Strategic Study of CAE 2008, Volume 10, Issue 8, Pages 60-64

Abstract: Aim at this problem, a method uses projection pursuit algorithm to establish combinational evaluationThe example shows the combinational evaluation method based on projection pursuit algorithm is scientific

Keywords： combinational evaluation projection pursuit algorithm real code daccelerating enetic algorithm identification

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A survey of the pursuit–evasion problem in swarm intelligence Review

Zhenxin MU, Jie PAN, Ziye ZHOU, Junzhi YU, Lu CAO,junzhi.yu@ia.ac.cn,yujunzhi@pku.edu.cn,caolu_space2015@163.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8, Pages 1093-1116 doi: 10.1631/FITEE.2200590

Abstract: We summarize predator pursuit behavior and prey behavior as predator–prey behavior.

Keywords： Swarm behavior Pursuit– evasion Artificial systems Biological model Collective motion

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Distribution system state estimation: an overview of recent developments Review Article

Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, Jian SUN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 1, Pages 4-17 doi: 10.1631/FITEE.1800590

Abstract:

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

Keywords： State estimation Cramér-Rao bound Feasible point pursuit Semidefinite relaxation Proximal linear algorithm

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Academician Du Xiangwan: Pursuit of Excellence (2022-3-28）

28 Mar 2022

Keywords：工程前沿

Optical Molecular Imaging Frontiers in Oncology: The Pursuit of Accuracy and Sensitivity Review

Kun Wang,Chongwei Chi,Zhenhua Hu,Muhan Liu,Hui Hui,Wenting Shang,Dong Peng,Shuang Zhang,Jinzuo Ye,Haixiao Liu,Jie Tian

Engineering 2015, Volume 1, Issue 3, Pages 309-323 doi: 10.15302/J-ENG-2015082

Abstract:

Cutting-edge technologies in optical molecular imaging have ushered in new frontiers in cancer research, clinical translation, and medical practice, as evidenced by recent advances in optical multimodality imaging, Cerenkov luminescence imaging (CLI), and optical image-guided surgeries. New abilities allow in vivo cancer imaging with sensitivity and accuracy that are unprecedented in conventional imaging approaches. The visualization of cellular and molecular behaviors and events within tumors in living subjects is improving our deeper understanding of tumors at a systems level. These advances are being rapidly used to acquire tumor-to-tumor molecular heterogeneity, both dynamically and quantitatively, as well as to achieve more effective therapeutic interventions with the assistance of real-time imaging. In the era of molecular imaging, optical technologies hold great promise to facilitate the development of highly sensitive cancer diagnoses as well as personalized patient treatment—one of the ultimate goals of precision medicine.

Keywords： optical molecular imaging multimodality molecular imaging optical multimodality tomography Cerenkov luminescence imaging intraoperative image-guided surgery