Fixed Structure Complexity

2008 ◽  
pp. 30-42 ◽  
Author(s):  
Yonatan Aumann ◽  
Yair Dombb
Keyword(s):  
Structure Complexity ◽  
Fixed Structure

Generalized Fixed-Structure Optimality Conditions for H2 Optimal Control

1993 ◽  
Author(s):  
Emmanuel G. Collins ◽  
Wassim M. Haddad ◽  
Sidney S. Ying
Keyword(s):  
Optimal Control ◽  
Optimality Conditions ◽  
Fixed Structure

scholarly journals Distinguishing Planting Structures of Different Complexity from UAV Multispectral Images

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1994
Author(s):  
Qian Ma ◽  
Wenting Han ◽  
Shenjin Huang ◽  
Shide Dong ◽  
Guang Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Confusion Matrix ◽  
Object Oriented ◽  
Low Complexity ◽  
Classification Model ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Multispectral Images ◽  
High Complexity ◽  
Structure Complexity

This study explores the classification potential of a multispectral classification model for farmland with planting structures of different complexity. Unmanned aerial vehicle (UAV) remote sensing technology is used to obtain multispectral images of three study areas with low-, medium-, and high-complexity planting structures, containing three, five, and eight types of crops, respectively. The feature subsets of three study areas are selected by recursive feature elimination (RFE). Object-oriented random forest (OB-RF) and object-oriented support vector machine (OB-SVM) classification models are established for the three study areas. After training the models with the feature subsets, the classification results are evaluated using a confusion matrix. The OB-RF and OB-SVM models’ classification accuracies are 97.09% and 99.13%, respectively, for the low-complexity planting structure. The equivalent values are 92.61% and 99.08% for the medium-complexity planting structure and 88.99% and 97.21% for the high-complexity planting structure. For farmland with fragmentary plots and a high-complexity planting structure, as the planting structure complexity changed from low to high, both models’ overall accuracy levels decreased. The overall accuracy of the OB-RF model decreased by 8.1%, and that of the OB-SVM model only decreased by 1.92%. OB-SVM achieves an overall classification accuracy of 97.21%, and a single-crop extraction accuracy of at least 85.65%. Therefore, UAV multispectral remote sensing can be used for classification applications in highly complex planting structures.

scholarly journals Reinforcement Learning based Design of Linear Fixed Structure Controllers

2020 ◽  
Vol 53 (2) ◽  
pp. 230-235
Author(s):  
Nathan P. Lawrence ◽  
Gregory E. Stewart ◽  
Philip D. Loewen ◽  
Michael G. Forbes ◽  
Johan U. Backstrom ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Fixed Structure

Extending Parallel Computing with Constraint of Fixed Structure by Adjusting Graph

2015 ◽  
Vol 62 (4) ◽  
pp. 453-467 ◽  
Author(s):  
Huanliang Xiong ◽  
Guosun Zeng ◽  
Chunling Ding ◽  
Canghai Wu ◽  
Wei Wang
Keyword(s):  
Parallel Computing ◽  
Fixed Structure

Research on RS-WNN Integrated Modeling

2011 ◽  
Vol 105-107 ◽  
pp. 2169-2173
Author(s):  
Zong Chang Xu ◽  
Xue Qin Tang ◽  
Shu Feng Huang
Keyword(s):  
Neural Network ◽  
Rough Set ◽  
Attribute Reduction ◽  
Wavelet Neural Network ◽  
Integrated Modeling ◽  
Generalization Ability ◽  
Decision Attributes ◽  
Optimum Decision ◽  
Structure Complexity ◽  
Modeling Algorithm

Wavelet Neural Network (WNN) integration modeling based on Rough Set (RS) is studied. An integration modeling algorithm named RS-WNN, which first introduces a heuristic attribute reduction recursion algorithm to determine the optimum decision attributes and then conducts WNN modeling, is proposed. This method is adopted to more effectively eliminate the redundant attributes, lower the structure complexity of WNN, which reduce the time of training and improve the generalization ability of WNN. The result of the experiment shows this method is superior and efficient.

Simulation Optimization of Backrest Mechanism of Separable Bed Chair System

2021 ◽  
Vol 15 ◽  
pp. 1114-1123
Author(s):  
Meng Ning ◽  
Zhi Wu ◽  
Lianjie Chen ◽  
Fan Zhang ◽  
Huitao Chen
Keyword(s):  
Sudden Change ◽  
Optimal Solution ◽  
Simulation Software ◽  
Final Solution ◽  
Integration System ◽  
Modeling And Analysis ◽  
Movement Characteristics ◽  
Fixed Structure ◽  
The Relationship ◽  
Research And Design

Research and design an intelligent bed and chair integration system for assisting inconvenient mobility and aging population. The system consists of a removable detached wheelchair and a c-shaped bed with a fixed structure. The user can switch freely between the mobile wheelchair and the bed to meet the user's requirements of free movement and repositioning.Through the simulation software to analyze the movement characteristics of the bed backboard, the angle of the take-off and landing of the backboard and the sudden change of the take-off and abrupt angular velocity will cause the user to have dizziness and discomfort. In the case of determining the speed of the driving push rod, the relationship between mechanism parameters and installation parameters is the key to affect the lifting rate of the rear plate. Modeling and analysis of each mechanism is performed to determine the relationship between the mechanism parameters and the take-off and landing speed of the backplane. After optimizing the mechanism, the simulation is compared again to obtain the optimal solution. Finally, the optimal solution parameter is the final solution to improve the overall comfort of the nursing bed.

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