检索结果-内蒙古大学图书馆

self-adaptive match algorithm for transmitter-receiver in the middle and upper atmospheric lidar

OPTICS COMMUNICATIONS 2021年 488卷 126811-126811页

作者： Lin, Zhaoxiang Huang, Kunpeng Xiong, Wei Wu, Jinquan Cheng, Xuewu Yang, Guotao South Cent Univ Nationalities Wuhan 430074 Hubei Peoples R China Chinese Acad Sci Innovat Acad Precis Measurement Sci & Technol State Key Lab Magnet Resonance & Atom & Mol Phys Wuhan 430071 Hubei Peoples R China Chinese Acad Sci Natl Space Sci Ctr State Key Lab Space Weather Beijing 100190 Peoples R China

A precise matching is required between the emitted laser beam and Field-of-View (FOV) of the received telescope to ensure useful observation of middle and upper atmospheric lidar. Nowadays, manual matching is commonly used, but it is time-consuming and has poor stability. Automatic matching is still hard to meet the actual application requirement because it is challenging to balance accuracy and efficiency. Thus, in this paper, a self-adaptive matching algorithm is proposed. In this process, the correlation coefficient between the echo signal and the standard pattern is considered as the matching criterion. It adaptively updates the adjustment step according to the current position?s matching state and uses the correlation coefficient?s increasing gradient as the adjustment direction. The above matching process is iteratively conducted until meeting the convergence condition. The matching process is within 3?5min. These results suggest that the proposed automated matching algorithm can play an important role in unattended atmospheric lidars.

关键词： The middle and upper atmospheric lidar self-adaptive algorithm Transmitter?receiver Correlation coefficient Matching state

来源：评论

学校读者我要写书评

暂无评论

Inertial self-adaptive algorithms for solving non-smooth convex optimization problems

引用

NUMERICAL algorithmS 2025年第1期98卷 133-163页

作者： Chen, Xin Duan, Peichao Civil Aviat Univ China Coll Sci Tianjin 300300 Peoples R China

In this paper, for two different forms of non-smooth convex optimization problems, we investigate the self-adaptive algorithms with inertia acceleration. Firstly, we propose a self-adaptive proximal gradient algorithm with an inertial step. Under reasonable parameters, the strong convergence theorem is established. Secondly, we propose a self-adaptive split proximal algorithm with inertial acceleration. We prove that our algorithm converges strongly under suitable conditions. Notably, both inertial algorithms are extended to multi-step inertial version to accelerate the convergence of the algorithms. Finally, numerical results illustrate the performances of our algorithms.

关键词： Convex optimization self-adaptive algorithm Inertial acceleration Proximal gradient algorithm Split proximal algorithm

来源：评论

学校读者我要写书评

暂无评论

An efficient algorithm with double inertial steps for solving split common fixed point problems and an application to signal processing

引用

COMPUTATIONAL & APPLIED MATHEMATICS 2025年第1期44卷 1-17页

作者： Thong, Duong Viet Reich, Simeon Li, Xiao-Huan Tham, Pham Thi Hong Natl Econ Univ Fac Math Econ Hanoi Vietnam Technion Israel Inst Technol Dept Math IL-32000 Haifa Israel Shandong Univ Technol Sch Math & Stat Zibo 255000 Peoples R China

The split common fixed point problem is an optimization challenge that involves finding an element within one fixed point set such that when transformed by a bounded linear operator, it belongs to another fixed point set. This problem falls under the category of inverse problems in mathematics. We present a novel self-adaptive algorithm based on double inertial steps for solving the split common fixed point problem for demicontractive mappings. We also establish a weak convergence theorem for our method. Furthermore, we also present some numerical experiments illustrating the convergence behavior and the efficiency of our proposed algorithm.

关键词： Demicontractive operator Double inertial steps self-adaptive algorithm Signal processing Split common fixed point problem

来源：评论

学校读者我要写书评

暂无评论

NOVEL STRONG CONVERGENCE THEOREMS FOR THE SPLIT COMMON FIXED POINT PROBLEM OF DEMICONTRACTIVE OPERATORS WITH AN APPLICATION TO SIGNAL PROCESSING

引用

JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2025年第5期21卷 3258-3277页

作者： Viet, Thong duong Tien, Dung vu Ngan, Dang huy An, Nguyen thi Natl Econ Univ Fundamental Sci Fac Hanoi City Vietnam Vietnam Natl Univ Univ Sci Dept Math Hanoi Vietnam

The purpose of this paper is to introduce two self-adaptive algorithms using inertial effects and step sizes which do not depend on the norm of the bounded linear operator for solving the split common fixed point problem of demicontractive operators in real Hilbert spaces. Strong convergence results of the proposed algorithms are proved and analyzed under some control conditions. Furthermore, some numerical experiments illustrating the convergence behavior and the efficiency of our proposed algorithm are also given.

关键词： Split common fixed point demicontractive operator self-adaptive algorithm the signal processing

来源：评论

学校读者我要写书评

暂无评论

self-adaptive algorithms for the split problem of the demicontractive operators

引用

OPTIMIZATION 2018年第9期67卷 1309-1319页

作者： Yao, Yonghong Liou, Yeong-Cheng Postolache, Mihai Tianjin Polytech Univ Dept Math Tianjin Peoples R China Kaohsiung Med Univ Dept Healthcare Adm & Med Informat Kaohsiung Taiwan Kaohsiung Med Univ Res Ctr Nonlinear Anal & Optimizat Kaohsiung Taiwan Kaohsiung Med Univ Hosp Dept Med Res Kaohsiung Taiwan China Med Univ Dept Neural Comp Taichung Taiwan Univ Politehn Bucuresti Dept Math & Informat Bucharest Romania

self-adaptive algorithms are presented for solving the split common fixed point problem of demicontractive operators in Hilbert spaces. Weak and strong convergence theorems are given under some mild assumptions.

关键词： Split common fixed point demicontractive operator self-adaptive algorithm

来源：评论

学校读者我要写书评

暂无评论

self-adaptive algorithms for proximal split feasibility problems and strong convergence analysis

引用

FIXED POINT THEORY AND APPLICATIONS 2015年第1期2015卷 1-13页

作者： Yao, Yonghong Yao, Zhangsong Abdou, Afrah A. N. Cho, Yeol Je King Abdulaziz Univ Dept Math Jeddah 21589 Saudi Arabia Tianjin Polytech Univ Dept Math Tianjin 300387 Peoples R China Nanjing Xiaozhuang Univ Sch Informat Engn Nanjing 211171 Jiangsu Peoples R China Gyeongsang Natl Univ Dept Math Educ Chinju 660701 South Korea Gyeongsang Natl Univ RINS Chinju 660701 South Korea

The purpose of the paper is to study the proximal split feasibility problems. For solving the problems, we present new self-adaptive algorithms with the regularization technique. By using these algorithms, we give som... 详细信息

关键词： proximal split feasibility problem self-adaptive algorithm fixed point method strong convergence

来源：评论

学校读者我要写书评

暂无评论

A data-dependent energy reduction algorithm for SAR ADC using self-adaptive window

引用

MICROELECTRONICS JOURNAL 2020年 100卷 104754-104754页

作者： Lu, Hao-wei Yu, Xiao-Peng Lu, Zheng-Hao Yeo, Kiat-Seng Chen, Jer-Ming Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Zhejiang Peoples R China Soochow Univ Suzhou 215006 Peoples R China Singapore Univ Technol & Design 8 Somapah Rd Singapore 487372 Singapore

A new data-dependent energy reduction algorithm for successive approximation register (SAR) analog-to-digital convert (ADC) is presented in this paper. The proposed algorithm starts with a less significant bit (LSB) window with N-bit length, which is configurable depending on signal characteristics. By using less significant bit to more significant bit (L2M) successive extending (SE), the signal window is self-adaptive to cover the input signal within boundary. The proposed technique leads to less mean bit trials per sample, suggesting higher energy efficiency in many data-dependant ADC applications. Furthermore, this algorithm can be implemented based on conventional charge redistribution SAR ADC without any change in analog circuits. According to MATLAB simulation, the proposed technique is able to reduce mean bit trials effectively in biomedical signal detection applications. The simulation results show 37.9%, 32.3% and 18.2% less mean bit trials than using conventional SAR algorithm in processing electrocardiogram (ECG), electroencephalogram (EEG) and in electro-myography (EMG) signals respectively.

关键词： Successive approximation register(SAR) Analog-to-digital converter(ADC) Bit-trial saving Biomedical detection self-adaptive algorithm

来源：评论

学校读者我要写书评

暂无评论

A self-adaptive AP Selection algorithm Based on Multiobjective Optimization for Indoor WiFi Positioning

引用

IEEE INTERNET OF THINGS JOURNAL 2021年第3期8卷 1406-1416页

作者： Zhang, Wei Yu, Kegen Wang, Weixi Li, Xiaoming Shenzhen Univ Res Inst Smart Cities Shenzhen 518060 Peoples R China China Univ Min & Technol Sch Environm Sci & Spatial Informat Xuzhou 221116 Jiangsu Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Shenzhen 518060 Peoples R China

With the widely deployed wireless access points (APs) and the worldwide popularization of smartphones, WiFi-based indoor positioning has attracted great attention to both industry and academia. Locating and tracking objects within an indoor environment plays an important role in Internet of Things application and service. However, it is a challenging problem to achieve high accuracy using WiFi positioning technique due to the high instability in received signal strength from AP. Thus, it is desirable to select APs by considering both signal strength and connection quality. In this article, an AP selection algorithm based on multiobjective optimization is proposed to improve indoor WiFi positioning accuracy. The self-adaptive AP selection algorithm can be easily applied to various real scenarios and the performance of the new method is considerably better than classical algorithms. Learning algorithm is exploited to obtain the optimal solution for the self-adaptive AP selection algorithm. Experiments are conducted and the proposed algorithm is compared with classical algorithms. The experimental results demonstrate that the performance of the self-adaptive AP selection algorithm is at least a few decimeters better than classical algorithms in terms of RMSE of position estimation. Meanwhile, the new method is robust to the random generation of initial particles and normalizing factor as their effect on the positional accuracy is less than 1 decimeter.

关键词： Wireless fidelity Internet of Things Optimization Calibration IP networks Fingerprint recognition Fixtures Access point (AP) selection indoor WiFi positioning Internet of Things (IoT) multiobjective optimization self-adaptive algorithm

来源：评论

学校读者我要写书评

暂无评论

New self-adaptive algorithms and Inertial self-adaptive algorithms for the Split Variational Inclusion Problems in Hilbert Space

引用

NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION 2022年第9期43卷 1050-1068页

作者： Chuang, Chih-Sheng Hong, Chung-Chien Natl Chiayi Univ Dept Appl Math Chiayi Taiwan Natl Pingtung Univ Sci & Technol Dept Ind Management Pingtung Taiwan

In the field of convex optimization, numerous problems can be modeled as the split variational inclusion problem. In this paper, we want to give self-adaptive algorithms and inertial self-adaptive algorithms to study ... 详细信息

关键词： self-adaptive algorithm inertial algorithm inertial self-adaptive algorithm split feasibility problem split variational inclusion problem

来源：评论

学校读者我要写书评

暂无评论

Reckoning solution of split common fixed point problems by using inertial self-adaptive algorithms

引用

REVISTA DE LA REAL ACADEMIA DE CIENCIAS EXACTAS FISICAS Y NATURALES SERIE A-MATEMATICAS 2019年第4期113卷 3101-3114页

作者： Suparatulatorn, Raweerote Suantai, Suthep Phudolsitthiphat, Narawadee Chiang Mai Univ Fac Sci Dept Math Res Ctr Math & Appl Math Chiang Mai 50200 Thailand

In this paper, we construct a novel algorithm for the split common fixed point problem for two demicontractive operators in Hilbert spaces. By using inertial self-adaptive algorithms, we obtain strong convergence results for finding a solution of the split common fixed point problems. Applications to solving the split minimization problem and the split feasibility problem are included. Our results extend and generalizemany previously known results in this research area. Moreover, numerical experiments are supplied to demonstrate the convergence behavior and efficiency of the proposed algorithm.

关键词： Split common fixed point problem Demicontractive operator self-adaptive algorithm Inertial algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：