检索结果-内蒙古大学图书馆

MIMO-Based Chirp Spread Spectrum with Permutation Matrix Modulation

IEEE Internet of Things Journal 2025年

作者： Maleki, Alireza Bedeer, Ebrahim Barton, Robert University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonS7N5A9 Canada Cisco Systems Inc United States

In this paper, we propose a multiple-input multiple-output (MIMO) configuration for chirp spread spectrum (CSS) modulation integrated with the permutation matrix modulation (PMM) scheme, namely, MIMO-CSS-PMM. The proposed MIMO-CSS-PMM simultaneously improves the spectral efficiency (SE) and error performance of the CSS-based transmission scheme. For the detection, we formulate the optimum maximum likelihood (ML) detector that turns out to be of high computational complexity. We propose two low complexity semi-coherent detection schemes, i.e., scheme I and scheme II, in which we average over the fast Fourier transform (FFT) output of the dechirped signal of each receiver antenna. Then, in scheme I, we reduce the ML search set by selecting the number of largest averaged signal values corresponding to the number of transmitter antennas. To further reduce the complexity of scheme I, in scheme II, we define and derive a probability of detection using concepts from order statistics and find a threshold value maximizing this probability of detection. We select the number of the largest averaged signal greater than or equal to the obtained threshold to eliminate the unnecessary cases from the search set of scheme I. With the help of computer simulations, we evaluate the proposed detectors in terms of bit error rates (BER). © 2014 IEEE.

关键词： Chirp modulation

来源：评论

学校读者我要写书评

暂无评论

Photon-magnon coupling using gain-assisted spoof-localized surface plasmons

引用

Optics Express 2025年第8期33卷 16809-16819页

作者： Xiong, Yuzan Christy, Andrew Li, Yi Sun, Rui Comstock, Andrew H. Wu, Junming Lopez, Rene Lei, Sidong Sun, Dali Cahoon, James F. Zhang, Xufeng Yang, Binbin Zhang, Wei Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Chemistry University of North Carolina at Chapel Hill Chapel HillNC27599 United States Materials Science Division Argonne National Laboratory ArgonneIL60439 United States North Carolina State University RaleighNC27695 United States NanoScience Technology Center University of Central Florida OrlandoFL32826 United States Department of Material Science and Engineering University of Central Florida OrlandoFL32816 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Physics Northeastern University BostonMA02115 United States Department of Electrical and Computer Engineering North Carolina A&T State University GreensboroNC27411 United States

Improving the photon-magnon coupling strength can be done by tuning the structure of microwave resonators to better interact with the magnon counterpart. Planar resonators accommodating unconventional photon modes beyond the half- and quarter-wavelength designs have been explored due to their optimized mode profiles and potentials for on-chip integration. Here, we designed and fabricated an actively controlled ring resonator supporting the spoof localized surface plasmons (LSPs), and implemented it in the investigation of photon-magnon coupling for hybrid magnonic applications. We demonstrated gain-assisted photon-magnon coupling with the YIG magnon mode under several different sample geometries. The achieved coupling amplification largely benefits from the high quality factor (Q-factor) due to the additional gain provided by a semiconductor amplifier, which effectively increases the Q-factor from a nearly null state (passive resonance) to more than 1000 for a quadrupole LSP mode. Our results suggest an additional control knob for manipulating photon-magnon coupled systems exploiting external controls of gain and loss. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Q factor measurement

来源：评论

学校读者我要写书评

暂无评论

Priority-Based Blockchain Packing for Dependent Industrial IoT Transactions

引用

IEEE Transactions on Network and Service Management 2025年第2期22卷 1618-1628页

作者： Lin, Chaofeng Tang, Jinchuan Dang, Shuping Chen, Gaojie Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China University of Bristol Department of Electrical and Electronic Engineering BristolBS8 1UB United Kingdom Guangdong Shenzhen518107 China 5GIC and 6GIC The University of Surrey United Kingdom

Blockchain plays a key role in establishing secure and decentralized Industrial Internet of Things (IIoT) systems. Currently, the dependent transactions generated by IIoT devices require a packing process to select a set of non-conflicted transactions, which results in significant delay and deviation of the transaction response time. In this paper, we propose a novel transaction packing algorithm named Priority-Pack to address the above issue. Firstly, we use directed acyclic graphs to model the dependent transactions in IIoT systems to establish the mathematical relationships between transaction priority and waiting time as well as dependencies. Secondly, we propose an algorithm to specify a higher priority to a transaction with longer waiting time without violating transaction dependencies. It eliminates the time required to traverse the subsets of transactions in other algorithms. Thirdly, to further reduce the response delay for transactions with the same priority level, we choose to first pack transactions with smaller sizes. We prove that this selection can achieve the lowest average response time. Finally, simulations are conducted to benchmark the Priority-Pack against the state-of-the-art algorithms including Fair-Pack and Random-Pack. The results demonstrate that Priority-Pack outperforms the others in terms of average response time and deviations. © 2004-2012 IEEE.

关键词： Industrial internet of things (IIoT)

来源：评论

学校读者我要写书评

暂无评论

Equilibrium-Independent Control of Continuous-Time Nonlinear systems Via the LPV Framework

引用

IEEE Transactions on Automatic Control 2025年

作者： Koelewijn, Patrick J. W. Weiland, Siep Toth, Roland Eindhoven University of Technology Control Systems Group Department of Electrical Engineering Eindhoven Netherlands Institute for Computer Science and Control Systems and Control Laboratory Budapest Hungary

In this paper, we consider the analysis and control of continuous-time nonlinear systems to ensure universal shifted stability and performance, i.e., stability and performance w.r.t. each forced equilibrium point of the system. This "equilibrium-free"concept is especially beneficial for control problems that require the tracking of setpoints and rejection of persistent disturbances, such as input loads. In this paper, we show how the velocity form, i.e., the time-differentiated dynamics of the system, plays a crucial role in characterizing these properties and how the analysis of it can be solved by the application of Linear Parameter-Varying (LPV) methods in a computationally efficient manner. Furthermore, by leveraging the properties of the velocity form and the LPV framework, a novel controller synthesis method is presented which ensures closed-loop universal shifted stability and performance. The proposed controller design is verified experimentally on a real system. Additionally, we compare the proposed method to a standard LPV control design, demonstrating the improved stability and performance guarantees of the new approach. © 1963-2012 IEEE.

关键词： Equilibrium independent dissipativity linear parameter-varying systems output feedback stability of nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Interference-Robust Broadband Rapidly-Varying MIMO Communications: A Knowledge-Data Dual Driven Framework

引用

IEEE Transactions on Wireless Communications 2025年

作者： Zhao, Jingjing Su, Jing Cai, Kaiquan Zhu, Yanbo Liu, Yuanwei Al-Dhahir, Naofal Beihang University Department of Electrical and Electronic Engineer Beijing China State Key Laboratory of CNS/ATM Beijing China Queen Mary University of London Department of Electronic Engineering and Computer Science London United Kingdom University of Texas at Dallas Department of Electrical and Computer Engineering Richardson United States

A novel time-efficient framework is proposed for improving the robustness of a broadband multiple-input multiple-output (MIMO) system against unknown interference under rapidly-varying channels. A mean-squared error (MSE) minimization problem is formulated by optimizing the beamformers employed. Since the unknown interference statistics are the premise for solving the formulated problem, an interference statistics tracking (IST) module is first designed. The IST module exploits both the time- and spatial-domain correlations of the interference-plus-noise (IPN) covariance for the future predictions with data training. Compared to the conventional signal-free space sampling approach, the IST module can realize zero-pilot and low-latency estimation. Subsequently, an interference-resistant hybrid beamforming (IR-HBF) module is presented, which incorporates both the prior knowledge of the theoretical optimization method as well as the data-fed training. Taking advantage of the interpretable network structure, the IR-HBF module enables the simplified mapping from the interference statistics to the beamforming weights. The simulations are executed in high-mobility scenarios, where the numerical results unveil that: 1) the proposed IST module attains promising prediction accuracy compared to the conventional counterparts under different snapshot sampling errors;and 2) the proposed IR-HBF module achieves lower MSE with significantly reduced computational complexity. © 2002-2012 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Data-driven model discovery with Kolmogorov-Arnold networks

引用

Physical Review Research 2025年第2期7卷 023037-023037页

作者： Shirin Panahi Mohammadamin Moradi Erik M. Bollt Ying-Cheng Lai School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Electrical and Computer Engineering Clarkson Center for Complex Systems Science Clarkson University Potsdam New York 13699 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Data-driven model discovery of complex dynamical systems can be done using sparse optimization, but it has a fundamental limitation: sparsity in that the underlying governing equations of the system contain only a small number of elementary mathematical functions. Examples where sparse optimization fails abound, including the classic Ikeda or optical-cavity map in nonlinear dynamics, as well as a wide variety of ecosystems. Another approach is based on machine learning, e.g., deep neural networks, which excels at capturing system behavior from data but functions as black boxes, offering little insight into how inputs influence the outputs. We propose a general model-discovery framework based on the Kolmogorov-Arnold networks (KANs) that are not constrained by the sparsity condition. The KAN framework with a simple structure is capable of accurately capturing the complex behavior of dynamical systems that do not meet the sparsity requirement while offering greater interpretability compared to conventional neural networks. This interpretability provides insights into the dynamics generating the data, which are typically inaccessible in traditional black-box function approximation methods. We demonstrate nonuniqueness in that a large number of approximate models of the system can be found that generate the same invariant set with the true statistics such as the Lyapunov exponents and Kullback–Leibler divergence. An analogy to shadowing of numerical trajectories in chaotic systems is pointed out.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Self-Adaptive Dynamic In-Band Network Telemetry Orchestration for Balancing Accuracy and Stability

引用

IEEE Transactions on Network and Service Management 2025年第2期22卷 1514-1530页

作者： Ouyang, Tianhao Yao, Haipeng He, Wenji Mai, Tianle Wang, Fu Yu, F. Richard Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Beijing Institute of Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing University of Posts and Telecommunications School of Electronic and Engineering Beijing100876 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In-band network telemetry (INT) is an emerging network measurement technique that offers real-time and fine-grained visualization capabilities for networks. However, the utilization of INT for network measurement introduces additional overheads to the network. The process of data collection consumes extra bandwidth resources, and adjustments to the data collection scheme can impact network stability. Additionally, the INT orchestration scheme requires adaptation to dynamics in the network to improve measurement accuracy. Therefore, striking a balance between accuracy and stability becomes a critical problem. In this paper, our focus lies in the trade-off between measurement accuracy and network stability. We consider the long-term orchestration of multiple telemetry tasks, rationally deploying distinct telemetry tasks to different application flows. To address the challenge, we propose a self-adaptive Dynamic INT Orchestration scheme, D-INTO. Specifically, we formulate a stochastic optimization problem for dynamic INT orchestration. Then we employ Lyapunov optimization to decouple the stochastic optimization problem and use surrogate Lagrangian relaxation to construct a polynomial-time approximation algorithm. Theoretical analysis and experimental results demonstrate that our proposed D-INTO outperforms existing schemes in terms of adaptability to the network dynamics. © 2004-2012 IEEE.

关键词： Polynomial approximation

来源：评论

学校读者我要写书评

暂无评论

Impact of diameter on D-shaped POF sensors for salt detection

Impact of diameter on D-shaped POF sensors for salt detectio...

引用

International Laser Technology and Optics Symposium 2024, iLATOS2024

作者： Khan, Abdul Ali Thirunavakkarasu, Punithavathi M. bte Saidin, Norazlina Noor, Ahmad Shukri Muhammad Waqas, Nawaf Communication Technology Section Universiti Kuala Lumpur British Malaysian Institute Kuala lumpur53100 Malaysia Faculty of I.C.T BUITEMS Quetta87100 Pakistan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia Department of Instrumentation and Control Engineering Universiti Kuala Lumpur British Malaysian Institute Bt. 8 Jalan Sungai Pusu Selangor Gombak53100 Malaysia

This study investigates the relationship between the diameter of a D-shaped plastic optical fiber (POF) sensor and its optical response as a function of varying salt concentrations. A simple and efficient dry etching polishing technique was employed to create D-shaped POF sensors with a range of diameters. All the fabricated sensors were carefully developed to maintain a consistent length of 20 cm with a sensing region of 1cm. To evaluate the optical intensity response, each sensor, with its respective diameter, was examined with the salt concentration ranging from (0 to 5%) examination utilizing a spectrometer. The sensor response was characterized by quantifying the variations observed in the intensity of the optical signal propagating through the sensing region. The sensors having a diameter of 500 μm, 700 μm, and 900 μm had a sensitivity of 149 A.U/%salt, 66 A.U/%salt, and 11.2 A.U/%salt respectively. The sensitivity of the 500 μm diameter sensor increased 13 times approximately as compared to the sensor having diameter of 900 μm. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Dry etching

来源：评论

学校读者我要写书评

暂无评论

SpikeSpec: An On-chip Learning Neuromorphic Accelerator for Spectrum Sensing With Triplet-Boosting and Hardware Friendly Loss Function

引用

IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Azmine, Muhammad Farhan Li, Ruizhe Sharma, Gauri Yi, Yang Virginia Tech Department of electrical and computer engineering BlacksburgVa United States United States Multifunctional Integrated Circuits and Systems Lab United States

Spectrum sensing is a pivotal function in next-generation (G) Multiple-Input-Multiple-Output (MIMO) communication systems, tasked with detecting and characterizing the occupancy or availability of frequency bands within the radio spectrum. Conventional spectrum sensing techniques are hindered by challenges such as hardware complexity and the Signal-to-Noise Ratio (SNR) wall, leading to suboptimal performance in environments with high noise levels. Recurrent Neural Networks (RNNs), particularly Liquid State Machines (LSMs), are highly effective for developing energy-efficient accelerators, as they efficiently capture temporal dependencies in primary user frequency spectrums with a reduced number of trainable parameters. This paper introduces an innovative FPGA accelerator based on Liquid State Machines (LSMs), featuring fully integrated on-chip learning capabilities for spectrum sensing. Our accelerator leverages Reward-based Spike Timing-Dependent Plasticity (R-STDP) to discern temporal correlations within the related frequency band. Although traditional R-STDP methods face convergence difficulties during on-chip learning, the introduced approach overcomes this challenge with a novel, hardware-efficient loss function. This mechanism which is also hardware friendly, facilitates accelerated convergence with reduction of training period of about 46.67% in spectrum sensing classification for hardware implementation. Moreover, we implemented a fully asynchronous, low-latency, unsupervised Triplet-based STDP learning mechanism in the LSM accelerator reservoir, which improves training accuracy by about 3.88% in high-noise channels while enhancing reconfigurability. Furthermore, we investigated various encoder mechanisms to identify the most efficient encoder architecture for our LSM, leading to an accuracy increase of 6.11%. Our optimized LSM architecture achieved 1.27 times and 2.01 times the LUT and register counts, respectively, compared to the basic fixed-reservoir LSM

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Interpretable CNN-Based Lithographic Hotspot Detection Through Error Marker Learning

引用

IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年第3期44卷 1031-1044页

作者： Sun, Haoyang Jiang, Cong Ye, Xun Feng, Dan Tan, Benjamin Ma, Yuzhe Liu, Kang Huazhong University of Science and Technology School of Computer Science and Technology Wuhan430074 China Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Wuhan430074 China University of Calgary Department of Electrical and Software Engineering CalgaryABT2N 1N4 Canada With Microelectronics Thrust Guangzhou510530 China

As the technology node develops toward its physical limit, lithographic hotspot detection has become increasingly important and ever-challenging in the computer-aided design (CAD) flow. In recent years, convolutional neural networks (CNNs) have achieved great success in hotspot detection. However, the interpretability of their hotspot prediction has yet to be considered. Compared with conventional lithography simulation and pattern matching-based methods, the black-box nature of CNNs wavers their practical applications with confidence. In this article, we propose the first interpretable CNN-based hotspot detector capable of providing high-detection accuracy and reliable explanations for hotspot identification. Specifically, we augment the training dataset with expanded error markers obtained and preprocessed from lithography simulation, which are then learned by an encoder-decoder architecture as intermediate features. We additionally introduce coordinate attention in the encoder to facilitate better-feature extraction. By learning these error markers and part of their surrounding metals as root cause hotspot features, our architecture achieves the highest-hotspot accuracy of 99.78% and the lowest-false positive rate of 5.29% compared to all prior work. Moreover, our method demonstrates the best visual and quantitative interpretability results when applying CNN interpretation methods. © 2024 IEEE.

关键词： Pattern matching

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：