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共 3487 条记录，以下是251-260 订阅

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Delay-Aware Probabilistic Cache Placement for Scalable Videos in Satellite-Terrestrial Networks

Delay-Aware Probabilistic Cache Placement for Scalable Video...

引用

International conference on Wireless Communications and signal processing (WCSP)

作者： Jiayi We Tianheng Xu Yuling Ouyang Jinfeng Tian Ting Zhou School of Microelectronics Shanghai University Shanghai China Chinese Academy of Sciences Shanghai Advanced Research Institute Shanghai China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

With the rapid expansion of video services, caching has emerged as a promising solution to reduce retrieval delay and alleviate backhaul pressure. Specifically, caching video content on user devices and satellites is particularly effective for users without ground base station services. However, addressing the challenge of meeting users' varying video quality demands while reducing content transmission delay is critical. Therefore, this paper investigates a layered caching scheme based on Scalable Video Coding, which encodes videos into different layers to provide various quality levels and caches video content on different nodes. Furthermore, an optimization problem for the probabilistic cache placement scheme in a multi-layer caching model is proposed and solved using the Quasi-Oppositional Whale Optimization Algorithm. The simulation results indicate that, compared to other algorithms and benchmark schemes, the proposed scheme effectively reduces transmission delay.

关键词： Wireless communication Satellites Simulation signal processing algorithms Static VAr compensators Probabilistic logic Space-air-ground integrated networks Whale optimization algorithms Delays Video recording

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Design and development of Reversible Comparator Circuit using Qiskit

Design and development of Reversible Comparator Circuit usin...

引用

signal processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), International conference on

作者： Kavitha S S Sitadevi Bharatula Harshit Royal Dandu Pradeep Kumar Reddy Department of ECE National Institute of Engineering Mysuru India(Affilated to VTU Belgavi) Department of ECE Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540692

Quantum computing is at the leading edge of advanced technology that uses quantum phenomena such as entanglement and super position to solve complex problems. One of the main application is to built comparator circuit to do arithmetic operations at stipulated time. Based on this our research is to propose the design and implementation of one-bit and two-bit quantum comparators using IBM Qiskit, which is formly compared with classical comparator. Also this work represents a comprehensive overview of the techniques required to optimize and design quantum comparator circuits using real quantum simulators. The results obtained from simulation promises the comparison accuracy with classical results. From the circuit designed it is inferred that the hardware complexity is very much reduced compared to classical comparator, which are tabulated in terms of number of quantum gates. The proposed method can further be extended to generate higher order comparator circuits. These results may form the basis for further research and development that will support the advancement of quantum computing and algorithms.

关键词： Quantum computing Quantum entanglement signal processing algorithms signal processing Logic gates Hardware Communications technology

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An Initial Survey on Quantum Enhanced RF signal Extraction in Cluttered Environments

An Initial Survey on Quantum Enhanced RF Signal Extraction i...

引用

IEEE National conference on Aerospace and Electronics (NAECON)

作者： Vatsa Patel Zhenhua Jiang University of Dayton Research Institute Dayon OH USA

ISBN: (数字)9798350367621

ISBN: (纸本)9798350367638

RF (radio frequency) signals are commonly used in modern communication systems, e.g., radio broadcasting, mobile electronic devices, smart meters, satellite transmission, etc., but often face significant challenges such as signal interference and/or background noise. To gain a deeper understanding of signal extraction methods, in this paper, we perform an initial survey on the existing approaches and general trends in extracting signals of interest from the mixed signals received in cluttered environments, including advanced sensing, filtering, data augmentation, machine learning, and emerging quantum-enhanced signal processing algorithms. We then study a specific machine learning model that employs a Bayesian neural network (BNN) as the encoder, combined with a decoder based on a deep neural network (DNN), a long short-term memory (LSTM) network, or another BNN. Case studies are performed to compare different autoencoder neural network models, and initial testing results show that the BNN's probabilistic parameters can handle input signal uncertainty well and may significantly enhance feature extraction and signal clarity. Planned future research will explore quantum computing methods to enhance RF signal extraction in cluttered environments, and some potential quantum algorithms are also identified in the paper.

关键词： Surveys Uncertainty RF signals signal processing algorithms Machine learning Feature extraction Smart meters

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Disease Detection in Groundnut Crop Using Deep Learning Models

Disease Detection in Groundnut Crop Using Deep Learning Mode...

引用

Artificial Intelligence and signal processing (AISP), INDIA, International conference on

作者： Bojja Bala Sai Harsha Vardhan Hitesh Paluvadi Vasudha Karthikeya Sai Srihari Rajesh C B Department of Electronics and Communication Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350350654

ISBN: (纸本)9798350350661

Early detection of the diseases is very vital for the well-being and improvement of the crop. Often, it is difficult to detect the disease of the crop upon observation with a naked eye. Professionals in identifying plant diseases are very less and their availability in each and every region is one of the primary difficulties that the agriculture sector is facing. So, the best solution for this problem is to replace a human with an advanced and well-trained model that can help in accurate detection of the plant disease. Several people have researched in this field. Yet, the results are not always promising and there is lot of scope for improvement. In this project, we made use of Groundnut crop for determining the performance of the disease detection model that we are developing. After referring to various papers, we eventually decided to work on three models- CNN, MobilenetV2 and InceptionResnetV2. Our ultimate aim is to determine the best model among these three for groundnut disease detection.

关键词： Deep learning Plant diseases Visualization Accuracy Scalability Crops signal processing algorithms signal processing Agriculture Classification algorithms

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Waveform Design for Sparse signal processing in Radar

Waveform Design for Sparse Signal Processing in Radar

引用

IEEE Radar conference (RadarConf)

作者： Anitori, Laura Ender, Joachim TNO Radar Technol The Hague Netherlands Univ Siegen Fraunhofer FHR Siegen Germany

ISBN: (纸本)9781728176093

In the past decades, there has been an extensive research interest in the areas of both waveform diversity/design and advanced signal processing algorithms departing from the more classical solutions based on Linear Frequency Modulated (LFM) pulses and Matched Filters (MF). In the waveform diversity community, especially within the context of spectrum sharing, MIMO and cognitive radars, several waveform optimization and design methodologies have been studied, see [1], [2] and references therein. In parallel to waveform design, several signal processing techniques have also been proposed which exploit some kind of prior knowledge and/or iterative algorithms to improve the performance of the more classical MF, such as the Adaptive Pulse Compression(APC) [3], MUSIC [4], CLEAN [5] and Sparse signal processing (SSP) [6], [7]. In this paper we present some results and examples to show how the combination of waveform design with SSP can lead to improved performance in radar compared to the more classical approach.

关键词： Target tracking Radar measurements signal processing algorithms Receivers Object detection Radar tracking Radar signal processing

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Evaluation of the Novel Technique's Performance in Terms of Energy Consumption, Security and Reliability using Simulations or Real-World Experiments

Evaluation of the Novel Technique's Performance in Terms of ...

引用

Electronics, Communication and signal processing (ICECSP), International conference on

作者： Avneesh Gour Nishant Kumar Pathak Department of CSE Shobhit Institute of Engineering & Technology (A NAAC Accredited Deemed to-be- University) Meerut UP. INDIA Department of CSE Ajay Kumar Garg Engineering College Ghaziabad UP. INDIA

ISBN: (数字)9798350364590

ISBN: (纸本)9798350375381

Wireless Sensor Networks (WSNs) are essential for many applications, such as industrial automation, healthcare, and environmental monitoring. As these networks continue to grow, ensuring the security and energy efficiency of data transmission becomes paramount. This research proposes a novel Secure Energy Consumption Technique (SECT) designed to address the simultaneous challenges of securing communication and optimizing energy consumption in WSNs. The SECT integrates advanced encryption algorithms and efficient key management protocols to fortify the security of data transmission within the network. By employing lightweight cryptographic techniques, the proposed solution aims to assault a balance between security and energy efficiency, ensuring that the overhead associated with encryption does not compromise the sensor nodes' restricted energy resources. Key features of the SECT include a dynamic key management system that adapts to the network's changing conditions, minimizing energy consumption while maintaining a robust security posture. Additionally, the technique incorporates energy-aware routing algorithms to optimize the path selection for data transmission, further reducing energy expenditure.

关键词： Wireless sensor networks Energy consumption Protocols Heuristic algorithms signal processing algorithms Particle measurements Energy efficiency Encryption Security Data communication

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Artificial Intelligence-based Interference signal Recognition for Satellite Communications

Artificial Intelligence-based Interference Signal Recognitio...

引用

advanced Control Systems and Automation Technologies (ACSAT), International conference on

作者： Xiaoyu Han The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China

ISBN: (数字)9798331541668

ISBN: (纸本)9798331541675

With the rapid development of satellite communication technology, the emergence of interference signals is becoming more and more frequent, which seriously affects the reliability and safety of communication. For this reason, this paper designs a satellite communication interference signal recognition system based on artificial intelligence, which adopts a modularized design and covers multiple aspects such as signal acquisition, pre processing, feature extraction and classification recognition. The system realizes high-fidelity signal acquisition through a high dynamic range broadband receiver, uses FPGA to carry out real-time data preprocessing, and combines deep learning technology to adaptively extract interference signal features. The classification and recognition module incorporates a variety of advanced algorithms to significantly improve the accuracy of detection and recognition. Experimental results show that the system designed in this paper exhibits excellent detection performance under different signal-to-noise ratio conditions, and the recognition accuracy reaches $\mathbf{9 7. 5 \%}$ on average, which is 5.7 percentage points higher than the traditional SVM-based algorithm. This research provides an effective guarantee for the anti-jamming capability of satellite communication system, which has important application value and promotion potential.

关键词： Deep learning Accuracy Heuristic algorithms Interference Receivers Feature extraction Real-time systems High dynamic range Satellite communications signal to noise ratio

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MAO: An Efficient Resource Utilization of Task Scheduling in Cloud Fog Environment

MAO: An Efficient Resource Utilization of Task Scheduling in...

引用

International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： K. Anusha Santhosh Kumar Medishetti P. Archana Ganesh Reddy Karri Kuppusamy P Marri Laxman Reddy Institute of Technology India VIT-AP University Amaravathi India Anurag University Hyderabad India

ISBN: (数字)9798350350845

ISBN: (纸本)9798350350852

In the context of Cloud-Fog Computing (CFC) efficient Task Scheduling (TS) plays a critical role in optimizing resource allocation and meeting the increasingly complex performance demands of modern computing infrastructures. This study introduces an advanced iteration of the Mexican Axolotl Optimization (MAO) algorithm, a bio-inspired metaheuristic designed to address the intricate challenges of task scheduling in dynamic and distributed computing environments. The MAO algorithm presented here incorporates advanced heuristics, self-optimization mechanisms, and innovative features to significantly improve task scheduling processes. By imitating the axolotl's capacity for self-healing, the algorithm offers a solution that is both robust and adaptable to dynamic computing conditions, making it well-suited to the challenges posed by CFC. The primary objectives of the MAO algorithm are to improve resource allocation, reduce latency, and enhance overall operational efficiency in cloud and fog computing ecosystems. It achieves this by optimizing the allocation of computing tasks to available resources, taking into account factors such as makespan time, success rate and response time, while dynamically adapting the fluctuations in workloads and resource availability. By enhancing resource utilization and reducing response time, this algorithm is poised to make significant contributions to the efficiency, reliability, and overall performance of CFC infrastructures. The experimental findings indicate that the proposed algorithm exhibits superior performance in terms of makespan and response time reduced by 28% and 36%, success rate increased by 31 % and compared to alternative approaches.

关键词： Wireless communication Processor scheduling Heuristic algorithms Metaheuristics signal processing algorithms signal processing Dynamic scheduling

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A Novel Method to Identify and Classify Deterioration of Orange Juice

A Novel Method to Identify and Classify Deterioration of Ora...

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Communication Engineering and Emerging Technologies (ICoCET), IEEE International conference on

作者： Saharsh Madassery Abeer Elkhouly Mohd Fareq Abd Malek School of Engineering University of Wollongong in Dubai Dubai UAE

ISBN: (数字)9798331504144

ISBN: (纸本)9798331504151

The deterioration of orange juice poses significant health risks to consumers and undermines the integrity of the fruit juice market. Current detection methods, such as the Brix method, have limitations in specificity and practicality, often requiring sophisticated laboratory equipment and being time-consuming. This paper explores an innovative approach to detecting orange juice adulteration using microwave reflection techniques combined with advanced machine learning models. A Vector Network Analyzer (VNA) was employed to measure the dielectric properties of orange juice samples over a broad frequency range. Data were processed using advanced signal processing algorithms and various normalization techniques. Several machine learning models were evaluated, with the Cubic Support Vector Machine (SVM) achieving a final validation accuracy of 99.7%. This study presents a novel, non-destructive, and cost-effective solution for real-time detection of adulterants in orange juice, contributing to consumer safety and market integrity.

关键词： Support vector machines signal processing algorithms Network analyzers Machine learning Vectors Reflection Real-time systems Frequency measurement Dielectrics Safety

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Research on embedded digital communication processing system

Research on embedded digital communication processing system

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Computers, Information processing and advanced Education (CIPAE), 2020 International conference on

作者： Yong Cao Yifan Zheng Caiyun Sun Di Zhang Army Academy of Armored Forces Beijing China

This project mainly studies the hardware architecture of the system, digital signal encoding and decoding processing and digital communication protocol. The composition of hardware architecture needs to address the adaptation of communication rate and information acquisition part to achieve the optimal hardware state, timely collect digital signals for processing and make system-level response; Digital signal encoding and decoding is the key to data signal processing and transmission of the project. Noise reduction and compression are completed by corresponding algorithms, and then transmitted to other equipment terminals via digital links for decompression and processing; The digital communication system adopts the serial communication network, and the communication mode adopts the single master/multiple slave device mode to realize the single master/multiple slave two-way communication and realize the communication control of the distributed electronic system.

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