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检索条件"主题词=Signal Processing Algorithms"

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Visualization of Real Time Forest Fire Detection

Visualization of Real Time Forest Fire Detection

引用

IEEE International Conference on Intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： E. Ajitha Priya V Priya Dhashini R I Department of Computer Science and Engineering St. Joseph's Institute of Technology Tamil Nadu India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Forest fires are a serious hazard to both the environment and human life. For an effective and timely response, early detection of these fires is essential. This study offers a reliable method for detecting forest fires utilizing the cutting-edge real-time object identification technique known as the YOLO (You Only Look Once) algorithm method. The process entails gathering a varied dataset of photos that include both fire and non-fire scenarios, labeling the photos with bounding boxes, and using this dataset to refine a YOLO model that has already been trained. Subsequently, the YOLO model is applied to real-time fire detection in photos or live video streams sourced from forested regions. Traditional fire detection techniques have been employed, but deep learning-based techniques have drawn a lot of attention because of their high accuracy and capacity to understand intricate patterns. The current research problem of keeping computing costs low while attaining high accuracy rates with deep learning-based fire detection techniques is addressed in this study. In order to properly address this difficulty, this study provides a method based on the YOLOv8 algorithm that involves the training, validation, and testing of the model as well as its development using a bespoke dataset. The precision, recall, and F1-curve metrics provide a concise evaluation of the model's effectiveness. Notably, the model is highly proficient in fire detection, which is critical for early alerts and prevention. Our proposed method works better than existing state-of-the-art methods, according to experimental data and performance evaluations. This makes this method quite promising for fire detection.

关键词： YOLO Training signal processing algorithms Forestry Streaming media signal processing Real-time systems

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High Precision Cooperative Location Method for Multistatic Radar Based on Sparse Recovery

High Precision Cooperative Location Method for Multistatic R...

引用

6th International Conference on Intelligent Computing and signal processing (ICSP)

作者： Hengcheng Zhu Yawei Chen Wenjun Yang Nanjing Research Institute of Electronics Technology Nanjing China National Key Laboratory of Radar Detection and Sensing Nanjing China Jiangsu Provincial Key Laboratory of Detection and Sensing Technology Nanjing China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

In the case of target location using multistatic radar in the far-field region, the linear superimposed cross-location method tends to generate more false alarms and misses, resulting in lower location accuracy. To solve this problem, a method of multistatic radar working together for sparse target location is proposed. Exploiting the sparse characteristics of targets mainly existing within specific ranges, a high-precision cooperative location method based on sparse recovery for multistatic radar is introduced. By employing sparse algorithms and nonlinear processing, the traditional cross-location method for multistatic radar is improved, thereby enhancing the location accuracy of the multistatic system. Simulation results show that this method can accurately locate the actual position of the target, achieving high-precision location of cooperative multistatic radar in far-field region.

关键词： Accuracy Radar cross-sections Simulation signal processing algorithms signal processing Multistatic radar

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Performance of CSI and RSS in Indoor Localization

Performance of CSI and RSS in Indoor Localization

引用

International Conference on Telecommunications and signal processing (TSP)

作者： Miroslav Hutar Peter Brida Juraj Machaj Department of Multimedia and Information-Communication Technology University of Zilina Zilina Slovakia

ISBN: (数字)9798350365597

ISBN: (纸本)9798350365603

Localization in WiFi networks has become an important research area due to its wide range of applications in various domains. In this paper, we focus on the evaluation of the localization performance achieved for fingerprinting localization using Channel State Information (CSI) and Received signal Strength (RSS) in WiFi networks. CSI and RSS are two types of measurements that can be extracted from WiFi signals and utilized to estimate the location of a mobile device. However, the accuracy and reliability of localization can vary depending on these measurements. In this paper experimental evaluation of the performance of the WiFi based positioning based on RSS and CSI measurements is presented. Both CSI and RSS data from two access points were collected under identical conditions and used to estimate the position of a mobile device. The performance was compared based on achieved localization errors for both approaches.

关键词： Location awareness Performance evaluation Wireless communication Accuracy signal processing algorithms Fingerprint recognition Mobile handsets

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Advancing Underwater Communication with NBO-MFO Hybrid Routing in UWSNs

Advancing Underwater Communication with NBO-MFO Hybrid Routi...

引用

International Conference on Communications and signal processing

作者： S.A. Kalaiselvan M.Lenin Kumar M. Amanullah T.R. Mani Chigurupati Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Electronics and Communications Engineering Vignan Institute of Technology and Science Telangana India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering TKR College of Engineering and Technology Telangana India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

In this research provides a solution for optimizing routing path selection in Underwater Wireless Sensor Networks (UWSNs). The algorithm combines Namib Beetle Optimization (NBO) and Moth-Flame Optimization (MFO), integrating them into the ILEACH methodology for efficient routing path selection. The algorithm operates in an iterative manner, commencing with NBO’s feature selection process, evaluating fitness through average classification error and feature selection ratio. Simultaneously, MFO mimics moth behavior, updating positions via a logarithmic spiral function based on flame locations. The mutual learning phase facilitates information exchange between NBO and MFO, enhancing their collective intelligence and refining the routing path selection process. ILEACH’s contribution lies in its fitness aggregation and selection methods. It amalgamates various criteria, including energy levels, distances, and node conditions, into a comprehensive fitness metric. Subsequently, ILEACH selectively identifies optimal routing paths aligned with energy-efficient criteria and node statuses, ensuring efficient data transmission and energy conservation within UWSNs. This integrated approach fosters a comprehensive strategy for routing path selection in UWSNs, ensuring sustainability and efficiency in data transmission within challenging underwater environments.

关键词： Wireless sensor networks Machine learning algorithms Scalability signal processing algorithms Routing Feature extraction Energy efficiency

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Design of Wireless ECG Monitoring System

Design of Wireless ECG Monitoring System

引用

Electronics, Circuits and Information Engineering (ECIE), International Conference on

作者： Yuan-Ge Yang Hao-Xiang Lei Fan Yang Li-Juan Chen School of Information Engineering Xi’an Mingde Institute of Technology Xi’an Shanxi China

ISBN: (数字)9798350388312

ISBN: (纸本)9798350388329

With the acceleration of people’s lifestyles, monitoring of human physiological signals has become increasingly important. This article designs a wireless electrocardiogram (ECG) monitoring system that can detect human physiological signals such as ECG, blood oxygen saturation, and body temperature. The physiological signal monitoring system mainly consists of system display, signal acquisition, cloud data sharing, signal processing, and feature detection. It includes a remote ECG data download and analysis platform for remote monitoring and analysis diagnosis. The system designs a denoising algorithm and a feature analysis algorithm based on wavelet transform, achieving filtering and feature extraction of ECG signals. This system has important research significance for the early prevention of heart disease and the development of ECG monitoring equipment.

关键词： Wireless communication Wavelet transforms Prevention and mitigation Noise reduction signal processing algorithms Electrocardiography Feature extraction

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Enabling Efficient Federated Learning via Ternary Quantization over Fading Channels

Enabling Efficient Federated Learning via Ternary Quantizati...

引用

International Conference on Communications, signal processing, and their Applications (ICCSPA)

作者： Ada Irem Pekdemir Ferkan Yilmaz Hakan Ali Çırpan Istanbul Technical University Electronics and Communication Engineering Istanbul Turkey Radar Electronic Warfare and Intelligence Systems Division ASELSAN A.Ş. Ankara Turkey

ISBN: (数字)9798350384819

ISBN: (纸本)9798350384826

Federated Learning (FL) performance degrades when noise and fading affect uplink and downlink transmissions between users and the Fusion Center (FC). This research addresses a gap by investigating the impact of these channel effects on global machine learning (ML) models. We propose a method to improve communication and computation efficiency in FL using ternary quantization and a doping ratio. We simulate an additive noise channel with Rayleigh fading in both uplink and downlink transmissions. Two algorithms, Stochastic Gradient Descent with Momentum (SGDM) and Gradient Descent Backpropagation (GRDBP), are used to train local ML models. ML model parameters are then quantized with three values and power-adjusted before transmission. The doping ratio explores how combining user's local ML model with the global ML model at different ratios affects re-learning. Our simulations show that a doping ratio of 0.5 or higher significantly improves the system's resistance to additive noise and channel fading, leading to higher accuracy. Further, the combination of GRDBP, ternary quantization, and a high doping ratio is shown to be particularly effective under these challenging channel conditions. This technique enables FL systems to achieve faster, more accurate performance while maintaining user data privacy.

关键词： Resistance Quantization (signal) Accuracy Federated learning Computational modeling signal processing algorithms Doping Rayleigh channels Semiconductor process modeling Uplink

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Electrochemical Sensing of the Colorectal Cancer BRAF p.V600E Mutation Using a Lab-on-Chip Integrated DNA Amplification Analysis Method

Electrochemical Sensing of the Colorectal Cancer BRAF p.V600...

引用

IEEE SENSORS

作者： Calista Adele Yapeter Katerina-Theresa Mantikas Costanza Gulli Nicolas Moser Constantinos Simillis Melpomeni Kalofonou Pantelis Georgiou Department of Electrical and Electronic Engineering Centre for Bio-Inspired Technology Imperial College London UK Department of Surgery Cambridge Colorectal Unit Cambridge University Hospitals NHS Foundation Trust UK

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Despite the increasing occurrence and high mortal-ity rate of colorectal cancer (CRC) in low resource settings, the lack of reliable point-of-care (POC) devices remains a critical issue in its diagnosis. Recent advancements in the miniaturisation of biosensors have contributed to the progression of lab-on-chip (LoC) technology for cancer diagnostics, where this study proves the feasibility of detecting the BRAF p. V600E mutation, one of the major CRC biomarkers, through loop-mediated isothermal amplification (LAMP) reactions conducted on integrated ion-sensitive field-effect transistor (ISFET) sensors. Our findings reveal that LAMP reactions conducted in a qPCR machine and on the LoC device are allele-specific and produce comparable output yields, with a limit of detection (LOD) of 500 copies/μL and time-to-positive (TTP) under 15 minutes. Preliminary results suggest that specific, non-specific and control reactions that have been conducted in parallel produce distinct trends in their output signals. A signal processing methodology was developed to quickly distinguish between positive and negative outputs using simple data manipulation and analysis techniques. The LoC system has proven to be a robust method for detecting cancer mutations and has the potential to be adapted for multi-reaction sensing. This research is an essential step towards creating a practical multigene cancer panel for POC testing, which would be a game-changer in cancer diagnostics.

关键词： DNA signal processing algorithms Colorectal cancer Biomarkers Lab-on-a-chip Sensors Classification algorithms Biosensors Transistors Testing

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Asymptotically Optimal Closed-Form Phase Configuration of 1-bit RISs via Sign Alignment

Asymptotically Optimal Closed-Form Phase Configuration of 1-...

引用

IEEE Workshop on signal processing Advances in Wireless Communications (SPAWC)

作者： Kyriakos Stylianopoulos Panagiotis Gavriilidis George C. Alexandropoulos Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece Department of Electrical and Computer Engineering University of Illinois Chicago IL USA

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

While Reconfigurable Intelligent Surfaces (RISs) constitute one of the most prominent enablers for the upcoming sixth Generation (6G) of wireless networks, the design of efficient RIS phase profiles remains a notorious challenge when large numbers of phase-quantized unit cells are involved, typically of a single bit, as implemented by a vast majority of existing metasurface prototypes. In this paper, we focus on the RIS phase configuration problem for the exemplary case of the signal-to-Noise Ratio (SNR) maximization for an RIS-enabled single-input single-output system where the metasurface tunable elements admit a phase difference of π radians. We present a novel closed-form configuration which serves as a lower bound guaranteeing at least half the SNR of the ideal continuous (upper bound) SNR gain, and whose mean performance is shown to be asymptotically optimal. The proposed sign alignment configuration can be further used as initialization to standard discrete optimization algorithms. A discussion on the reduced complexity hardware benefits via the presented configuration is also included. Our numerical results demonstrate the efficacy of the proposed RIS sign alignment scheme over iterative approaches as well as the commonplace continuous phase quantization treatment.

关键词： Upper bound Wireless networks signal processing algorithms Rayleigh channels Reconfigurable intelligent surfaces Metasurfaces SISO communication Surface treatment Standards signal to noise ratio

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Query processing And Optimization Method of Ethnic Music Data Based on Deep Belief Network

Query Processing And Optimization Method of Ethnic Music Dat...

引用

Data Analytics, Computing and Artificial Intelligence (ICDACAI), International Conference on

作者： Sixian He Siyuan He Xin Gao College of Music and Dance North Minzu University School Yinchuan China College of Music Ningxia University Yinchuan China Faculty of Music and Performing Arts Universiti Pendidikan Sultan Idris Tanjung Malim Perak Malaysia School of Materials Science & Engineering North Minzu University Yinchuan China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

With the development of the Internet and the large-scale digital music industry, the acquisition and listening of music are presented to users in a more convenient way. How to find the music that users like to hear from the massive digital music data on the Internet has become a key issue in the field of ethnic music information retrieval. Key issues and main goals addressed. There is a complex relationship between ethnic music data, which is suitable for modeling and query processing with data structure. However, the existing query processing algorithms only focus on structural features, and are not optimized for folk music metadata and music content data, and the query efficiency is not high. Currently, the amount of data in various media is exploding, and digital music is everywhere and increasing day by day. At the same time, various music applications have also greatly contributed to the advancement of information technology, such as music sharing, which made the ancient peer-to-peer technology mainstream at the end of the 20th century. The method used in this paper is a deep belief network. Compared with other classification algorithms, its error convergence speed is faster, and the final recognition error for the data set is relatively smaller.

关键词： Query processing Refining signal processing algorithms Optimization methods Music Prototypes signal processing Internet Peer-to-peer computing Pattern matching

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MU-MIMO and Multi-Beam ISAC Hybrid Beamforming Design

MU-MIMO and Multi-Beam ISAC Hybrid Beamforming Design

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International Symposium on Communication Systems, Networks and Digital signal processing, CNSDSP

作者： Leonardo Leyva Daniel Castanheira Adão Silva Atílio Gameiro Instituto de Telecomunicações and Universidade de Aveiro Aveiro Portugal

ISBN: (数字)9798350348743

ISBN: (纸本)9798350348750

This paper addresses the problem of fully-connected hybrid analog-digital (HAD) beamforming design for a multi-user and multi-beam ISAC systems. The traditional approaches to this problem involve a two-step process: first, a fully digital precoder is obtained, then the HAD beamforming is resolved by minimizing the Euclidean distance to the previously designed fully digital precoder. However, the main drawback of this method is that the communication or radio-sensing constraints considered in the first phase may be not preserved after the second one. In contrast, our work prioritizes preserving these constraints by directly designing the fully-connected HAD beamforming. We maximize the weighted sum rate while subject to power budget and radio-sensing constraints. To solve this, we propose an innovative iterative alternate optimization algorithm. Simulation results demonstrate a performance close to that of a fully digital precoder, outperforming previous fully-connected hybrid beamforming methods for ISAC.

关键词： Radio frequency Array signal processing Simulation signal processing algorithms Euclidean distance Digital signal processing Iterative algorithms

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