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检索条件"主题词=Signal Processing Algorithms"

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Fragmentation-Aware Demand Routing on Elastic Optical Network

Fragmentation-Aware Demand Routing on Elastic Optical Networ...

引用

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

作者： Der-Rong Din Department of CSIE NCUE Changhua City Taiwan R. O. C.

ISBN: (数字)9798350348743

ISBN: (纸本)9798350348750

In this paper, we address the demand routing problem in elastic optical networks (EONs), where the objective is to establish suitable lightpaths for each connection request. Our contribution lies in proposing two fragmentation-aware algorithms that take into account both fragmentation and misalignment factors. These algorithms are designed to determine optimal routing paths, modulation formats, and spectrum assignments in EONs. Through comprehensive simulations, we assess the performance of the proposed algorithms in terms of bandwidth blocking probability (BBP) and demonstrate their efficacy in achieving favorable outcomes. Considering the misalignment measure can yield better BBP values than algorithms only considering fragmentation.

关键词： signal processing algorithms Modulation Digital signal processing Bandwidth Optical fiber networks Optical variables measurement Routing

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Simulator for Underwater Acoustic Vector Sensor's Recorded Pressure and Particle Velocity signals for User Defined Scenarios

Simulator for Underwater Acoustic Vector Sensor's Recorded P...

引用

OCEANS

作者： Sandhya Prajapati Arun Kumar Rajendar Bahl Centre of Applied Research in Electronics Indian Institute of Technology Delhi New Delhi India

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

This paper presents a simulator for pressure and particle velocity signals recorded by an underwater Acoustic Vector Sensor (AVS) for user-defined scenarios, incorporating an underwater sound propagation model to estimate the AVS's signals. Its utility is multi-fold. Firstly, it can be used to study and evaluate the performance of signal processing algorithms such as DOA estimation for various underwater applications. Secondly, it acts as a precursor or substitute for a controlled testing environment during the prototyping phase. The AVS consists of one hydrophone and three co-located orthogonal uniaxial accelerometers, effectively encoding the sound field's 4D information. It measures acoustic pressure and particle velocity along three orthogonal axes. It inherently exhibits a directivity index of 3–6 dB compared to a hydrophone. Compared to hydrophone arrays, its dimensions are significantly smaller. These qualities make it a better option than hydrophone arrays when looking for compact, directed acoustic receivers for applications like AUV platforms. Thus, this paper has addressed the need for an AVS simulator in order to better understand and design supporting algorithms. The presented simulator may serve multiple user defined scenarios. For a given input pressure waveform, it emulates the signals received at the four channels of the AVS in both physical and electrical units. Furthermore, the validity of the simulated signals is verified through separate analyses using cases independent of the simulator.

关键词： Training Machine learning algorithms Echo sounders Software algorithms signal processing algorithms Vectors Velocity measurement

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Return-to-Go Predicting Decision Transformer for Energy-Saving in 5G Base Stations with Photovoltaic Integration

Return-to-Go Predicting Decision Transformer for Energy-Savi...

引用

International Conference on Wireless Communications and signal processing (WCSP)

作者： Jun Li Xiao Yu Pengcheng Xia Ting Ma Jie Zhang School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

To address the challenges of energy conservation, emission reduction, and the dual-carbon strategy, the integration of photovoltaic solar panels has become increasingly important in the energy management of 5G Base Stations (BS). Efficient energy scheduling is essential to accommodate the growing number of users and traffic demands. To optimize the energy efficiency and service quality of BS, this paper proposes an intelligent decision model based on the Decision Transformer (DT), named Return-to-Go Predicting Decision Transformer (PDT). This model incorporates training for the target return-to-go (RTG) during the training phase, enabling it to auto-matically select an appropriate RTG during inference based on the environment. This approach enhances the model's accuracy and performance in complex environments. Simulation results demonstrate the PDT can dynamically adjust the working status of base stations, as well as the use of photovoltaic solar panels and batteries, thereby achieving optimization of base station energy consumption and efficient utilization of photovoltaic energy, and its adaptability and robustness in scenarios with varying numbers of base stations surpass the current state-of-the-art reinforcement learning algorithms.

关键词： Training Base stations Energy conservation signal processing algorithms Predictive models Transformers Prediction algorithms Batteries Solar panels Optimization

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A Noval Real Time Sleep Apnea Detection

A Noval Real Time Sleep Apnea Detection

引用

International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： S. Susila Sakthy T. P. Rani Dhoorika Anurega TR Department of Information Technology Sri Sairam Engineering College Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

Sleep apnea is a prevalent sleep disorder characterized by repetitive interruptions in breathing during sleep. Timely detection and monitoring of sleep apnea are crucial for effective diagnosis and treatment. We propose a novel approach for sleep apnea detection using Ultra-Wideband (UWB) sensor technology. The UWB sensor system offers several advantages, including high precision, low power consumption, and the ability to penetrate through different materials. By leveraging these features, we aim to develop a non-intrusive and cost-effective method to detect sleep apnea events accurately. Our research focuses on designing a wearable UWB sensor device that can be comfortably placed near the user’s sleeping area. The sensor system utilizes UWB technology to measure and analyze subtle movements and physiological signals during sleep, such as oxygen and heart rate variability. To detect sleep apnea events, we employ advanced signal processing algorithm, By extracting specific features from the UWB sensor data, we can identify the characteristic patterns associated with sleep apnea episodes. The proposed system has the potential to provide an accessible and effective solution for early detection and continuous monitoring of sleep apnea, leading to improved diagnosis, treatment, and overall patient care. Further research on creating a website for hospitals to monitor the apnea patients.

关键词： Power demand signal processing algorithms Process control Feature extraction Sleep apnea Sensor systems Real-time systems Biomedical monitoring Monitoring Ultra wideband technology

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Energy-Efficiency Resource Optimization in Internet of Vehicles

Energy-Efficiency Resource Optimization in Internet of Vehic...

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

作者： Yaxuan Zhao Haixia Cui Qikai Hao School of Electronic Information Engineering South China Normal University Guangzhou China School of intelligent Sciences National University of Defense Technology Changsha China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

With the surge in the number of in-vehicle users and the demand for high-quality in-vehicle communications, a resource optimization strategy that combines power control and channel allocation with the goal of maximizing energy efficiency is proposed to address the problem of insufficient spectrum resources and energy efficiency resources. The strategy proposes a power control algorithm with low computational complexity to address the inaccurate estimation of Channel State Information (CSI) caused by the Doppler effect and fast fading; meanwhile, to address the energy resource management problem, an improved many-to-one matching scheme is proposed to establish an objective function to maximize the energy efficiency of the Telematics system, taking into account the co-channel interference. system energy efficiency objective function. Numerical analysis shows that the strategy proposing the new joint power control and channel assignment algorithm has improved performance in energy efficiency performance compared to the traditional method.

关键词： Numerical analysis Power control signal processing algorithms Channel allocation Linear programming Telematics Energy efficiency Surges Optimization Internet of Vehicles

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Acquisition and processing of Chromatic Derivatives using FPGA-based Digital Hardware

Acquisition and Processing of Chromatic Derivatives using FP...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Zhaofeng Zhong Pathmapirian Nanthakumar Gabriel Field Chamira U. S. Edussooriya Aleksandar Ignjatovic Chamith Wijenayake School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia Department of Electronic and Telecommunication Engineering University of Moratuwa Moratuwa Sri Lanka School of Computer Science and Engineering University of New South Wales Sydney Australia

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Chromatic derivatives (CDs) and associated chromatic approximations (CAs) provide a numerically robust and powerful framework for digital processing of continuous-time/space signals, using not only the discrete signal amplitudes, but also higher order derivatives. Acquisition of CDs has so far been limited to software implementations. This paper presents field-programmable gate array (FPGA)-based digital hardware architectures suitable for the real-time acquisition of CDs, thus enabling CDs to be used for practical signal processing algorithm development in embedded systems. With 24 bits of fixed-point precision, the proposed hardware architectures provide approximate 116 dB accuracy in the frequency responses of FIR filters capturing the CDs, and 76.85 dB and 75.09 dB accuracy in signal reconstruction with synthetic and real audio signals using CDs up to order 28 degrees. The designs have been verified on an AMD Kintex UltraScale KCU105 FGPA device using bit-true cycle-accurate hardware co-simulation.

关键词： Accuracy Embedded systems Finite impulse response filters signal processing algorithms Computer architecture Hardware Software

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Enhanced Convergence Speed For DOA Estimation Utilizing Covariance-Free SBL Algorithm

Enhanced Convergence Speed For DOA Estimation Utilizing Cova...

引用

IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： Han Cao Haihong Tao Tiantian Zhong Haiyun Liao National Key Laboratory of Radar Signal Processing Xidian University Xi'an China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Sparse Bayesian learning (SBL) is widely applied in direction of arrival (DOA) estimation for its noise robustness and excellent performance. However, it involves high computational costs due to the covariance matrix inversion required in each Expectation-Maximization iteration. In this paper, we propose an efficient DOA estimation method based on Covariance-Free SBL, which converts the matrix inversion issue into a linear equation-solving problem via a diagonal estimation criterion. Then we employ the complex conjugate gradient algorithm to solve the complex symmetric linear equations, for its advantages of fast convergence, memory efficiency, and accuracy controllability. Simulation results indicate that our method significantly enhances calculation speed meanwhile maintaining estimation accuracy, especially for high grid-resolution DOA estimation.

关键词： Direction-of-arrival estimation Accuracy Symmetric matrices Estimation signal processing algorithms Approximation algorithms Computational efficiency Covariance matrices Standards Convergence

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Advancements in Crime Detection: Bridging Domain Gaps with Dual Variational Generation

Advancements in Crime Detection: Bridging Domain Gaps with D...

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IEEE International Conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Devipriya Sozharajan Riya Mittal Yash Singhvi Evany Anne M M. Brindha Computer Science and Engineering National Institute of Technology Tiruchirappalli India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376142

The objective of this project is to implement facial recognition technology on a dataset consisting of individuals from India in a heterogeneous environment. To address the absence of an Indian dataset, web scraping techniques are utilised to collect photos of players from a league’s official website. These players included both Indian and foreign nationals. Subsequently, a Dual Variational Generator is applied to the web-scraped photos to augment the training dataset. A framework of Haar Cascade and LBPR algorithm is utilised for face recognition. The combination of Haar cascades, LBPH algorithm, and DVG approach creates a robust framework for facial recognition in security applications. This framework offers a powerful blend of simplicity, efficiency, and accuracy that is specifically designed to address the issues faced in real-world deployments.

关键词： Training Accuracy Face recognition signal processing algorithms signal processing SPICE Generators Security Informatics

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DoH Detection Method Based on Self-Attention BiLSTM

DoH Detection Method Based on Self-Attention BiLSTM

引用

International Congress on Image and signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Zhaorui Deng Kui Jang Ruibin Huang Bo Wu Silin Zhu College of Electronics and Information Engineering Shenzhen University Shenzhen China Information Center Shenzhen University Shenzhen China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

DoH (DNS over HTTPS) is an encrypted DNS Protocol encapsulated in Hyper Text Transfer Protocol over SecureSocketLayer (HTTPS). It is one of the main protocols used to encrypt traffic in the domain name system. DoH plays an important role in preventing DNS hijacking and protecting user privacy, but attackers can also use DoH to establish DNS covert tunnels to achieve botnet control and other malicious behaviors. Aiming at the difficulty of classification and low accuracy in DoH detection, this paper designs a multi-classification detection method for DoH based on Self-Attention BiLSTM model. Experimental results show that the proposed method is superior to common machine learning models and traditional deep learning models in accuracy.

关键词： Training Deep learning Accuracy Bidirectional long short term memory signal processing algorithms Feature extraction Transformers HTTP Cryptography Data mining

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FPGA Design of Digital Circuits for Phonocardiogram Pre-processing Enabling Real-Time and Low-Power AI processing

FPGA Design of Digital Circuits for Phonocardiogram Pre-Proc...

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Euromicro Symposium on Digital System Design

作者： Domenico Ragusa Antonio J. Rodriguez-Almeida Marco Gazzoni Emanuele Torti Elisa Marenzi Himar Fabelo Gustavo M. Callico Francesco Leporati Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Institutc for Applied Microelectronics (IUMA) University of Las Palmas de Gran Canaria Las Palmas de G.C. Spain Fundación Canaria Instituto de Investigación Sanitaria de Canaria Las Palmas de G.C. Spain Research Unit Hospital Universitario de Gran Canaria Dr. Negrin Las Palmas de Gran Canaria Spain

ISBN: (数字)9798350380385

ISBN: (纸本)9798350380392

Cardiovascular Diseases (CVDs) stand as the leading cause of mortality worldwide. Detecting subtle heart sounds alterations in the early stages of CVDs can be crucial for an initial effective treatment. Accordingly, the analysis of Phonocardiograms (PCGs) through segmentation could be helpful for CVDs screening. A well-established algorithm for this task is based on a Convolutional Neural Network (CNN) with an encoding-decoding topology. Prior to the CNN processing., a computationally intensive input pre-processing., based on envelopes extraction, is needed. Thus., achieving real-time performance can be challenging. The main goal of this study is the hardware design., implementation, and evaluation of four PCG pre-processing circuits to be employed together in the design of a low-power point-of-care device for real-time Artificial Intelligence (AI)-based PCG segmentation. Results have shown that the approximations introduced by the fixed-point format and this innovative architecture have a negligible impact on the AI segmentation quality. Finally, the pre-processing chain is real-time compliant., achieving a maximum latency of 257 ms for an available processing window of 1.28 s., while dissipating only 61 mW of power.

关键词： Point of care signal processing algorithms Transforms Standardization Real-time systems Topology Convolutional neural networks Artificial intelligence Phonocardiography Digital circuits

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