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检索条件"任意字段=Conference on Advanced Signal Processing Algorithms"

共 3499 条记录，以下是681-690 订阅

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Decision-Directed Channel Equalizer Scheme Based on the Recursive Non Quadratic Adaptive Algorithm

Decision-Directed Channel Equalizer Scheme Based on the Recu...

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Advances in Electronics, Control and Communication Systems (ICAECCS), International conference on

作者： Fatima Lounoughi Mohamed Djendi Electronic dept Signal Processing and Image Laboratory (LATSI) Saad Dahleb University Blida Alegria

This paper presents a new adaptive decision directed equalizer (DDE) for the receivers of advanced Wireless communication systems. The proposed approach is based on the use of a recursive non quadratic (RNQ) adaptive algorithm in a DDE system with a training sequence, the new algorithm is denoted DDE-RNQ. The proposed DDE-RNQ equalizer achieves better performances in different situations even when strong noise components are present in the channel. In the proposed DDERNQ, the non quadratic distance criterion between the equalizer output and the decision circuit is used rather than the squared mean square error (MSE) distance for the computation of the branch metrics. Compared to the conventional DDE based normalized least mean square (DDE-NLMS) equalizer, the proposed DDE-RNQ shows superior performances of speed convergence and residual error versus the original DDE-NLMS equalizer in terms of MSE.

关键词： Training Wireless communication Adaptive systems Equalizers Adaptive algorithms Symbols Modulation

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Big data acquisition and processing platform for embedded prognostics of the ultrasonic motor 2

Big data acquisition and processing platform for embedded pr...

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2nd International conference on Big Data Mining and Information Processes, BDMIP 2021

作者： Qin, Taichun Li, Dan Li, Peng Huang, Shouqing Dai, Wei Beijing Key Laboratory of Environment and Reliability Test Technology for Aerospace Mechanical and Electrical Products Beijing Institute of Spacecraft Environment Engineering Beijing100094 China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing100094 China University of Chinese Academy of Sciences Beijing100049 China

To ensure reliability and safety, embedded prognostics are essential for ultrasonic motor, which is a key component of spacecraft. Although many big-data algorithms have been proposed for prognostics and health management (PHM), no suitable embedded prognostic platform is found for the ultrasonic motor. In this paper, a big data acquisition and processing platform is proposed. The platform is composed of a high-speed signal acquisition board, an edge computing module and a display screen. As the key part, the high-speed signal acquisition board is discussed in detail. Moreover, this platform has been tested with an ultrasonic motor. The results show that the acquired waveform is quite clear, which indicates this platform can successfully be used for prognostics of ultrasonic motors. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Big data

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Research on Unmanned Aircraft Environment Perception Methods in Urban Low Altitude Complex Backgrounds 23

Research on Unmanned Aircraft Environment Perception Methods...

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Proceedings of the 4th International conference on Artificial Intelligence and Computer Engineering

作者： Jinyi Qu Wenping Gao Haoyu Wang Daquan Huang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China China

ISBN: (纸本)9798400708831

With the continuous development of drone-related technologies, the application of UAV (Unmanned Aerial Vehicle) in urban low-altitude scenes is gradually increasing. Autonomous localization and perception of the surrounding environment are prerequisites for autonomous control. As a result, our team apply the VDO-SLAM algorithm to the scene of coexistence of dynamic and static obstacles in the complex background of urban low altitude. Effective segmentation of static background and moving objects is achieved by combining semantic segmentation and optical flow estimation algorithms. Since there is a lack of relevant public data for urban low-altitude scenarios, a binocular image dataset containing both static and dynamic objects is created by Airsim simulator, which is utilized for training a semantic segmentation model. In addition, a novel numbering maintenance algorithm is introduced for the semantic segmentation of continuous image sequences. The experimental results show that the algorithm can realize the autonomous perception of UAV posture and the motion state of dynamic objects in low altitude complex urban environment. This method provides the necessary self-pose information and reliable environmental data for autonomous obstacle avoidance of UAVs, and provides important support for the application of UAVs in urban low-altitude environment.

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Noise and performance analysis on fundus images with CNN and transformer models

Noise and performance analysis on fundus images with CNN and...

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conference on Information and Communication Technology (CICT)

作者： Niranjana Vannadil Priyanka Kokil Department of Electronics and Communication Engineering Advanced Signal and Image Processing (ASIP) Lab Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai

Fundus imaging is a valuable diagnostic tool in ophthalmology, providing clinicians with detailed visualizations of the retina and aiding in the detection and monitoring of various eye diseases, including age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and cataract. However, the quality of fundus images can be significantly affected by noise, mainly additive white Gaussian noise (AWGN), which is inherent in many imaging systems. The presence of noise in real-world data poses significant challenges for computer vision tasks. In the field of medical image classification, a wrong diagnoisis has heavy consequences. Understanding the impact of AWGN on fundus images is crucial for developing practical denoising algorithms and improving diagnostic accuracy. This work presents an analysis of AWGN noise in fundus images aims to characterize its effects on image quality and assess its impact on diagnostic tasks. The work also analyzes the performance of six models (3 each) of two popular deep learning architectures, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) in the presence of AWGN. AWGN is first introduced to the clean image datasets to conduct the analysis. The CNN and ViT models are trained on the noisy datasets to evaluate the performance of the image classification task. The work also involves six denoising algorithms and a popular image enhancement algorithm- Contrast Limited Adaptive Histogram Equalization (CLAHE).

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Ultra-stable and Low-complexity Retiming Technique for Bandwidth-limited 112-Gbps PAM-4 systems

Ultra-stable and Low-complexity Retiming Technique for Bandw...

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Optoelectronics Global conference (OGC)

作者： Lin Sun Luxiao Zhang Yi Cai Gangxiang Shen Gordon Ning Liu Bin Chen Suzhou Key Laboratory of Advanced Optical Communication Network Technology Soochow University Suzhou China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

We proposed an improved retiming algorithm for optical PAM-4 system by introducing a moving average filter into the conventional Gardner loop. It exhibits an enhanced stability especially when system bandwidth is limi... 详细信息

ISBN: (纸本)9781665486996

关键词： Optical filters Timing jitter signal processing algorithms Bandwidth Filtering algorithms Real-time systems Field programmable gate arrays

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Traffic signal recognition using YOLO, a comparative analysis

Traffic signal recognition using YOLO, a comparative analysi...

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International conference on Image Information processing

作者： Ashish Kumar Dogra Vipal Sharma Harsh Sohal Computer Science Engineering/IT JUIT Solan India Electronic and communication Engineering JUIT Solan India

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371413

The identification of traffic signs is a major challenge for intelligent automobiles. Recognition of traffic signs gives useful data, such as alerts and directions, for cooperative intelligent transport systems (CITS) and advanced driver assistance systems (ADAS). In realistic autonomous driving scenarios, traffic signs can be challenging to identify even with a very precise real-time method. As a result, drivers are calling for more secure and trustworthy traffic sign recognition technology, and current automakers are also working on developing one. All images captured by the actual driving car are blurry and distorted. The study of traffic sign recognition systems faces several challenges due to external, unmanageable components, such as the impact of unfavorable conditions, and the practical use is still in its infancy. This study provides the YOLO model for traffic sign identification as a solution for the issues mentioned above. The first step is to generally arrange the traffic signs into various categories. Next, the prepossessing process then follows the characteristics of the different kinds of signs. The improved convolution neural network receives the altered images and breaks down the categories into more specific subcategories. The YOLOv3-tiny and YOLOv4-tiny algorithms are examined by using the CCTSDB dataset and the Tsinghua-Tecent 100k(TTK100) dataset and YOLOv2,YOLOv3 andYOLOv5 are examined using the CCTSDB and HRRSD(High Resolution Remote Sensing Detection) datasets depending on the various categories. The findings indicate that YOLOv4-tiny algorithm achieves good recognition performance on both TTK100 and CCTSDB datasets and YOLOv5 on both CCTSDB and HRRSD dataset are most suited for use in traffic sign recognition systems and has a high classification accuracy.

关键词： YOLO Image resolution Neural networks Information processing Real-time systems Classification algorithms Automobiles

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Application of optical sensor array in partial discharge signal location of GIS/GIL 5

Application of optical sensor array in partial discharge sig...

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2021 5th International Workshop on advanced algorithms and Control Engineering, IWAACE 2021

作者： Shiling, Zhang State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing401123 China

The optical sensor array inside the high-voltage equipment can effectively realize the on-line measurement of the high-voltage switch operation state, significantly improve the efficiency and accuracy of SF6 Electrical equipment fault diagnosis, and effectively guarantee the safety and reliability of equipment operation. Firstly, the structure and performance of the micro optical sensor are analyzed, and the system model and data processing unit of the optical sensor array are given. Furthermore, the influence characteristics of single sensor and array sensor Gaussian noise on signal are given, and the noise elimination strategy of observation signal based on Kalman filter is given. The results show that: the optical sensor has a good focusing ability for the optical signal, the light of the sensor array is reflected and propagated many times in the GIS/GIL of the high voltage switch-gear, and the internal partial discharge signal is located more accurately. The research results of this paper can provide important technical support for the GIS/GIL fault monitoring and early warning of the gas insulated electrical equipment on the transmission line. © Published under licence by IOP Publishing Ltd.

关键词： Gaussian noise (electronic)

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Retinal OCT Image Denoising Based on Adaptive Bessel K-form Modeling

Retinal OCT Image Denoising Based on Adaptive Bessel K-form ...

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Iranian conference of Biomedical Engineering (ICBME)

作者： Sahar Jorjandi Zahra Amini Maryam Samieinasab Hossein Rabbani Department of Bioelectrics and Biomedical Engineering School of Advanced Technologies in Medicine Student Research Committee Isfahan University of Medical Sciences Isfahan Iran Medical Image & Signal Processing Research Center School of Advanced Technologies in Medicine Isfahan University of Medical Sciences Isfahan Iran Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA

In this study, an adaptive approach is addressed to reduce the noise of retinal Optical Coherence Tomography (OCT) images. Since the layered structure of retinal OCT images creates a dependency between adjacent pixels at particular distances, the presented method is based on the adaptive selection of variable neighborhood windows for each pixel of OCT images. Indeed, by defining this spatial adaptivity, we extend our earlier work in which a pixel-wise fixed window was considered. Here, the variance is calculated in an optimal window for each pixel; so that the ultimate distribution of the variance image follows a gamma model. Besides, the asymmetry observed in the distribution of retinal layers led to suggest Asymmetric Bessel K-form (ABKF). This model is easily transformed into a Gaussian distribution through dividing the image into the root of the variance image. Then, it can be used with Gaussian-based algorithms for OCT denoising application. The results show the impressive performance of the proposed adaptive local BKF model in noise reduction and increasing image contrast as visual and quantitative criteria.

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Performance Comparison of Sparse Multipath Channel Estimation Models for B5G Network 3

Performance Comparison of Sparse Multipath Channel Estimatio...

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3rd IEEE International Virtual conference on Innovations in Power and advanced Computing Technologies, i-PACT 2021

作者： Kumar, K. Vijaya Bhattacharyya, Budhaditya School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9781665426916

Any OFDM-based wireless communication receiver relies on channel estimation. Across a wireless multipath fading channel, there is a growing need for high-data-rate communication, which typically demands previous channel knowledge at the receiver. The OFDM system is the multicarrier transmission technology, permits the transmission of wireless signals at high data rates. Onto the channel estimate, the OFDM plays a major role;and more researches have been focused on the development of new channel estimation methods for successful signal detection over time. In this research work, a compact review is undergone of the different algorithms adopted for channel estimation in OFDM. Here, 20 recent papers are collected from different journals that have been framed during different years (2018 to 2021). In addition, the features and challenges of each of the collected research papers on channel estimation in OFDM are manifested in order to grab more worthy information about the research. In addition, the recorded performance of the collected research papers is portrayed, and this might aid the researchers, who attempt to develop hybrid techniques using the conventional models. Ultimately, the research gaps identified in the different channel estimation models in OFDM are manifested to guide future researchers in developing and organizing the new intelligent channel estimation models. © 2021 IEEE.

关键词： Digital signal processing

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Slice Freshness Guaranteed Resource Allocation in Vehicular Networks

Slice Freshness Guaranteed Resource Allocation in Vehicular ...

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International conference on Wireless Communications and signal processing (WCSP)

作者： Yaping Cui Xisheng Yang Peng He Ruyan Wang Dapeng Wu School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China Chongqing China Chongqing Key Laboratory of Ubiquitous Sensing and Networking Chongqing China

ISBN: (纸本)9781665450867

Network slicing is becoming an effective solution to meet the heterogeneous quality of service (QoS) requirements in internet of vehicles (IoV). Caused by these, the coupling effect of intra- and inter-slice resource allocation have brought great challenges to *** this end, the intra- and inter-slice resource allocation problems are formulated as hierarchical optimization problem. Further, we propose an one leader and two followers resource allocation (OL-TFRA) algorithm based on Stackelberg game. Firstly, the bandwidth ratio of eMBB slice is determined by the bisection method, then the optimal strategy of inter-slice resource allocation is derived through the leader-follower game. The algorithm identifies the existence and uniqueness of the Stackelberg equilibrium, and takes the equilibrium point as the optimal result of inter- and intra-slice resource allocation. Simulation results reveal the interaction of different slices per-formance. Compared with the exhaustive search algorithm, the proposed algorithm converges faster than the exhaustive search algorithm with 2% utility decreases.

关键词： Couplings Wireless communication Network slicing Simulation Data integrity signal processing algorithms Games

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