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The Analysis of Channel Capacity in Reconfigurable intelligent Surface-Aided Wireless Communication systems 16

The Analysis of Channel Capacity in Reconfigurable Intellige...

引用

16th international conference on Wireless Communications and signal processing, WCSP 2024

作者： Zhang, Qi Wang, Zhengyu Xiong, Rujing Mi, Tiebin Qiu, Robert Caiming School of Electronic Information and Communication Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9798350390643

This work analyzes the capacity of the Reconfigurable intelligent Surface (RIS)-aided wireless communication system deploying linear RIS. We propose modeling the cascade channel with a mixed product of random Vandermonde matrices and a random diagonal matrix. A challenging problem that has yet to be addressed is the lack of a concise and accurate expression for the capacity of this channel due to the absence of spectral properties of the Vandermonde matrix. In this paper, we tackle this problem by expressing the capacity as a series expansion and obtaining the exact moment expression of the channel covariance matrix. Simulations indicate that the derived moments provide a good prediction of the true values. The approximate expression for the channel capacity, using finite terms, is simple enough to offer valuable insights and matches the simulation results well. © 2024 ieee.

关键词： Matrix algebra

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InCloud: Incremental Learning for Point Cloud Place Recognition

InCloud: Incremental Learning for Point Cloud Place Recognit...

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ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Knights, Joshua Moghadam, Peyman Ramezani, Milad Sridharan, Sridha Fookes, Clinton CSIRO Robot & Autonomous Syst DATA61 Brisbane Qld 4069 Australia Queensland Univ Technol Res Program Signal Proc Artificial Intelligence & Brisbane Qld Australia

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Place recognition is a fundamental component of robotics, and has seen tremendous improvements through the use of deep learning models in recent years. Networks can experience significant drops in performance when deployed in unseen or highly dynamic environments, and require additional training on the collected data. However naively fine-tuning on new training distributions can cause severe degradation of performance on previously visited domains, a phenomenon known as catastrophic forgetting. In this paper we address the problem of incremental learning for point cloud place recognition and introduce InCloud, a structure-aware distillation-based approach which preserves the higher-order structure of the network's embedding space. We introduce several challenging new benchmarks on four popular and large-scale LiDAR datasets (Oxford, MulRan, In-house and KITTI) showing broad improvements in point cloud place recognition performance over a variety of network architectures. To the best of our knowledge, this work is the first to effectively apply incremental learning for point cloud place recognition. Data pre-processing, training and evaluation code for this paper can be found at https://***/csiro-robotics/InCloud.

关键词： Point cloud compression Training Degradation Deep learning Laser radar Codes Network architecture

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Channel Estimation and User Localization Assisted by Hybrid RIS with 1-Bit ADCs in MIMO systems 2

Channel Estimation and User Localization Assisted by Hybrid ...

引用

2nd ieee international conference on signal, Information and Data processing, ICSIDP 2024

作者： Liu, Xinyue Li, Jie Xi, Feng Nanjing University of Science and Technology Department of Electronic Engineering Nanjing China

ISBN: (纸本)9798331515669

This paper investigates the deployment of Hybrid Reconfigurable intelligent Surfaces (HRIS) equipped with analog-to-digital converters (ADCs) with one-bit quantization in multiple-input multiple-output systems to address the inherent limitations of passive elements in traditional RIS. The integration of one-bit ADCs into the HRIS simplifies the system architecture while reducing both cost and energy consumption. For channel estimation and user localization, we jointly leverage the one-bit data received at the HRIS and the reflected signals at the Base Station (BS). The atomic norm minimization method is utilized to substantially enhance the accuracy of channel estimation, while Vandermonde decomposition of a two-level Toeplitz matrix is applied to derive the Angle of Arrival (AoA) information of the User Terminals (UTs). To further optimize the HRIS configuration, we develop a Cramér-Rao Bound-based algorithm. Our simulation results show that the method we propose can improve the performance of both channel estimation and user localization. © 2024 ieee.

关键词： Cramer-Rao bounds

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Presenting a Method for Gluing Error Detection Using Image processing 10

Presenting a Method for Gluing Error Detection Using Image P...

引用

10th international conference on signal processing and intelligent systems, ICSPIS 2024

作者： Shishebor, Moein Derhami, Vali Khouri, Masoud Yazd University Computer Engineering Department Yazd Iran

ISBN: (纸本)9798331532543

The application of artificial intelligence and image processing for automatic fault detection in industrial settings holds substantial significance. However, image processing systems encounter challenges in achieving accurate automatic detection, including variable lighting conditions, low image quality, and the complexity of observed objects. This study specifically addresses the detection of gluing errors in automotive parts. An improved template matching algorithm is employed to identify boundary errors. The proposed method incorporates SIFT (Scale-Invariant Feature Transform) for feature extraction, allowing for the identification of key local features in images regardless of changes in scale, rotation, or lighting conditions. To address variations in scale and alignment, affine transformations are employed to standardize the images, ensuring consistent dimensions and orientations. After this preprocessing step, brute-force matching techniques are utilized to accurately match the extracted features from the modified images with a target reference, refining the output and enhancing the detection accuracy of improperly glued areas. Results from executing the algorithm on input images demonstrate the high performance of the proposed method in gluing error detection. © 2024 ieee.

关键词： Affine transforms

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Image Segmentation Algorithm of Ischemic Stroke based on Wavelet Pooling Neural Network 2

Image Segmentation Algorithm of Ischemic Stroke based on Wav...

引用

2nd ieee international conference on signal, Information and Data processing, ICSIDP 2024

作者： Zhu, Huiyuan Zhai, Yao Wu, Jinghe Lu, Chuwei Zhang, Xianchao Li, Ruide Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China College of Medicine Jiaxing University Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Department of Nursing Jiaxing China Beijing Institute of Technology School of Information and Electronics Beijing China Aviation Industry Corporation of China Avic Xi' An Flight Automatic Control Research Institute Xi'an China Jiaxing University Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Jiaxing China

ISBN: (纸本)9798331515669

Ischemic stroke is a high-risk brain disease that causes disability or death in adults worldwide. Rapid diagnosis and treatment, as well as segmentation of ischemic lesions from stroke medical images so that doctors can evaluate and develop treatment plans, are crucial to reducing brain damage. Currently, doctors' manual segmentation of lesions is time-consuming and labor-intensive and prone to missed or misdiagnosed diagnoses, delaying the best time for treatment. A well-trained neural network is considered as an effective aid for image segmentation tasks. However, in the traditional neural network down-sampling process, the pooling layer loses feature information, and the lost information significantly impacts the edge regions. While for medical images, edge regions are crucial features in the segmentation process. Therefore, to address the above issues, in this paper we improve upon the existing stroke lesion segmentation algorithm U-net, we design a segmentation network based on wavelet pooling and attention mechanisms. The network was tested on ISLES 2018 and ISLES 2022 datasets, and the Dice coefficient improved by 2.13% and 1.93% compared to baseline network, respectively. © 2024 ieee.

关键词： Image segmentation

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Machine Learning for signal processing in Communication systems

Machine Learning for Signal Processing in Communication Syst...

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2024 international conference on Innovative Computing, intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Reddy, PoliLokeshwara Shreyas, Chanda Bhargavi, Pamulapati. Raja, G.V. Rani, D. Leela Maheswari, S. Anurag University Department of Electronics and Communication Engineering Telangana Hyderabad500088 India Kkr & Ksr Institute of Technology and Sciences Department of Computer Science Engineering Andhra Pradesh Guntur522017 India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Karnataka Bengaluru562106 India Mohan Babu University Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Kongu Engineering College Department of Electrical and Electronic Engineering Tamil Nadu Perundurai638060 India

ISBN: (纸本)9798331543617

The traditional styles of signal processing are passing constraints in their capability to handle the different and dynamic character of ultramodern data transfers. This is because communication systems are getting increasingly complicated. The operation of machine literacy presents a potentially useful answer since it enables data-driven, adaptive approaches that have the eventuality to ameliorate signal processing performance. This composition provides a comprehensive examination of a variety of machine literacy ways and their operations in important disciplines such as modulation recognition, noise reduction, channel estimation, and signal discovery. The study demonstrates how machine literacy ways may vastly increase the effectiveness, delicacy, and robustness of signal-processing tasks in communication systems. This is fulfilled through detailed analysis and comparison. With the help of machine literacy, unborn communication systems will be suitable to attain advanced situations of robotization and intelligence, which will pave the way for further developments in areas similar to wireless dispatches, the Internet of Effects(IoT), and other areas. In light of these findings, it's clear that machine literacy can fully transfigure assiduity by furnishing new shoes and approaches to the optimization of signal processing in the unborn generation of communication networks. © 2024 ieee.

关键词： Noise abatement

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Performance Analysis of STAR-RIS Assisted UWOC-RF systems with NOMA 9

Performance Analysis of STAR-RIS Assisted UWOC-RF Systems wi...

引用

9th international conference on intelligent Computing and signal processing, ICSP 2024

作者： Song, Jize Liu, Xin Luo, Wenwei Zhang, Jiliang Southwest University School of Electronic and Information Engineering Chongqing China

ISBN: (纸本)9798350376548

Simultaneously transmitting and reflecting recon- figurable intelligent surface (STAR-RIS) can enable signals' transmitting and reflecting simultaneously to result in a full-space 360° coverage. Therefore, in this analysis, we investigate a STAR-RIS assisted dual-hop mixed underwater wireless optical communication radio frequency system with non-orthogonal multiple access (NOMA). In particular, a submerged transmitter sends a superimposed signal to an above-water relay, which initially employs either heterodyne detection or intensity modulation direct detection technique to process the received signal and then reformats the NOMA signal and forwards it to two land-based NOMA users via a STAR-RIS. Assuming the UWOC channel experiences a mixture Exponential-Generalizead Gamma distribution and the RF channels undergo the Nakagami-m fading, the closed-form expressions of outage probability are presented using the Meijer's G-function and the series of Laguerre polynomials. Furthermore, some system parameters, i.e., the underwater metrics, the number of the STAR-RIS elements, and the power allocation factor, on the system performance are also investigated. Monte-Carlo simulations confirm the accuracy of these expressions. © 2024 ieee.

关键词： Heterodyne detection

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A Detailed Analysis of Secrecy and Performance Metrics in Hybrid RF/ FSO Communication systems: Implications of Composite Weibull and Log-normal Fading with M Turbulent Channels

A Detailed Analysis of Secrecy and Performance Metrics in Hy...

引用

2024 ieee international conference on intelligent signal processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

In this paper, we have analyzed the secrecy performance and system operation performance for hybrid RF/FSO systems against composite Weibull-log-normal fading channel with M turbulent channels. The performance is evaluated by carrying out extensive simulations to calculate signal-to-Noise Ratio (SNR), Bit Error Rate (BER) and outage probability, we also re-evaluate channel capacity and secrecy capacity with respect of environmental conditions. Compared with RF only system, FSO only standalone scheme and some meaningful orthogonal-modulation multicarrier IM/DD-based schemes proposed by the literatures. Similarly, the utilization of adaptive modulation schemes improved resistance to fading and roughness in systems. The above results confirm the hybridization of both RF and FSO a comprehensive solution for dependable communication in different and even hostile surrounding conditions which set this work as reliable foundation point towards forthcoming research activity or application relevance within all range telecommunication sector. © 2024 ieee.

关键词： Bit error rate

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Design and Implementation of Shenyang Event Venue Reservation System Based on intelligent Computing 2

Design and Implementation of Shenyang Event Venue Reservatio...

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2nd international conference on signal processing and intelligent Computing, SPIC 2024

作者： Xu, Xiaoyang Yang, Li Li, Chengyu Shenyang Ligong University College of Equipment Engineering Shenyang China

ISBN: (纸本)9798350368888

As all walks of life gradually return to normal, various event venues in Shenyang are both full and idle. In order to make full and effective use of venue resources, event venue booking is particularly important. This paper designs a Shenyang event venue reservation system based on intelligent computing. The design process mainly includes the user front-end interface design. The system is developed using Eclipse tools, using three major frameworks: intelligent Computing, Spring MVC and MyBatis. MySQL is used in the background for data management, and Java Web is used for coding. This system uses user learning to push personalized venue reservation plans, saving users time in selecting and arranging venues, and has practical significance. The methods used in the design process and the conclusions drawn have certain guiding significance for the practical application of the intelligent computing framework. © 2024 ieee.

关键词： Reservation systems

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Small Object Vehicle Detection Based on Improved YOLOv5 9

Small Object Vehicle Detection Based on Improved YOLOv5

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9th international conference on intelligent Computing and signal processing, ICSP 2024

作者： Li, Yongsong Kong, Bin Yu, Weiwei Jiang, Jinhui Institute of Material Science and Information Technology Anhui university Hefei China Institute of Intelligent Machines Chinese Academy of Sciences Hefei China School of Mechanical Engineering Chongqing Three Gorges University Chongqing China

ISBN: (纸本)9798350376548

With the advent of deep learning, object detection has been extensively utilized in intelligent transportation systems. However, the performance of baseline object detection models in traffic scenes is suboptimal, particularly for small object detection. To address this issue, this paper introduces an improved method for small object detection in traffic scenes based on YOLOv5, designated as YOLOv5-CBS. Initially, the convolutional modules of the model network are replaced to enhance the capability of feature extraction. Subsequently, an attention mechanism is incorporated into the Neck section of the model network, which bolsters the network's ability to capture contextual information through bidirectional encoding and decoding. Additionally, the imbalance between simple and challenging samples is mitigated by introducing a weighting function, Slide, into the model's loss function. Experimental results on the SODA10M dataset demonstrate that YOLOv5-CBS achieves average detection accuracies of 64.3% for mAP@0.5, 46.3% for mAP@0.5:0.95, and 16.2% for small object detection, representing improvements of 4.3%, 7.8%, and 2.1% over YOLOv5, respectively. © 2024 ieee.

关键词： intelligent systems

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