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6G XL-MIMO Channel Estimation with Sub-Nyquist Tensor Completion

6G XL-MIMO Channel Estimation with Sub-Nyquist Tensor Comple...

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Digital signal Processing and its Applications (DSPA), international conference on

作者： Semyon Dorokhin Vladimir Lyashev Mikhail Makurin Moscow Institute of Physics and Technology Moscow Russia Radio Transmission Technology Lab Moscow Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

Channel estimation overhead reduction is one of the main problems for 6G XL-MIMO systems. As the number of antennas and subcarriers grows, so does the overhead of traditional channel estimation methods. High overhead limits user mobility and affects the latency. Most of the popular tensor-based channel estimation algorithms combine reference signals transmission and channel tensor estimation into one problem. Such approach typically imposes limitations on reference signals, making backward-compatibility with existing 5G standard challenging. We propose to separate tensor completion and channel tensor elements estimation into different tasks. We show that tensor completion algorithms from image processing and fMRI scanning can be reused for sub-Nyquist completion of OFDM MIMO tensors to reduce the overhead. Furthermore, we extend one of these algorithms from CPD to Tensor Train (TT) and demonstrate that TT-based algorithm reduces channel estimation error up to 2 times. With the proposed approach other algorithms can be further developed based on tensor completion theory.

关键词： 6G mobile communication Tensors OFDM image processing Channel estimation signal processing algorithms Estimation Massive MIMO Functional magnetic resonance imaging Standards

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Implementation of English Translator Speech Recognition System Function

Implementation of English Translator Speech Recognition Syst...

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Artificial Intelligence and Autonomous Robot systems (AIARS), international conference on

作者： Xiaodong Sun Xiyang Sun Qiang Cui School of Foreign Languages Dalian University of Science and Technology Dalian Liaoning China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

As a complex technology, speech recognition has entered the stage of large-scale application after more than half a century of development, but there are still challenges such as low recognition rate and slow recognition speed. In view of these problems, this paper delves into the algorithms of speech signal preprocessing, framing and windowing, endpoint detection and feature extraction, and constructs an English translator speech recognition system. The development status of speech recognition technology, as well as some new methods based on deep learning and neural networks, are introduced in related work. In the method part, this paper proposes a four-module language recognition system, including a recognition module, a front-end module, an acoustic module and an execution module, and describes in detail the process of speech sampling and preprocessing. This paper uses the feature extraction method to extract the voice data of the Common Voice open source database, builds an English translator, adopts pattern recognition and automated control methods, and controls it through the internet and the internet of Things to realize the network modular design of the English translator and improve the integration capabilities of the English translator.

关键词： Training Deep learning Databases Neural networks Speech recognition Feature extraction Software internet of Things Data mining Speech processing

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Research on signal Modulation Type Recognition based on Cyclic Spectrum in internet of Things 6

Research on Signal Modulation Type Recognition Based on Cycl...

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6th international conference on signal and image Processing, ICSIP 2021

作者： Li, Hongfa Liao, Ye State Grid Fujian Electric Power Company China Fujian350000 China

ISBN: (纸本)9780738133737

Identifying signal modulation type in the perception supervision mechanism in the power internet of Things environment is the primary content. Because the wireless communication channel environment is complex and challenging to predict, especially in substantial noise interference, many parameter estimations and modulation type identification methods are challenging to achieve the desired accuracy. In this paper, based on the apparent differences between the cyclic spectrum of different modulation types, related features are extracted. Some recognition techniques are used to distinguish these features. The identification of signal modulation based on the cyclic spectrum has the characteristics of strong anti-interference ability. It can also be applied well in the case of a low signal-to-noise ratio. © 2021 IEEE.

关键词： internet of things

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RF MEMS switch with double-clamp and wafer level package with through silicon vias for integration RF MEMS in applications 5G and internet of Things 14

RF MEMS switch with double-clamp and wafer level package wit...

引用

14th international conference on Micro- and Nano-Electronics 2021, ICMNE 2021

作者： Tkachenko, Alexey V. Lysenko, Igor E. Kovalev, Andrey V. Southern Federal University Rostov-on-Don region Taganrog347922 Russia

ISBN: (数字)9781510651913

ISBN: (纸本)9781510651906

Reducing the complexity of the architecture of radio-frequency systems and subsystems of 5G mobile networks and internet of Things currently requires the presence of passive RF components with very high performance. Considering these requirements, the technology of radio-frequency microelectromechanical systems for the development of passive RF devices allows us to solve the corresponding tasks related to the requirements of 5G and internet of Things, concerning passive components and building blocks. Packaging of radio-frequency microelectromechanical systems and other passive components is a delicate issue, especially in line with future application contexts such as 5G and the internet of Things, in which operating frequencies are approaching millimeter waves. In fact, when working with radio-frequency signals, the package, in addition to protecting encapsulated devices, should also have as limited an impact on their electromagnetic characteristics and performance as possible. Therefore, the packaging design stage must be carried out with extreme care. In this study, the verification of the methodology for electromagnetic modeling of a packaging solution at the wafer-level using through silicon vias for redistributing an electrical signal from passive radio-frequency microelectromechanical devices in package to other radio-frequency devices is discussed using the example of the developed capacitive radio-frequency microelectromechanical switch with double-clamp. © 2022 SPIE.

关键词： MEMS

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Distributed Honey pot based on Block chain

Distributed Honey pot Based on Block chain

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international conference on Communications and signal Processing

作者： S Vinod C Pandi S Sheik Dhanveer Hussain C Pavithran M Arjun Sathish R S Tejas Department of CSE Vel Tech Multi Tech Dr. Rangarajan Dr.Sakunthala Engineering College Avadi Chennai India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Proactive protection policies must be activated in order to protect our networks, systems, and data assets. On the internet, millions of individuals as well as bots are waiting to attack vulnerable systems. Honeypot technology is a useful tool for attracting attackers and draining their resources. In contrast, the traditional static honeypot can be easily recognized thanks to anti-honeypot technology. By instance, most dynamic honeypots can imitate the real system in real time and let users engage with a surreptitious invader. The project’s goal is to use the Blockchain technology to store port access data on a private chain and decentralize our system. With information that needs to be protected, many organizations and institutions have real-time cyber concerns that can be addressed by the system that is being built. Numerous uses of the blockchain already exist in other cyberspaces, such as cryptocurrency, etc. Numerous researchers are utilizing it to address a range of other data security-related issues.

关键词： Productivity Organizations Machine learning signal processing Information age Real-time systems Blockchains

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SSFEN: SELF-SUPERVISED FEATURE EXTRACTION NETWORK FOR INTERRUPTED-SAMPLING REPEATER JAMMING SUPPRESSION

SSFEN: SELF-SUPERVISED FEATURE EXTRACTION NETWORK FOR INTERR...

引用

IET international Radar conference 2023, IRC 2023

作者： Ji, Tengwei Wu, Zhenhua Cao, Yice Xu, Jiafei Cui, Jinxin Zhang, Lei Yang, Lixia Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China East China Research Institute of Electronic Engineering Hefei230031 China School of Electronics and Communication Engineering Sun Yet-Sen University Guangzhou510006 China

ISBN: (纸本)9781839539954

Interrupted-sampling repeater jamming (ISRJ), a form of main-lobe deception jamming, presents a significant obstacle for radar systems. Traditional anti-jamming techniques typically require the estimation of jamming parameters, which can introduce the potential for information loss regarding the target. In addition, methods based on convolutional neural networks (CNN) require a substantial amount of manually labeled data for training in order to achieve satisfactory results. However, obtaining a significant amount of labeled data in the radar domain poses a challenge. For the above problems, this article proposes a self-supervised feature extraction network (SSFEN) for jamming suppression. Localization and suppression of jamming is then formulated as a image processing problem and solved utilizing the classical GrabCut algorithm. In this approach, First, utilize the Short-Time Fourier Transform (STFT) to convert the one-dimensional signals into two-dimensional time-frequency representation. Next, employ the SSFEN to locate jamming and generate a mask. Finally, suppress the jamming by using the mask. © The Institution of Engineering & technology 2023.

关键词： ANTI-ISRJ RADAR signal SELF-SUPERVISED VISION TRANSFORMER

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Research on Network Security Protection technology based on Honeypot technology

Research on Network Security Protection Technology Based on ...

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image Processing and Computer Applications (ICIPCA), IEEE international conference on

作者： Yulong Cheng Yuchuan Tao Shijie Zhao Yujie Shi Lan Cui Xuesong Bai Zhaoqing Liang Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

In this era of rapid development of information technology, more and more industries are beginning to use information systems to improve the efficiency of their own industries. Websites exposed to the internet are also springing up like mushrooms after a rain, showing a trend of prosperity and rapid development. While informatization brings convenience to people, the risk of being attacked is also increasing day by day. In the face of possible threats, most website builders still stick to the traditional model of protection. That is, preparing protective software and passively wait for network attacks to be protected. However, as technology is constantly updated, attack methods are becoming more and more diverse. In the face of endless attack methods, just using protection software to passively protect is no longer able to fully adapt to complex network attack scenarios. This article attempts to perform protection operations from a new angle and compares it with the traditional passive protection mode to provide a new reference for network security protection in all walks of life.

关键词： Industries Costs Rain Face recognition Network security Market research Software internet Recording Protection

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The Study of Fashion Style Classification: Harajuku-type Kawaii and Street Fashion

The Study of Fashion Style Classification: Harajuku-type Kaw...

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international IEEE conference on signal-image Technologies and internet-based System

作者： Poonyawat Woottisart Peeraya Sripian Kejkaew Thanasuan Department of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand Innovative Global Program Shibaura Institute of Technology Tokyo Japan Media Technology King Mongkut’s University of Technology Thonburi Bangkok Thailand

This work provides a comparison among four fashion image classification models, which are a random forest classification method, a convolutional neural network (CNN), a CNN model trained with preprocessed images that a human head and face are removed, and a CNN model trained with images that a head, face, and background are removed. We are interested in three fashion categories, including Harajuku kawaii style, Thai street style, and European street fashion styles. We retrieved images from Google images, and adopted various preprocessing techniques, which were human detection, clothing segmentation, landmark detection, and colorfulness matrix to locate humans and clothes, and extract fashion features. We grouped the images into 2 classes, which were Harajuku kawaii fashion and other street fashion styles. Results showed that the accuracy score from the CNN model without cropping and background removing process was greater than the others. However, when we validated the models using the fashion dataset that was evaluated by fashion experts, the result indicated that the performance of the CNN model trained with the head-cropped image dataset was greater than the others. We concluded that the deep learning model trained with the head-cropped dataset achieved better results because it learned only clothing features, which are the most significant information in the fashion domain.

关键词： image segmentation Clothing Neural networks Europe Predictive models Feature extraction internet

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Home Security Voice based Alert System using IoT

Home Security Voice based Alert System using IoT

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Smart Electronics and Communication (ICOSEC), international conference on

作者： P. Pandiaraja R Venkatramani R. Arunraj P Rajesh Kanna G Mahendran T. Suresh Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Chennai Department of Computer Science and Engineering M. Kumarasamy College of Engineering Thalavapalayam Karur Tamilnadu India Department of Information Technology K. Ramakrishnan college of Engineering Samayapuram Tamil Nadu India Department of Computer Science and Engineering Bannari Amman Institute of Technology Erode Tamil Nadu India Department of AIML K. Ramakrishnan college of Engineering Samayapuram Tamilnadu India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Every home has an issue, such as the inability to determine if a gas leak is occurring or not. Similarly, when a water storage tank overflows, we are unable to determine the level of the condition until it causes a spill. An existing system is employed to address this issue; however, it has a low level of attentiveness, making it difficult for users to correctly identify the problem. To solve all of these issues in every home, we have developed a voice-based internet of Things device. This instrument’s voice-based output enables the user to readily understand the situation. When a gas leak occurs, a gas detector that can identify LPG gas sends a signal to a microcontroller, which then sends the signal to a voice bank to generate a speech-based warning message. Additionally, it comes into touch with water when the water is expected to flow out, sends a signal to the Arduino, and produces a voice-based output. This will cut down significantly on accidents and product waste.

关键词： Electric potential Water storage Microcontrollers Instruments Alarm systems Safety Maintenance internet of Things Gas detectors Accidents

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Video Encryption Using Optimization Lightweight Algorithm for Secure internet of Things

Video Encryption Using Optimization Lightweight Algorithm fo...

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international conference on Data Analytics and Insights, ICDAI 2023

作者： Nayak, Manoja Kumar Dash, Dinesh Kumar Swain, Prasanta Kumar Sahu, Abhimanyu Department of Computer Application MSCB University Baripada India Department of ETCE PMEC Berhampur Berhampur India Department of CSE Seemanta Engineering College Mayurbhanj India

ISBN: (纸本)9789819938773

Video encryption based on lightweight algorithm has grew in importance as a research problem in the areas of internet of things (IoT). Traditional encryption techniques rely on long keys and more rounds, which are ineffective for small and low-power battery-operated devices. In this paper, we propose an effective approach for video encryption which is suggested in response to the popularity of lightweight encryption techniques created specifically for IoT environments. An effective video encryption technique based on optimization lightweight key generation method is proposed which uses two important approaches such as genetic algorithm for key generation and + 2 function for encryption and decryption. In this scenario, the most significant bit addition’s carry is mitigated by the binary addition, which presents as + 2. Correlation, entropy, and the image histogram of video frames have all been used to evaluate the suggested work. Experimental evaluation on a standard video, named Xylophone, clearly demonstrates the outcomes of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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