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SEMG feature extraction methods for pattern recognition of upper limbs

SEMG feature extraction methods for pattern recognition of u...

引用

International conference on advanced Mechatronic Systems (ICAMechS)

作者： Feng Zhang Pengfeng Li Zeng-Guang Hou Yixiong Chen Fei Xu Jin Hu Qingling Li Min Tan Laboratory of Complex Systems and Intelligence Science Institute of Automation the Chinese Academy of Sciences Beijing China Department of Chemical and Environmental Engineering China University of Mining and Technology Beijing China Chinese Academy of Sciences Beijing Beijing CN

In this paper, a new feature of surface electromyo-graphy (sEMG) by using discrete wavelet transform (DWT) is proposed for motion recognition of upper limbs, and this method can be eventually used for rehabilitation robot control. Seven traditional features of sEMG are also extracted for comparative study, they are integral of absolute value (IAV), difference absolute mean value (DAMV), zero crossing (ZC), variance (VAR), mean power spectral density (MPSD), mean frequency (MF) and median frequency (MDF) respectively. For comparing the recognition rate of the different motions of the upper limb, each feature or their combination are used to construct the feature vectors, and the BP neural network with variable learning rate back propagation with momentum (GDX) algorithm is used to classify these motion modes. The experimental results summarize that the new feature extracted by using DWT presents a higher recognition rate (98.9%) than all of the traditional features, and the traditional features combination can also greatly improve the recognition rate (99%).

关键词： Feature extraction Discrete wavelet transforms Training Muscles Reactive power Neurons signal processing algorithms

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Robust Vehicle Localization with GPS Dropouts

Robust Vehicle Localization with GPS Dropouts

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International conference on Intelligent and advanced Systems

作者： Salman Ali Shaukat Muhammad Arif Umar Iqbal Bhatti Khalid Munawar Aamer Iqbal Bhatti Ubaid M. Al-Saggaf Center of Excellence in Intelligent Engineering Systems King Abdulaziz University Department of Computer Science Umm-Alqura University Department of Aeronautics and Astronautics Institute of Space Technology Control and Signal Processing Research Group Capital University of Science and Technology

ISBN: (纸本)9781509008469

Vehicle navigation systems rely on the correct positioning information and GPS is the best solution. However, in situations of GPS outage, like in tunnels and dense woods, the vehicle can lose track quickly. Modern vehicle navigation systems are mostly based on the vehicle dynamics;proprietary algorithms keep navigating for quite some time. But these solutions are expensive and add much to a vehicle's cost. This paper proposes a Kalman filter based dead-reckoning algorithm that fuses GPS information with the orientation information from a cheap IMU/INS, and the vehicle's speed accessed from its ECU. This low-cost system uses GPS and IMU/INS in a loosely coupled manner along with vehicle's speed and keeps supplying a quite accurate position information with GPS outage for significantly long intervals. With proper tuning and initialization, the proposed scheme has a potential to keep working in a completely GPS-denied situation.

关键词： Navigation GPS IMU/INS Dead-reckoning

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Adaptive threshold vein enhancement method based on illuminance estimation

Adaptive threshold vein enhancement method based on illumina...

引用

IEEE advanced Information Technology, Electronic and Automation Control conference (IAEAC)

作者： Hailan Kuang Fuying Guan Xiaolin Ma Xinhua Liu School of Information Engineering Wuhan University of Technology Wuhan China Key Laboratory of Fiber Optic Sensing Technology and Information Processing Wuhan University of Technology Ministry of Education Wuhan China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Infrared vein images often contain a lot of noise due to the performance defects of the infrared imaging system, and these images have the characteristics of low contrast, low signal-to-noise ratio, and blurred target details. In order to improve this situation, an adaptive threshold enhancement algorithm based on guided filter illuminance estimation (ATEBIE) is proposed to enhance the detailed information of the vein infrared image in this paper, especially the vein pattern, which is of great significance for applications such as vein display and vein recognition. Firstly, the infrared image of the vein is converted to the LAB color space representation to obtain the L-component of the image; Secondly, the multi-scale Gaussian blurring is performed on the component, and the noise is removed at the same time to obtain the initial illuminance estimation; then the guided filtering is used for accuracy illumination estimation; Finally, according to the illuminance image, an adaptive threshold is adopted to dynamically adjust the image to achieve the purpose of vein image enhancement. The experimental results show that the proposed algorithm not only suppresses the image noise very well, but also effectively enhances the vein texture details, and has a good application prospect.

关键词： Image color analysis Veins Estimation Filtering algorithms Information filters Image enhancement signal to noise ratio

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Model-Based Systems Engineering to Design An Onboard Surround Vision System for Cooperative Automated Vehicles

Model-Based Systems Engineering to Design An Onboard Surroun...

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International Informatics and Software Engineering conference (UBMYK)

作者： Narsimlu Kemsaram Anweshan Das Gijs Dubbelman Space Robotics (SpaceR) Research Group SnT Centre University of Luxembourg Kirchberg Luxembourg Mobile Perception Systems (MPS) Lab Signal Processing Systems Group Eindhoven University of Technology Eindhoven AZ Netherlands

ISBN: (纸本)9781665407601

Cooperative automated vehicles have various electronic control units with multiple sensors running complex software algorithms to perceive and navigate their environment. Hence, there is a need to use advanced software engineering design methodology to reduce the software complexity and increase modularity. In this paper, we applied the SysCARS model-based systems engineering methodology to design an onboard surround vision system with a SysML modeling language using the IBM Rational Rhapsody modeling tool. The modeling methodology is described through various phases and steps with a modeling language to overcome the challenges. The modeling tool takes the information from the design model of the system and generates a skeletal code. The algorithm is written for each generated skeletal code, compiled with a C++ compiler on the host Desktop PC (Ubuntu 16.04 LTS), and deployed on the target Nvidia Drive PX2 embedded hardware platform. The designed solution fulfills the requirements of the onboard surround vision system.

关键词： Codes Software design Navigation Machine vision Computational modeling Design methodology Software algorithms

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Parallel stochastic search for PAPR reduction of OFDM signal

Parallel stochastic search for PAPR reduction of OFDM signal

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Noritaka Shigei Hideaki Kumashiro Hiromi Miyajima Kagoshima University Kagoshima

Tone injection (TI) is an effective technique to overcome high PAPR (peak-to-average power ratio) of OFDM. The PAPR reduction problem solved with TI is a combinatorial problem. Although the effectiveness of GA has been demonstrated for this problem, GA involves relative complex operators. This implies that, when implementing the methods of TI on digital circuits, other methods may outperform GA under the same processing time. In this paper, we investigate effective parallel search methods for the PAPR reduction, which are of simple structure for implementing digital circuits. At first, as the basis of the parallel methods, we propose two types of stochastic search methods. The one is Flip-Probability-specified type (FP) search and the other is a specified-Number-of-Flips type (NF) search. Both of them use only simple stochastic operators. Then, we propose an effective digital circuit implementation of the solution evaluation function. Finally, we propose a parallel search method based on FP and NF search. The simulation results show that, the proposed parallel search methods can improve not only the processing speed but also the quality of the solution.

关键词： Noise measurement Search methods Peak to average power ratio Genetic algorithms Digital circuits Simulation

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An Implementation of Montgomery Modular Multiplication on FPGAs

An Implementation of Montgomery Modular Multiplication on FP...

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International conference on Information Science and Cloud Computing (ISCC)

作者： Xinkai Yan Guiming Wu Dong Wu Fang Zheng Xianghui Xie State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China State Key Lab. of Math. Eng. & Adv. Comput. Wuxi China

Modular multiplication is one of the most important operations in the public key cryptographic algorithms. In order to design a high-performance modular multiplier, we present a novel hybrid Montgomery modular multiplier over GF(p) on FPGAs, which employs Karatsuba and Knuth multiplication algorithms in different levels to implement large integer multiplication. A 9-stage pipeline full-word multiplier is proposed for the 256-bit multiplication with 4-level recursion. The performance of our modular multiplier is improved through optimizing the pipeline and reducing carry-chain latency of the modular adder. On average, our modular multiplier can perform one 256-bit modular multiplication in 3 cycles. We can integrate 13 modular multipliers on a Xilinx Virtex-6 V6VSX475T FPGA. The experimental results show that the throughput of 856.9 million modular multiplications per second can be achieved and the hybrid Montgomery modular multiplier has an outstanding performance in the situations which need continuous multiplications.

关键词： Adders Pipelines Digital signal processing Field programmable gate arrays Algorithm design and analysis Elliptic curve cryptography Table lookup

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A Review of Acoustic signal-based Detection of Damage in Railway Tracks

A Review of Acoustic Signal-based Detection of Damage in Rai...

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Engineering Informatics, IEEE

作者： Akula Prakash Tezeswi Tadepalli Department of Civil Engineering National Institute of Technology Warangal (NITW) Hanamkonda Telangana India

ISBN: (数字)9798331505776

ISBN: (纸本)9798331505783

Regular inspection of railway tracks is critical for providing safety and efficiency in railway transportation systems to minimize accidents, maintenance costs and improve reliability by early detection. In this paper, a systematic review for damage detection in railway tracks using Acoustic signals (sound generated at the wheel and track interaction point) during the movement of the train is presented. Distributed Acoustic Sensing (DAS) is a valuable method for quick, long-distance monitoring of railway maintenance and technological development and crucial for accident avoidance. In regions prone to frequent train accidents, free automation of inspection processes is essential to prevent disasters and to provide safe and reliable operation of train vehicles. A wide range of Structural Health Monitoring (SHM) systems sensor data is noisy, making Machine Learning (ML) algorithms paramount for detecting abnormal railroad conditions among many others and achieving higher accuracy in maintenance and inspection. Several advanced signal processing techniques are used to recognize crack or misalignment patterns by employing Fourier transform and wavelet analysis. Further, the signals are classified through machine learning algorithms to classify between normal and damaged conditions, presenting a non-invasive, real-time and economic monitoring system that validates the system’s capability to detect several types of damage and could enhance rail infrastructure safety. Integration of these acoustic sensing with a set of trains in a predictive analytics framework makes the study of the field a scalable tool for efficient railway management.

关键词： Machine learning algorithms Tracking Wheels Inspection Rail transportation Acoustics Maintenance Sensors Monitoring Accidents

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A Variable Step-Size Transform-Domain LMS Algorithm Based on Minimum Mean-Square Deviation for Autoregressive Process

A Variable Step-Size Transform-Domain LMS Algorithm Based on...

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IEEE conference on Industrial Electronics and Applications

作者： Shengkui Zhao Douglas L. Jones Zhihong Man Suiyang Khoo Advanced Digital Sciences Center (ADSC) Illinois at Singapore Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Faculty of Engineering and Industrial Sciences Swinburne University of Technology School of Engineering Deakin University

ISBN: (纸本)9781467363204

In this paper, we investigate the optimal variable step-size approach for the transform-domain least-mean-square (TDLMS) algorithm to achieve fast convergence speed and low steady-state misadjustment. By minimizing the mean-square deviation (MSD) between the filter weight vector and the true vector, we derive and approximate the optimal variable step-size for the TDLMS algorithm given autoregressive (AR) process as input signals. The resulted variable step-size has simple formulation and easily-setting parameters. Computer simulation is demonstrated in the framework of adaptive system modeling with a fourth-order AR input process. The overall performance are observed superior to the existing popular variable step-size approaches of the TDLMS algorithm.

关键词： Convergence signal processing algorithms Vectors Least squares approximations Approximation algorithms Steady-state Time-domain analysis

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A Knowledge-Driven Graph Convolutional Network for Spectrum Prediction

A Knowledge-Driven Graph Convolutional Network for Spectrum ...

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International conference on Communication Technology (ICCT)

作者： Yibo Guo Yang Huang Qiuming Zhu College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

In the 6G mobile communication systems, the integration of sensing, communication, and array signal processing technologies heralds a new era of advanced situational awareness. However, this advancement raises critical concerns about privacy and security, especially with the widespread deployment of devices equipped with radar-like sensing capability, including malicious ones. Moreover, suffering from rapidly changing spectrum environments and the restricted capability of spectrum prediction, jamming effectiveness evaluation values may not be fully obtained. Therefore, in order to effectively jam the malicious sensing device and improve the spectrum utilization, spectrum prediction is expected to be a key enabler, which features predicting the jamming effectiveness evaluation values and recommending frequency-domain subbands for utilization. In order to characterize the relation between jamming devices and malicious sensing devices when predicting spectrum, we construct a spectrum knowledge graph (SKG). In order to encode the KGE vectors from the triplets composed of entities and relations, we develop the CNN-based KGE model, where the CNN can be exploited to derive embedding encoded with knowledge of relations. In order to address the problem of predicting spectrum, we convert this issue into a node regression problem based graph model and graph convolution network (GCN). In order to address the problem of sparse feature vectors related to entities and relationships within the SKG, we exploit KGE vectors generated by a CNN-based KGE algorithm to replace the one-hot encoding method, which can be used to formulate the feature matrix in the graph model. Simulation results indicate that the spectrum prediction algorithm based on a knowledge-driven graph convolutional network (KGCN) can significantly improve the accuracy of spectrum prediction.

关键词： Accuracy Graph convolutional networks Simulation signal processing algorithms Knowledge graphs Prediction algorithms Vectors Encoding Sensors Jamming

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F5: advanced optical communication: From devices, circuits, and architectures to algorithms

F5: Advanced optical communication: From devices, circuits, ...

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IEEE International conference on Solid-State Circuits (ISSCC)

作者： Bo Zhang Frederic Gianesello Simone Erba Mounir Meghelli Azita Emami Takayuki Shibasaki Broadcom Irvine CA STMicroelectronics Crolles France STMicroelectronics Pavia Italy IBM Thomas J Watson Research Center Yorktown Heights NY California Institute of Technology Pasadena CA Fujitsu Laboratories Kawasaki Japan

ISBN: (纸本)9781538622278;9781509049400

Since the invention of optical fiber in the 1970's, optical communication has been changing the landscape of telecommunication and data communication worldwide with its ultra-broad bandwidth and long haul transmission capabilities. It connects people around the world through submarine inter-continent optical cables, is the backbone of metro area networks, and is essential for data center network connectivity. Today, cost effective 100Gb/s optical links on a single fiber, using either III-V based optical devices or silicon photonics, are readily available for few meters to few kilometers connectivity solutions inside the data center and between data centers, while next generation links are poised to reach 400Gb/s. In this forum, the current state-of-the-art of optical communications will be reviewed, including advances in long-haul transport, progress in silicon photonics covering transceivers, packaging, assembly and test, progress in high order modulation schemes and signal processing, description of 56Gb/s and beyond electrical serial interfaces, and closing with a presentation on optical backplane technology.

关键词： Optical fibers High-speed optical techniques Integrated optics Optical fiber communication Optical signal processing Photonics

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