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

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Development of BCI-Driven Robotic Hand Control System: A Preliminary Study

Development of BCI-Driven Robotic Hand Control System: A Pre...

引用

Control Technology and Applications (CCTA),

作者： Rohit Gupta Bijuni Charan Sutar Amit Bhongade Tapan K. Gandhi Department of of Biomedical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India

ISBN: (数字)9798350370942

ISBN: (纸本)9798350370959

The sophisticated Brain-Computer Interface (BCI) utilizes discrete or model-based control techniques to manage external devices. A continuous control strategy is vital for achieving optimal and smooth operation. Achieving a continuous estimation of control parameters with minimal latency is crucial for enhancing the effectiveness and acceptance of mind-controlled prostheses, exoskeletons, and robotic arms by users. This research proposes a novel BCI model for controlling a robotic hand, incorporating Task Classification (TC) and Trajectory Estimation (TE) modules. The TC module interprets user intentions based on EEG signals, identifying tasks such as initiating, grasping, releasing, halting, or maintaining the current state. Upon detecting grasping (Task 2), the TE module estimates the 3D trajectory of hand movements, enabling precise control of the robotic hand. The control algorithm translates the estimated trajectory into commands for the robotic hand, facilitating object manipulation and task execution. Real-time feedback loops and error-handling mechanisms enhance user interaction and system robustness. Results demonstrate the efficacy of the integrated TC and TE modules in providing seamless control of the robotic hand, empowering individuals with motor disabilities to perform daily tasks independently. The implications of this work extend to the development of advanced BCIs, facilitating more natural and seamless communication between the human brain and technological devices.

关键词： Accuracy Robot kinematics Estimation signal processing algorithms Grasping Control systems Brain modeling

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Denoising techniques for multi-parametric prostate MRI: A Comparative Study

Denoising techniques for multi-parametric prostate MRI: A Co...

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5th International conference on advanced Technologies for signal and Image processing, ATSIP 2020

作者： Latrach, Afef Trigui, Rania Sellemi, Lamia Gabes University Atms Advanced Technologies for Medicine and Signal Enig Tunisia

ISBN: (纸本)9781728175133

Since recent years, denoising become one Of the most active area of research in image processing topic. Usually, MR images are affected by noise and artifacts during the acquisition process. Therefore, many denoising algorithms have been developed although noise elimination still an undefended challenge. In this paper, we study firstly different denoising filters for T2-Weighted prostate cancer MR images, in order to select the appropriate filter. As example of denoising filters, homomorphic, Median, Wavelet, nonlocal means, gaussian, Anisotropic, Laplacian, Cure-LET, LMMSE and bilateral. Then, we discuss the problem of evaluation of image quality which become necessary. As example of evaluation metrics, we present the PSNR, MSE and SSIM. We consider both subjective and objective quality assessment parameters for determining a final score of filters executed over 40 T2-Weighted MR images. This study concludes that Anisotropic filter should be opted for denoising T2-Weighted MR image since its details preserving capability. © 2020 IEEE.

关键词： Image quality

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Particle Gibbs Sampling for Regime-Switching State-Space Models

Particle Gibbs Sampling for Regime-Switching State-Space Mod...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Yousef El-Laham Liu Yang Heather J. Lynch Petar M. Djuric Monica F. Bugallo Stony Brook University Stony Brook NY Institute for Advanced Computational Sciences Stony Brook University Stony Brook NY

ISBN: (纸本)9781728176055;9781728176062

Regime-switching state-space models (RS-SSMs) are an important class of statistical models that can be used to represent real-world phenomena. Unlike regular state-space models, RS-SSMs allow for dynamic uncertainty in the state transition and observations distributions, making them much more expressive. Unfortunately, there are no existing Bayesian inference techniques for joint estimation of regimes, states, and model parameters in generic RS-SSMs. In this work, we develop a particle Gibbs sampling algorithm for Bayesian learning in RS-SSMs. We demonstrate the proposed inference approach on a synthetic data experiment related to an ecological application, where the goal is in estimating the abundance and demographic rates of penguins in the Antarctic.

关键词： Uncertainty Biological system modeling Heuristic algorithms signal processing algorithms Estimation signal processing Inference algorithms

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Terahertz Range Interconnecting Line For LEO-System 15

Terahertz Range Interconnecting Line For LEO-System

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15th International conference on advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)

作者： Saiko, Volodymyr Nakonechnyi, Volodymyr Narytnyk, Teodor Brailovskyi, Mykola Lukova-Chuiko, Nataliia Taras Shevchenko Natl Univ Kyiv Kiev Ukraine Ukrainian Acad Sci Inst Elect & Commun Kiev Ukraine

ISBN: (数字)9781728155661

ISBN: (纸本)9781728155661

The proposed technical solution relates to the field of mobile telecommunications, namely satellite communications systems, and can be used to provide low-orbital spacecraft communications with terrestrial stations and users of 5G / IoT satellite services. The essence of the proposed development is that in order to increase the communication distance and improve the noise immunity of the satellite channel in the system of low-orbital satellite communication, which includes the grouping of root (leading) satellites and satellites (relayed), the introduction of groupings of the satellite is proposed in the research, around each root satellite, which is synchronously radiating space-spaced low-power transmitting devices with a spatial correlation coefficient of less than 0.3 and terahertz receiving devices. With a view to improving the noise immunity of the terahertz band intercommunication line on the receiving side, a multipath signal processing scheme is proposed in which compensation of interfering signals in each channel is applied. A feature of the developed multipath signal processing algorithm is the compensation of interfering signals in each channel. In contrast to the well-known algorithms [12], the interference compensator does not use filtering but interpolation estimates. This is a significant difference in the use of the estimated-compensation principle of processing multipath signals. The difference between the new solution and the conventional one is that the interference compensator uses interpolation estimates. The simulation results of the proposed multipath signal processing scheme showed that the use of such a signal processing algorithm allows to increase the filtering accuracy by about 90-100% at a signal / noise ratio = 10 dB in a wide range of changes in the time delay of the signal in the i-th beam due to the increase of the propagation path.

关键词： terahertz lines "distributed satellite" low-orbiting satellite systems Internet of Things interference compensator multipath signal noise immunity inter-satellite communication

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Imbalanced Data Classification using Optimized Support Vector Machine for IoMT Application

Imbalanced Data Classification using Optimized Support Vecto...

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Ambient Intelligence in Health Care (ICAIHC), International conference on

作者： Binod Kumar Pattanayak Mihir Narayan Mohanty Smitarani Satpathy Jay Bijay Arjun Das Dept. of CSE ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Advanced Signal Processing Lab ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

In this digital age, most of the applications need to be Internet of Things based for easy access. Biomedical research has made significant growth related to it. The visual pathological information provides comparatively better information as compared to signals that help physicians with further analysis and suggestions. Medical data often exhibit class imbalance, where the number of samples in different classes is not proportional. This imbalance can pose significant challenges to traditional classification algorithms. This report explores the application of Support Vector Machines (SVM) to imbalanced medical data classification, discussing the inherent issues, techniques for addressing class imbalance, and experimental results showcasing the effectiveness of SVM in handling imbalanced medical datasets. As a result, the retrieval process over the internet will be faster. In this paper, authors have considered three different cancerous image data of breast cancer, brain tumor, and liver cancer for analysis and detection using a machine learning approach. The data is collected from the UCI machine learning repository. The statistical features like class, radius, and area are considered and optimized using the Brain Storm Optimization algorithm for good accuracy. The optimized features are applied to the support vector machine classifier. Further, use for different kernels such as radial basis function (RBF), linear, polynomial, and sigmoid are used with SVM and verified for comparison. It is found that the RBF kernel provides SVM better accuracy as compared to other kernels.

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Improvements on signal processing Algorithm for the VOPITB Equipment 12th

Improvements on Signal Processing Algorithm for the VOPITB E...

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12th IFIP WG 5.5/SOCOLNET advanced Doctoral conference on Computing, Electrical and Industrial Systems, DoCEIS 2021

作者： Cardoso, Filipa E. Vassilenko, Valentina Batista, Arnaldo Bonifácio, Paulo Martin, Sergio Rico Muñoz-Torrero, Juan Ortigueira, Manuel NOVA School of Science and Technology - NOVA University of Lisbon Caparica2829-516 Portugal NMT S.A. Edifício Madan Parque Caparica2825-182 Portugal Iberian Network on Arterial Structure Central Hemodynamics and Neurocognition Caceres Spain UNINOVA CTS NOVA School of Science and Technology - NOVA University Lisbon Caparica2829-516 Portugal Department of Nursing Nursing and Occupational Therapy College Universidad de Extremadura Caceres Spain Department of Internal Medicine Hospital San Pedro de Alcantara Caceres Spain

ISBN: (纸本)9783030782870

The pulse signal obtained non-invasively through an oscillometric method can accurately measure the Cardio-Ankle Vascular Index (CAVI) and Pulse Wave Velocity (PWV), two valuable physiological markers of arterial stiffness and cardiovascular health. The VOPITB device is designed to obtain these markers whose accuracy heavily depends on the correctness of feature extraction from pulse wave signals. Typically, a threshold method is obtained, leading to excessive detection success dependency on the established level. To overcome this limitation two signal processing methods are proposed, one based on a modified version of the Pan-Tompkins algorithm and the other centered on a Wavelet approach. A statistical study is presented assessing the accuracy of both methods. The new algorithms are presented as an alternative to the simple thresholding method. © 2021, IFIP International Federation for Information processing.

关键词： Wavelet analysis

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An investigation on digital signal processing for coherent optical communication system with advanced modulation format

An investigation on digital signal processing for coherent o...

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2020 International conference on Electrical Engineering and Control Technologies, CEECT 2020

作者： Huang, Simiao Xidian University Communication Engineering Xi'an China

ISBN: (纸本)9781728197975

In recent years, many new applications such as cloud computing, Internet of Things (IoT), artificial intelligence (AI) are developing rapidly, which put large capacity requirements on communication network. Coherent optical communication systems based on advanced modulation format have been extensively studied to improve transmission capacity. High-order modulation format requires a better signal-to-noise ratio (SNR) for signal receiving. However, the various damages in transmission links would decrease SNR. In this paper, digital signal processing (DSP) techniques are investigated to compensate signal damages, including Time-domain equalization (TDE) algorithm to compensate chromatic dispersion (CD), constant mode algorithm (CMA) and direct decision least mean square (DD-LMS) algorithm to compensate polarization mode dispersion (PMD), fourth power algorithm to correct frequency deviation, Viterbi & Viterbi and Blind Phase Search (BPS) algorithms to estimate phase noise. Moreover, constellation shaping technology is also discussed to make the transmission capacity closer to Shannon limit. © 2020 IEEE.

关键词： signal to noise ratio

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A Dynamic JPEG CODEC with Adaptive Quantization Table for Frame Storage Compression

A Dynamic JPEG CODEC with Adaptive Quantization Table for Fr...

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IEEE Asia-Pacific conference on Circuits and Systems

作者： Yichen Ouyang Xianglong Wang Gang Shi Lei Chen Fengwei An School of Microelectronics Southern University of Science and Technology Shenzhen China

Joint Photographic Experts Group (JPEG) is one of the most advanced compression formats for still images. However, JPEG is still limited and inefficient in real-time image processing and hardware implementation. This paper presents a dynamic JPEG CODEC (the encoder and decoder) to compress the frame storage. Based on the pipeline structure, the system uses ping-pong buffers to support the circuit across two clock domains. In addition, through dynamically adjusting the quantization table, the frame storage compression can fluctuate around 80% with high quality. Also, the simplification of compression decreases the initialization time of the decoder. The proposed word can yield a reduction of the frame storage of 76.60% and an improvement of the latency of 77.10% compared to the baseline JPEG CODEC.

关键词： Image coding Quantization (signal) Codecs Heuristic algorithms Pipelines Transform coding Real-time systems

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Cascade AOA Estimation Technique Based on The Combined Flexible Massive Array Antenna

Cascade AOA Estimation Technique Based on The Combined Flexi...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Tae-Yun Kim Heui-Seon Park Seul-Bi Jeon Tae-Ho Jo Suk-Seung Hwang Institute of AI Convergence Chosun University Gwangju Korea Dept. of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence System Chosun University Gwangju Korea Dept. of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence System Chosun University Gwangju Republic of Korea Interdisciplinary Program in IT-Bio Convergence System School of Electronic Engineering Chosun University Gwangju Korea

In the next-generation communication system, various communication services employs beamforming and massive array antenna techniques for reliable and efficient wireless communications. Based on the massive array antenna with a huge number of elements, the beamforming technique such as the estimation of Angle of Arrival (AOA) may not operate in real time, because the computational complexity for this situation should be extremely high. In order to enhance this problem, in this paper, we propose the cascade AOA estimation algorithm based on the Flexible Massive Combined Array (FMCA) antenna. The proposed algorithm finds AOA groups including multiple signal AOAs employing Capon based on some elements of the FMCA antenna, and it estimates the detail signal AOAs in the found AOA groups employing Beamspace Multiple signal Classification (MUSIC) based on entire elements of the FMCA antenna. In addition, we provide the received signal model for applying the FMCA antenna and the proposed cascade AOA estimation algorithm.

关键词： Wireless communication Array signal processing Estimation Receiving antennas Real-time systems Multiple signal classification Classification algorithms

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Post-processing algorithms for Performance Improvement of Substitution Boxes Based on Chaotic System 22

Post-processing Algorithms for Performance Improvement of Su...

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22nd International conference on Digital signal processing and its Applications, DSPA 2020

作者： Bahceci, Yasar Selim Ozkaynak, Fatih Firat University Faculty of Technology Department of Software Engineering Elazig Turkey

ISBN: (纸本)9781728175287

Substitution boxes are an important cryptographic primitive. Design techniques based on mathematical transformations, a design technique of these cryptographic primitives, have played a particularly important role in the block encryption algorithm known as the advanced Encryption Standard (AES). Because AES substitution box structure has the best cryptographic properties. However, various weaknesses arise when the implementation attacks are considered. Although the cryptographic properties of substitution box structures based on random selection techniques are worse than the AES substitution box structure, they are more successful to prevent implementation attacks. The aim of this study is to investigate the performance improvement algorithms of substitution boxes based on random selection. In this study, it has been shown that performance improvements of substitution boxes based on random selection can be achieved with the proposed post-processing algorithms. These results are thought to make significant contributions in the future, especially as a countermeasure for the prevention of implementation attacks. © 2020 IEEE.

关键词： Cryptography

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