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检索条件"主题词=Signal Processing Algorithms"

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Low Power Brushed Direct Current Motor Commutation Noise Analysis

Low Power Brushed Direct Current Motor Commutation Noise Ana...

引用

International Symposium on Intelligent Systems and Informatics (SISY)

作者： Mark Wendler József Kopják Doctoral School of Applied Informatics and Applied Mathematics Obuda University Budapest Hungary Kandó Kalmán Faculty of Electrical Engineering Obuda University Budapest Hungary

ISBN: (数字)9798350385601

ISBN: (纸本)9798350385618

Brushed DC (BDC) motors are widely used in cost-sensitive applications due to their simplicity and affordability, typically relying on Hall sensors or optical gate-based sensors for position and speed control. This paper explores the potential for sensorless control in BDC motors with power consumption below 5W, with the aim of further reducing costs by eliminating the need for physical sensors. The study begins with an overview of the low-cost encoder mechanisms, followed by an in-depth analysis of the commutation process and the mathematical modeling of the motor. Empirical measurements validate the-oretical findings, demonstrating the derivation of an index signal from the commutation ripple, which enables precise rotation feedback. In addition, the paper discusses the implementation of signal conditioning circuitry on development boards to facili-tate advanced digital signal processing in educational settings. This approach opens new opportunities for higher education students to experiment with and verify various sensorless control algorithms, using voltage and current noise as key inputs for embedded motor control applications.

关键词： Commutation Current measurement Velocity control Noise signal processing algorithms Sensorless control DC motors Reliability Optical sensors Indexes

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Simple Clustering-Based Algorithm for R-Peak Detection in Single-Lead ECG Chest Monitors

Simple Clustering-Based Algorithm for R-Peak Detection in Si...

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International Flexible Electronics Technology Conference (IFETC)

作者： Denice Gerardo Victor Toral Yann Houeix Encarnacion Castillo Almudena Rivadeneyra Francisco J. Romero Dept. Electronics and Computer Technology University of Granada Granada Spain

ISBN: (数字)9798331529468

ISBN: (纸本)9798331529475

This study presents a simple algorithm for R-peak detection in single-lead electrocardiograms (ECG) acquired on the chest of various volunteers using a wearable device. To achieve a balance between computational efficiency and detection accuracy, the proposed algorithm consists of two optimized stages that can be implemented in portable hardware. First, the ECG signal is preprocessed using the discrete wavelet transform (DWT) to remove the baseline wandering and denoise the signal. Second, a clustering-based algorithm classifies the different peaks in the ECG signal into two clusters based on their max-min amplitude. It is demonstrated that, despite the high variability of the ECG waveform among volunteers, the proposed algorithm effectively identifies the R-peaks with high accuracy without requiring the specific cardiac profile for each individual patient, thus ensuring a reliable and robust heart rate (HR) monitoring.

关键词： Heart rate signal processing algorithms Clustering algorithms Electrocardiography Classification algorithms Discrete wavelet transforms Reliability Wearable devices Biomedical monitoring Monitoring

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Multi-target data association method via T-S negative hesitation fuzzy model

Multi-target data association method via T-S negative hesita...

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International Conference on signal processing Proceedings (ICSP)

作者： Chuyun Zhang Weixin Xie Yanshan Li Zongxiang Liu Xuan Yang College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

To address the challenge of data association under uncertainty due to overlapping feature value ranges of multiple targets, we present a novel multi-target data association algorithm based on the Takagi-Sugeno (T-S) negative hesitant fuzzy model. This approach introduces a new multi-target T-S negative hesitant fuzzy model (MTSNH-FM), which is developed by integrating negative hesitant fuzzy sets with negative hesitant fuzzy numbers. For the parameter identification in the MTSNH-FM, we propose a new negative hesitant fuzzy index and apply the least squares method to adjust the model's parameters. Moreover, to tackle the multi-target data association problem within the MTSNH-FM framework, the input variables are determined by maximizing the negative hesitant fuzzy entropy. The results of simulations indicate that the proposed algorithm outperforms existing multi-target tracking techniques, particularly in cluttered environments.

关键词： Fuzzy sets Uncertainty Parameter estimation Input variables signal processing algorithms Data models Entropy Takagi-Sugeno model Indexes Least mean squares methods

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Atomic Norm Denoising for Multi-Frequency-Snapshot Doa Estimation

Atomic Norm Denoising for Multi-Frequency-Snapshot Doa Estim...

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Sensor Array and Multichannel signal processing Workshop

作者： Yongsung Park Peter Gerstoft Yifan Wu Michael B. Wakin NoiseLab University of California San Diego La Jolla CA USA Colorado School of Mines Golden CO USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Motivated by atomic norms in gridless sparse signal recovery’ we introduce a gridless direction-of-arrival (DOA) estimator capable of handling scenarios with multiple frequencies and multiple snapshots. Within the atomic norm frame-work, we consider a multi-frequency model analogous to a multi-snapshot model. Subsequently, we extend the model to accommodate both multi-snapshot and multi-frequency data. The proposed method is illustrated through numerical simulations and validated using ocean acoustic experimental data.

关键词： Time-frequency analysis Direction-of-arrival estimation Array signal processing Estimation signal processing algorithms Frequency estimation Data models

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Region based Image Contrast Enhancement Depending on Local Dominant Colour Component

Region based Image Contrast Enhancement Depending on Local D...

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International Conference on Imaging, signal processing and Communication (ICISPC)

作者： Debashis Das Diptadip Maiti Dept. of CSE Techno India University West Bengal India

ISBN: (数字)9798350367157

ISBN: (纸本)9798350367164

In this paper, we propose an image contrast enhancement mechanism by analysing the dominant colour component of every contributory pixel. The contrast enhancement is performed on the regions having similar dominating colour components by employing local histogram equalization. The process ensures the increment of the colour purity by preserving the level of brightness which is a major drawback of histogram equalization-based methods. The proposed method provides satisfactory results without any learning mechanism applied in the system which reduces the execution time of the process as well. The proposed algorithm is formulated, experimented and tested on a large set of standard colour images, in RGB format, collected from various databases. We compare the proposed method with both standalone and learning based image enhancement algorithms from the literature. The comparative analysis establishes the efficacy of the proposed method.

关键词： Learning systems Histograms Phase measurement Image color analysis signal processing algorithms Imaging signal processing

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Energy-Aware Adaptive Dijkstra: A Robust Routing Algorithm for Wireless Sensor Networks in Dynamic Environments

Energy-Aware Adaptive Dijkstra: A Robust Routing Algorithm f...

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IEEE International Conference on Intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： S. Regilan L.K. Hema J. Jenitha Department of Electronics and Communication Engineering Aarupadai Veedu Institute of Technology Vinayaka Missions Research Foundation (DU) Chennai Tamilnadu India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

In the realm of Wireless Sensor Networks (WSN s), the quest for efficient routing algorithms that optimize energy consumption and adapt to dynamic network conditions is paramount. This paper introduces a novel routing algorithm, Energy-Aware Adaptive Dijkstra (EAAD), designed to address these challenges. EAAD leverages the principles of Dijkstra's algorithm while incorporating energy-awareness and adaptability to mobility. The algorithm computes energy-efficient paths from source nodes to sinks, taking into account the node's energy levels and the distance involved. Moreover, EAAD accommodates mobility-induced changes by dynamically recalculating routes. In a simulation-based evaluation, EAAD demonstrated superior performance in terms of energy conservation and adaptability, resulting in a higher number of alive nodes and enhanced throughput. EAAD offers a promising solution for optimizing routing in WSN s, contributing to prolonged network lifetime and robustness in dynamic environments. Its potential extends to diverse applications where energy-efficient routing is vital.

关键词： Wireless sensor networks Energy consumption Adaptation models Adaptive systems Heuristic algorithms signal processing algorithms Routing

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3D Geometry Compression with Hybrid Framework: Quasi-JPEG and Phase Encoding

3D Geometry Compression with Hybrid Framework: Quasi-JPEG an...

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IEEE Workshop on Multimedia signal processing

作者： Wonbeen Oh Jae-Sang Hyun Department of Mechanical Engineering Yonsei University Seoul South Korea

ISBN: (数字)9798350387254

ISBN: (纸本)9798350387261

This paper proposes a novel end-to-end compression framework and implementation of depth image using phase encoding. Our method divides depth image into stair map and periodic map using sinusoidal phase encoding, and utilize lossless compression for stair map and lossy compression for periodic map to reduce errors on depth discontinuities. Our algorithm uses Run Length Encoding and entropy encoding for lossless compression of stair map. Periodic map is subdivided using trigonometric functions, and Discrete Cosine Transform was used for lossy compression. Experimental results show our method can achieve higher PSNR quality than JPEG2000, when compression was done on same bit-rate.

关键词： Geometry Solid modeling Image coding Three-dimensional displays Transform coding signal processing algorithms Stairs signal processing Entropy Discrete cosine transforms

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Single-Note Electric Guitar Picking Detection by Using Wrist-Worn Inertial Motion Sensors

Single-Note Electric Guitar Picking Detection by Using Wrist...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Soichiro Matsushita School of Computer Science Tokyo University of Technology Hachioji Tokyo Japan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

A wrist-worn inertial motion-sensing device with a high sampling frequency has been applied to evaluate single-note electric guitar picking. A combinatorial analysis using wrist-twisting angular jerk and time-differential vertical jerk signals detected on the guitar player’s dominant wrist achieved an accurate picking timing estimation. The developed signal processing algorithm succeeded in eliminating motion artifacts such as vibration from the guitar strings especially in the case of palm mute techniques. The timing differences between the motion-based method using a sampling frequency of 1024 Hz and a sound-based on-set timing analysis method as ground truth became less than 10 milliseconds. As a result, a population test in a 14-week-long guitar lesson class showed convincing results that reflected the difficulties of picking techniques.

关键词： Wrist Vibrations Visualization signal processing algorithms Estimation Rhythm Real-time systems Motion detection Timing Motion artifacts

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Principal Component Analysis in Matched Filtering of signals

Principal Component Analysis in Matched Filtering of Signals

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： Ivan Chesanovskyi Dmytro Mul Aleksiy Vavrichen Roman Horodyskyi Ruslan Khoptinskiy Serhii Tabenskyi Department of Telecommunication and Information Systems Bohdan Khmelnytskyi National Academy of the State Border Guard Service of Ukraine Khmelnytskyi Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

The article discusses a general approach to using the Karhunen-Loève transform to construct an optimal functional basis for coherent signal processing tasks. The potential gain is demonstrated by applying the synthesized matched basis in filtering narrowband signals against a quasi-white noise background. An example of a PSK signal fragment illustrates the general approach to the synthesis and use of a synthesized linear basis space in matched filtering.

关键词： Phase shift keying Filtering Noise signal processing algorithms Transforms Market research Telecommunications Power harmonic filters Narrowband Principal component analysis

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A Novel Quantum Algorithm for Solving Optimization Problems in Electrical Engineering

A Novel Quantum Algorithm for Solving Optimization Problems ...

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Innovative Practices in Technology and Management (ICIPTM), International Conference on

作者： Ajay Sharma Kuldeep Sharma Kanchan Yadav A L N Rao Amit Srivastava Shivani Pant Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Centre of Research Impact and Outreach Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Department of Electrical Engineering GLA University Mathura Lloyd Institute of Engineering & Technology Greater Noida Lloyd Law College Greater Noida Uttaranchal Institute of Technology Uttaranchal University Uttarakhand India

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

The ability of theoretical and monadic quantum models against number comparison to conventional Quantum Genetic Algorithm (QGA), quantitative particle swarm optimization, ant colony groups with simulated annealing types is analyzed in the context of electrical engineering. Several experiments were done, involving a collection of multiple data sets standard for the proposed circuit layout within power distribution and signal processing applications. In regard to comparative analysis, each algorithm presents its particular strengths for QGA-competitive convergence speed; ͟QPSO – quick conversion of individuals into a global optimum during evolution’s course and robust solutions quality in an unstable environment without tuning. The related works of the proposed algorithms include evaluating it against metaheuristics for power systems, nature-inspired hybrid heuristic approaches as well as physics motivated optimization schemes. The paper emphasizes the superiority of quantum algorithms over their classical counterparts, which is a major innovation in optimization space. This detailed analysis contributes to further comprehending the potentials of quantum computing in overcoming tough optimization challenges faced by electrical engineers.

关键词： Electrical engineering Electric potential Quantum algorithm signal processing algorithms Quantum mechanics Simulated annealing Writing

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