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检索条件"主题词=Signal Processing Algorithms"

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Sparse Array Design for Mimo Radar in Multipath Scenarios

Sparse Array Design for Mimo Radar in Multipath Scenarios

引用

Acoustics, Speech, and signal processing Workshops (ICASSPW), IEEE International Conference on

作者： Xuchen Li Ronghao Lin Hing Cheung So Department of EEIS University of Science and Technology of China Hefei China Department of EE City University of Hong Kong Hong Kong China

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

Sparse array designs have focused mostly on angular resolution (mainlobe width), peak sidelobe level and directivity factor of virtual arrays for multiple-input multiple-output (MIMO) radar. The notion of the MIMO radar virtual array is based on the direct path assumption in that the direction-of-departure (DOD) and direction-of-arrival (DOA) of the targets are equal. However, the DOD and DOA of targets in multipath scenarios are likely to be very different. The identification of multipath targets requires DOD-DOA imaging using the transmit and receive arrays, not the virtual array. To improve the imaging of both direct path and multipath targets, we introduce several new criteria for MIMO radar sparse linear array (SLA) designs for multipath scenarios. Under the new criteria, we adopt a cyclic optimization strategy under a coordinate descent framework to design the MIMO SLAs. We present several numerical examples to demonstrate the effectiveness of the proposed approaches.

关键词： Array signal processing MIMO radar signal processing algorithms Imaging Radar imaging Parallel processing US Department of Defense

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A Fast Image Matching Approach in Fatigue Testing of Wall Plate Structures

A Fast Image Matching Approach in Fatigue Testing of Wall Pl...

引用

IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： Zhang Wendong Shi Baoquan Chen Xianmin Lv Yuanbo National Key Laboratory of Strength and Structural Integrity AVIC Aircraft Strength Research Institute Xi'an China School of Mechano-Electronic Engineering Xidian University Xi'an China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

To address the challenges in motion vector estimation due to local non-uniform deformation of specimens during fatigue tests, this paper proposes an image matching method that combines template sub-image techniques with a Kalman filter. This method employs a mesh motion estimation model, initially using the Kalman filter to predict the matching point positions of mesh nodes. Subsequently, template matching is utilized to achieve precise matching of these nodes. The algorithm is accelerated through GPU-CPU heterogeneous parallel computing technology. Test results indicate that the GPU-accelerated image matching method attains the accuracy of the CPU-based algorithm while significantly reducing processing time, thereby fully meeting the real-time requirements of online image feature matching applications.

关键词： Accuracy Deformation Image matching signal processing algorithms Fatigue Prediction algorithms Vectors Real-time systems Kalman filters Testing

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Ultra-Low Memory Speech Denoising using Quantization-Aware Neural Architecture Search

Ultra-Low Memory Speech Denoising using Quantization-Aware N...

引用

IEEE Workshop on Machine Learning for signal processing

作者： Anastasios Vafeiadis Nick van de Waterlaat Clement Castel Bruno Defraene Gerardo Daalderop Sebastian Vogel Christophe Macours NXP Semiconductors

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

This paper introduces a novel neural network-based speech denoising approach designed for operation on ultra-low memory devices such as, e.g., gaming headsets. We show that neural network models with a memory footprint in the range of 15–30 kB can achieve effective speech denoising performance. First, to this end, a Neural Architecture Search (NAS) approach is proposed in a search space encompassing Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNN s). The goal is to optimize the trade-off between speech denoising performance and memory usage. Experiments indicate that Gated Recurrent Units (GRUs) are particularly prone to quantization issues in tight memory conditions compared to Long Short-Term Memory (LSTM) RNNs, a phenomenon not explored in prior research. Secondly, this work introduces a data preprocessing technique to model the microphone characteristics of the target gaming headset device, which further helps to optimize the speech denoising performance on-device. We believe these findings can serve as future guidance for deploying sophisticated neural network-based speech and audio processing algorithms on resource-constrained edge devices.

关键词： Performance evaluation Headphones Recurrent neural networks Quantization (signal) Noise reduction signal processing algorithms Training data Speech processing Long short term memory Microphones

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Classification and Characterization of RFI Events for Passive Earth Observation Bands

Classification and Characterization of RFI Events for Passiv...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Adrian Perez-Portero Jorge Querol Adriano Camps CommSensLab – UPC Universitat Politècnica de Catalunya – BarcelonaTech Institute of Space Studies of Catalonia (IEEC) – CTE-UPC SnT SigCom Group University of Luxembourg Luxembourg CoE UAE University Al-Ain UAE

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Passive Microwave remote sensing is a very energy-efficient and time-proven technology for remote sensing. Microwave Radiometry and Global Navigation Satellite System (GNSS)-Reflectometry are two widely-used examples. The increasing effects of Radio-Frequency Interferences (RFI) on the performance of these receivers have sparked serious concerns due to their proliferation. Detection and mitigation of RFI heavily rely on the identification and location of the interference sources. Due to the vast amount of degrees of freedom found in these RFIs, classification using classical signal processing techniques becomes problematic, especially if combined RFIs are found within the same bandwidth. In this work, continuous recordings of real RFI events from a real-time system to detect and locate RFI sources are used as training data for an automated classification system, the description and performance of which are presented and analyzed.

关键词： Training Time-frequency analysis Heuristic algorithms signal processing algorithms Training data Interference Kurtosis

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Online Dictionary Learning Method for Cone-beam X-ray Luminescence Computed Tomography Reconstruction: A Preliminary Simulation Study

Online Dictionary Learning Method for Cone-beam X-ray Lumine...

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International Conference on signal processing Proceedings (ICSP)

作者： Xin Cao Wenlong Tang Yifan Wang Yi Chen Linzhi Su Tianyu Liang Xingxing Hao School of Information Science and Technology Northwest University Xi’an China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Cone-beam X-ray luminescence computed tomography (CB-XLCT), an emergent hybrid imaging modality, has witnessed rapid advancements and is poised to emerge as a pivotal tool for the early three-dimensional detection of tumors. Nevertheless, the impediments posed by weak light absorption and pronounced scattering phenomena in biological tissue render the CB-XLCT reconstruction task a severely ill-conditioned inverse problem, thereby hampering the attainment of satisfactory reconstruction outcomes. This investigation introduces an innovative strategy rooted in Online Dictionary Learning (ODL), underpinned by Iterative Reduction FISTA (IR-FISTA), to surmount these challenges and enhance CB-XLCT's reconstruction efficacy. The ODL framework encompasses two primary stages: sparse coding and dictionary updating. During the sparse coding phase, the IR-FISTA algorithm is employed, distinguished by its rapid computational velocity and heightened accuracy in solution derivation. Subsequently, in the dictionary update stage, an online algorithm leveraging stochastic approximations is implemented to optimally exploit the distinct structural attributes of the problem domain, thereby facilitating efficient extraction of sparse features. To validate and quantify the performance enhancements, a series of numerical simulation trials were orchestrated. The resultant data evidences that this novel approach significantly outperforms conventional reconstruction methodologies, exemplified by heightened localization precision, improved morphological restoration, and augmented robustness, thereby affirming its potential in advancing the frontiers of CB-XLCT.

关键词： Dictionaries signal processing algorithms Imaging Machine learning Luminescence Approximation algorithms Encoding Image reconstruction X-ray imaging Tumors

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Integrated Modeling of Wireless System Performance under Beaulieu-Xie Fading and κ-μ Co-Channel Interference: A Multi-Dimensional Exploration

Integrated Modeling of Wireless System Performance under Bea...

引用

International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Deepak Upadhyay Kunj Bihari Sharma Rashmi Sharma Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350392319

ISBN: (纸本)9798350356137

This paper proposes simulation and analysis to discuss how the fading affects the wireless signal waves on different fading levels. Four types of fading: (i) no fading, (ii) a low level of fading, (iii) moderate level of fading and (iv), high level of fading was considered for simulating the signal amplitude over time. Selected fading levels were ‘added’ to model real world wireless scenarios in which both environmental and interference conditions are at play. The results indicated that in the absence of fading, the amplitude of the signal wave was continuous and not changed significantly; however, from low to severe fading, there could be directly proportional soaring fluctuations in its proper amplitude corresponding to lose of signal strength. Together, these findings underscore the importance of adaptive signal processing techniques and robust modulation strategies in suppressing the degradative effects of fading against the desirable characteristics of proper signal integrity and reliable performance. The findings highlight one reality in communications: understanding fading is critical for designing ultrareliable wireless systems that perform consistently across a variety of operational settings. The knowledge extracted based on this study would further add to novel way of designing robust strategies for signal resilience and Communication reliability emerged in future wireless networks.

关键词： Fading channels Wireless communication Fluctuations Wireless networks Modulation signal processing algorithms Reliability engineering Adaptive signal processing Robustness signal integrity

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Robust Hypersphere Fitting from Noisy Data Using Gibbs Sampling

Robust Hypersphere Fitting from Noisy Data Using Gibbs Sampl...

引用

European signal processing Conference (EUSIPCO)

作者： Younes Boutiyarzist Julien Lesouple Jean-Yves Tourneret TéSA Laboratory University of Toulouse Toulouse France ENAC University of Toulouse Toulouse France INP-ENSEEIHT/IRIT/TéSA University of Toulouse Toulouse France

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

This paper studies a robust algorithm allowing the estimation of the center and the radius of a hypersphere in the presence of outliers. To that extend, the Student-t distribution is assigned to the noise samples to mitigate the impact of the outliers. A von Mises-Fisher prior distribution is also assigned to latent variables in order to exploit the fact that the observed samples are located in a part of the hypersphere. A robust Bayesian algorithm based on a Gibbs sampler is then proposed to solve the hypersphere fitting problem. This algorithm generates samples asymptotically distributed according to the joint distribution of the unknown parameters of the hypersphere (radius and center), as well as the other model parameters such as the noise variance. Simulations conducted on synthetic data with controlled ground truth allow the performance of this algorithm to be appreciated.

关键词： Laser radar Noise Fitting signal processing algorithms Estimation Europe Data models Bayes methods Noise measurement Synthetic data

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Design and Implementation of Underwater Wireless Communication System Using MATLAB

Design and Implementation of Underwater Wireless Communicati...

引用

Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), IEEE International Conference on

作者： Amit Gangopadhyay P. Naveen Kumar R. Rushikesh Reddy S. Mohammed Anees P. Sivapradeep Electronics and Communication Engineering Mohan Babu University(Erstwhile Sree Vidyanikethan Engineering College) Tirupati India Electronics and Communication Engineering Sree Vidyanikethan Engineering College Tirupati India

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

Establishing dependable communication in underwater situations is extremely difficult because of things like noise, multipath propagation, and signal attenuation. In order to properly solve these issues, a comprehensive underwater wireless communication system is introduced. To improve dependability and reduce errors, the system starts by encoding the incoming data bits using channel coding algorithms. For effective transmission, the modulated signal is subsequently converted using Quadrature Phase Shift Keying (QPSK) modulation. An Inverse Fast Fourier Transform (IFFT) and cyclic prefix addition are used to counteract the effects of underwater channel distortion and lessen inter-symbol interference. The quality of the broadcast signal is lowered by a number of impairments, including as fading and additive white Gaussian noise (AWGN). An adaptive equalizer is used to dynamically modify the receiver characteristics in order to counteract these effects and enhance signal recovery. To precisely retrieve the sent information, the received signal is additionally subjected to the Fast Fourier Transform (FFT). The system's performance is evaluated by comparing the output bits with the original input following demodulation and decoding. The bit error rate, throughput, and overall dependability of the suggested system are assessed in order to determine its efficacy through simulation and analysis. All things considered, the suggested underwater wireless communication system shows potential for reliable and effective data transfer in difficult underwater settings.

关键词： Wireless communication Fading channels Fast Fourier transforms System performance Bit error rate Noise signal processing algorithms

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Aerial Photovoltaic Panel Infrared Image Defect Detection Method Based on Improved YOLOv8

Aerial Photovoltaic Panel Infrared Image Defect Detection Me...

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6th International Conference on Intelligent Computing and signal processing (ICSP)

作者： Hongtao Hu Yunxiang Li Junfeng Wang Yong Lu School of Computer Science Xi'an ShiYou University Xi'an China No.3 Oil Production Plant PetroChina Changqing Oilfield Company Xi'an Shannxi China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Photovoltaic panels are the core equipment of photovoltaic power generation. Defects in photovoltaic panels are generally detected by analyzing infrared images taken by drones. However, the photovoltaic panel defects to be detected in infrared images are small, and traditional target detection algorithms are not sensitive to small targets. Misdetections and missed detections are prone to occur. In response to the above problems, this article proposes an Improved-YOLOv8 model to increase the accuracy of small target detection. Firstly, the CA attention mechanism is integrated into the YOLOv8 model to improve the ability to extract defect target features and locations; secondly, the Bidirectional Feature Pyramid Network (BiFPN) is used to replace Concat to reduce the loss of target information and enhance the model's ability to fuse targets of different scales. Maintain the sensitivity of the model to targets of different scales; finally, experiments were conducted using infrared image data of photovoltaic panels taken aerially from a photovoltaic power station. The results show that the accuracy and mAP@0.5 of the Improved-YOLOv8 model reached 88.5% and 95.2% respectively, effectively improving the YOLOv8 model's ability to handle small target defects in photovoltaic panels.

关键词： Photovoltaic systems Accuracy Attention mechanisms signal processing algorithms Object detection signal processing Feature extraction Data models Drones Defect detection

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Sensor Placement Problem on Networks for Sensors with Multiple Specifications

Sensor Placement Problem on Networks for Sensors with Multip...

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European signal processing Conference (EUSIPCO)

作者： Junya Hara Shunsuke Ono Hiroshi Higashi Yuichi Tanaka Osaka University Osaka Japan Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

In this paper, we address a sensor placement problem on networks for a set of sensors with multiple specifications. Sensor placement problem has been studied extensively in environmental monitoring applications on various sensor networks, such as water supply, power electric, and gas pipeline networks. While most existing studies assume all sensors have the same specifications, one may need to consider a set of sensors composed of two or more specifications. We formulate a sensor placement problem with multiple sensor specifications based on a difference-of-convex (DC) optimization. Sensor placements are selected such that they simultaneously maximize the overall coverage area and minimize the total sensing budget. In experiments, we demonstrate the effectiveness of our proposed approach.

关键词： Sensor placement Pipelines signal processing algorithms Europe signal processing Environmental monitoring Optimization

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