Motor control method using single-sensor phase current reconstruction by Yin Lu, Yuntian Huang, Hao Guo

“…By collecting the motor's current signals and utilizing signal processing techniques such as Fourier transform and wavelet transform, information about the three-phase currents is extracted from the data of a single sensor. …”
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Model of 2D-imaging system using correlation-based reception for image synthesis of radio light sources by Petrosyan, Manvel Mher, Ryzhov, Anton Igorevich

“…It is shown how, using correlation signal processing methods, it is possible to construct 2D images of radio light sources using the example of computer modeling. …”
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Space-Based FPGA Radio Receiver Design, Debug, and Development of a Radiation-Tolerant Computing System by Zachary K. Baker, Mark E. Dunham, Keith Morgan, Michael Pigue, Matthew Stettler, Paul Graham, Eric N. Schmierer, John Power

“…Using two Xilinx Virtex 4 FPGAs, we have achieved 1 TeraOps/second signal processing on a 1920 Megabit/second datastream. …”
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Analysis of Marketing Prediction Model Based on Genetic Neural Network: Taking Clothing Marketing as an Example by Hua Peng, Luxiao Dong, Yi Sun, Yanfang Jiang

“…With the development of genetic neural network technology, this technology has been more and more widely used in signal processing, pattern recognition and other application fields. …”
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Imaging exoplanets with coronagraphic instruments by Galicher, Raphaël, Mazoyer, Johan

“…Finally, we present instrumental and signal processing techniques used for on-sky minimization or a posteriori calibration of these speckles in order to improve the performance of coronagraphs.…”
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Power Load Prediction Algorithm Based on Wavelet Transform by Xu Chen, Haomiao Zhang, Chao Zhang, Zhiqiang Cheng, Yinzhe Xu

“…This achievement is attributed to the powerful signal processing capabilities of the discrete wavelet transform, advanced pattern recognition and prediction capabilities of these three deep learning network algorithms, and the intelligence of digital twin technology. …”
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Measurement of Microvibration by Using Dual-Cavity Fiber Fabry-Perot Interferometer for Structural Health Monitoring by Dae-Hyun Kim, Jin-Hyuk Lee, Byung-Jun Ahn

“…The interferometer has structurally two arbitrary cavities; therefore the initial phase difference between two sinusoidal signals induced from the interferometer was also arbitrary. In order to do signal processing including an arc-tangent method, a random value of the initial phase difference is automatically adjusted to the exact 90 degrees in the phase-compensating algorithm part. …”
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Robust Multi-Subtype Identification of Breast Cancer Pathological Images Based on a Dual-Branch Frequency Domain Fusion Network by Jianjun Li, Kaiyue Wang, Xiaozhe Jiang

“…In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain. …”
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Multiple Aliasing of Windowed Real-Valued Signal as a Cause of Accuracy Limitation of DFT Methods by Karel Hajek, Zdenek Kohl

“…DFT spectral signal analysis is a widely used method for various types of signal processing due to its several advantages. In the case of incoherently sampled real-valued signals, spectral leakage and aliasing occur, causing errors in the signal spectrum estimate. …”
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Multitask Convolutional Neural Network for Rolling Element Bearing Fault Identification by Mingxing Jia, Yuemei Xu, Maoyi Hong, Xiyu Hu

“…The traditional signal processing-based rolling bearing fault diagnosis algorithms rely on artificial feature extraction and expert knowledge. …”
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Measuring transducers for optical diagnostic system with multifunctional unitary photovoltaic converters by R. I. Vorobei, O. K. Gusev, A. I. Svistun, A. K. Tyavlovsky, K. L. Tyavlovsky, L. I. Shadurskaya

“…Traditional solution of this problem lies in the field of multi-sensory systems, complex optical schemes and complex signal processing algorithms. The paper aims at the development of new measuring transducers for optical diagnostic system on a basis of multifunctional unitary photovoltaic converters built on semiconductors with low-concentration deep dopants that form multiple energy levels for different charge states in the band gap. …”
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Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition by Shiyuan Liu, Xiao Yu, Xu Qian, Fei Dong

“…To enhance the performance of the fault diagnosis of bearings under different working conditions, a novel diagnosis framework inspired by feature extraction, transfer learning (TL), and feature dimensionality reduction is proposed in this work, and dual-tree complex wavelet packet transform (DTCWPT) is used for signal processing. Additionally, transferable sensitive feature selection by ReliefF and the sum of mean deviation (TSFSR) is proposed to reduce the redundant information of the original feature set, to select sensitive features for fault diagnosis, and to reduce the difference between the marginal distributions of the training and testing feature sets. …”
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Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition by Maoqi Chen, Ales Holobar, Xu Zhang, Ping Zhou

“…Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. …”
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EEG-DGRN: dynamic graph representation network for subject-independent ERP detection by Jiabin Zhu, Xuanyu Jin, Yuhang Ming, Wanzeng Kong

“…Objectives The inter-subject variability remains a formidable challenge in electroencephalogram (EEG) signal processing. Existing event-related potential (ERP) detection methods inadequately consider the dynamic connectivity of EEG signals and event response differences between subjects, limiting the discriminability of task-related features.Methods In this article, we propose EEG-DGRN, a dynamic graph representation network designed for subject-independent ERP detection. …”
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Secure channel estimation model for cognitive radio network physical layer security using two-level shared key authentication by K. Saravanan, K. B. Gurumoorthy, Allwin Devaraj Stalin, Om Prakash Kumar

“…The security models for sensing and beamforming reduce the impact of adversaries such as eavesdroppers in the signal processing layer. To such an extent, this article introduces a Secure Channel Estimation Model (SCEM) using Channel State Information (CSI) and Deep Learning (DL) to improve the PLS. …”
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Control of Coexisting Attractors with Preselection of the Survived Attractor in Multistable Chua’s System: A Case Study by Zeric Tabekoueng Njitacke, Theophile Fonzin Fozin, Christian Tchito Tchapga, Gervais Dolvis Leutcho, K. Marcel Wouapi, Jacques Kengne

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High-Performance Wireless Piezoelectric Sensor Network for Distributed Structural Health Monitoring by Shang Gao, Xuewu Dai, Zheng Liu, Guiyun Tian

“…In addition to hardware, embedded signal processing and distributed data processing algorithm are designed as the intelligent “brain” of the proposed wireless monitoring network to extract features of the PZT signals, so that the data transmitted over the wireless link can be reduced significantly.…”
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Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions by Jiangtao Shen, Xinjing Wang, Ruixuan He, Ye Tian, Wenxin Wang, Peng Wang, Zhiwen Wen

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Autonomous Jerk Oscillator with Cosine Hyperbolic Nonlinearity: Analysis, FPGA Implementation, and Synchronization by Karthikeyan Rajagopal, Sifeu Takougang Kingni, Gaetan Fautso Kuiate, Victor Kamdoum Tamba, Viet-Thanh Pham

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Seismic Random Noise Suppression Using Optimal ANFIS as an Adaptive Self-Tuning Filter and Wavelet Thresholding by K. Geetha, Malaya Kumar Hota

“…Random noise attenuation plays a vital step in seismic signal processing. Numerous attenuation algorithms have been developed to separate and remove the random noise; nevertheless, they have failed to attain high precision. …”
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