Gait Signal Analysis with Similarity Measure by Sanghyuk Lee, Seungsoo Shin

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A convolutional autoencoder framework for ECG signal analysis by Ugo Lomoio, Patrizia Vizza, Raffaele Giancotti, Salvatore Petrolo, Sergio Flesca, Fabiola Boccuto, Pietro Hiram Guzzi, Pierangelo Veltri, Giuseppe Tradigo

“…AE specialized for signal data, named Convolutional Autoencoder (CAE), showed the best performances in the analysis of ECG signals.This paper presents a CAE-based framework for ECG signal analysis and anomaly identification. The trained phase is performed on synthetic data signals. …”
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Editorial: Smart biomedical signal analysis with machine intelligence by Tilendra Choudhary, Pulakesh Upadhyaya, Mohammad Zavid Parvez, Mohammad Zavid Parvez, Shaik Rafi Ahamed

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Bolt Detection Signal Analysis Method Based on ICEEMD by Chunhui Guo, Zhan Zhang, Xin Xie, Zhengyu Yang

“…In this paper, the improved complete ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt detection signal analysis. The ICEEMD is used in order to decompose the anchor detection signal according to the approximate entropy of each intrinsic mode function (IMF). …”
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Intelligent Fault Diagnosis Based on Vibration Signal Analysis by Minvydas Ragulskis, Lu Chen, Ganging Song, Ameen El Sinawi

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Control entropy: A complexity measure for nonstationary signals by Erik M. Bollt, Joseph D. Skufca, Stephen J . McGregor

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Corrigendum to “Bolt Detection Signal Analysis Method Based on ICEEMD” by Chunhui Guo, Zhan Zhang, Xie Xin, Zhengyu Yang

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Fault Diagnosis of Planetary Gearbox Based on Motor Current Signal Analysis by Ziyuan Jiang, Qinkai Han, Xueping Xu

“…Induction motor current signal analysis (MCSA) is a noninvasive method that uses current to detect faults. …”
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Vibration Signal Analysis of Journal Bearing Supported Rotor System by Cyclostationarity by Chang Peng, Lin Bo

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Machine learning-enhanced gesture recognition through impedance signal analysis by Huynh Hoang Nhut, Diep Quoc Tuan Nguyen, Dinh Minh Quan Cao, Tran Anh Tu, Dang Nguyen Chau, Phan Thien Luan, Tran Trung Nghia, Ching Congo Tak Shing

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Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter by Chun Lv, Peilin Zhang, Dinghai Wu, Bing Li, Yunqiang Zhang

“…Bearing fault signal analysis is an important means of bearing fault diagnosis. …”
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Unraveling landslide failure mechanisms with seismic signal analysis for enhanced pre-survey understanding by J.-M. Chang, J.-M. Chang, C.-M. Yang, W.-A. Chao, W.-A. Chao, C.-S. Ku, M.-W. Huang, M.-W. Huang, T.-C. Hsieh, C.-Y. Hung

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Analysis of Emotional Stress of Teachers in Japanese Teaching Process Based on EEG Signal Analysis by Jie Dong

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Deformable Models for Segmentation of CLSM Tissue Images and Its Application in FISH Signal Analysis by P. S. Umesh Adiga, B. B. Chaudhuri

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Vibration Signal Analysis of Water Seal Blasting Based on Wavelet Threshold Denoising and HHT Transformation by Jiang-chao Liu, Wen-xue Gao

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Non-Linear Signal Analysis Applied to Surface Wear Condition Monitoring in Reciprocating Sliding Testing Machines by Francisco Paulo Lépore Neto, José Daniel Biasoli de Mello, Marcelo Braga dos Santos

“…Since the linear path can be identified by traditional signal analysis, the non-linear function can be evaluated by the global input/output relationships. …”
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Remote Epilepsy Monitoring: Signal Quality and Reliability Comparative Analysis by Theeban Raj Shivaraja, Rabani Remli, Wan Asyraf Wan Zaidi, Kalaivani Chellappan

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FAST DATA ACQUISITION SYSTEM by Florin GROFU

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Optimization of Sample Size, Data Points, and Data Augmentation Stride in Vibration Signal Analysis for Deep Learning-Based Fault Diagnosis of Rotating Machines by Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen

“…However, the accuracy and reliability of these models in fault diagnosis tasks can be significantly influenced by critical input parameters, such as the sample size, the number of data points within each sample, and the augmentation stride in vibration signal analysis. To address this challenge, this paper proposes a new adaptive method based on Bayesian optimization to determine the optimal combination of these input parameters from raw vibration signals and enhance the diagnostic performance of deep learning models. …”
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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

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