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Artykuły w czasopismach na temat „Time-frequency distribution (TFD)”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 29 stycznia 2023

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1

Mika, Dariusz, Grzegorz Budzik, and Jerzy Józwik. "Single Channel Source Separation with ICA-Based Time-Frequency Decomposition." Sensors 20, no. 7 (April 3, 2020): 2019. http://dx.doi.org/10.3390/s20072019.

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This paper relates to the separation of single channel source signals from a single mixed signal by means of independent component analysis (ICA). The proposed idea lies in a time-frequency representation of the mixed signal and the use of ICA on spectral rows corresponding to different time intervals. In our approach, in order to reconstruct true sources, we proposed a novelty idea of grouping statistically independent time-frequency domain (TFD) components of the mixed signal obtained by ICA. The TFD components are grouped by hierarchical clustering and k-mean partitional clustering. The dis

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Wang, Yuqi, Jun Wang, Xingxing Jiang, Weiguo Huang, Juanjuan Shi, and Zhongkui Zhu. "Varying-parameter time-frequency manifold for gearbox fault diagnosis." Journal of Physics: Conference Series 2184, no. 1 (March 1, 2022): 012008. http://dx.doi.org/10.1088/1742-6596/2184/1/012008.

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Abstract The vibration signals of a faulty gearbox are non-stationary and contaminated by heavy background noise. Time-frequency transform is able to present the non-stationary fault impulsive features in the time-frequency distribution (TFD). However, the time-frequency fault information is still contaminated by the noise. This paper proposes a varying-parameter time-frequency manifold (VPTFM) method with the aim to remove the noise in the TFD for accurate identification of gearbox fault. First, a high-dimensional TFD is constructed by performing short- time Fourier transform (STFT) using som

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Wang, S. C., J. Han, Jian Feng Li, and Zhi Nong Li. "Adaptive Signal Analysis Based on Radial Parabola Kernel." Applied Mechanics and Materials 10-12 (December 2007): 737–41. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.737.

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Because of the deficiency of fixed kernel in bilinear time-frequency distribution (TFD), i.e. for each mapping, the resulting time-frequency representation is satisfactory only for a limited class of signals, a new adaptive kernel function named the radial parabola kernel (RPK), is proposed. The RPK can adopt the optimizing method to filter cross-terms adaptively according to the signal distribution, obtain good time-frequency resolution, and offer improved TFD for a large class of signals. Compared with traditional fixed -kernel functions, such as Wigner-Ville distribution, Choi-Willams distr

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Habban, M. F., M. Manap, A. R. Abdullah, M. H. Jopri, and T. Sutikno. "An Evaluation of Linear Time Frequency Distribution Analysis for VSI Switch Faults Identification." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 1 (March 1, 2017): 1. http://dx.doi.org/10.11591/ijpeds.v8.i1.pp1-9.

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This paper present an evaluation of linear time frequency distribution analysis for voltage source inverter system (VSI). Power electronic now are highly demand in industrial such as manufacturing, industrial process and semiconductor because of the reliability and sustainability. However, the phenomenon that happened in switch fault has become a critical issue in the development of advanced. This causes problems that occur study on fault switch at voltage source inverter (VSI) must be identified more closely so that problems like this can be prevented. The TFD which is STFT and S-transform me

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Manap, Mustafa, Abdul Rahim Abdullah, Srete Nikolovski, Tole Sutikno, and Mohd Hatta Jopri. "An improved smooth-windowed Wigner-Ville distribution analysis for voltage variation signal." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 4982. http://dx.doi.org/10.11591/ijece.v10i5.pp4982-4991.

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This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth-windowed wigner-ville distribution (SWWVD) used to represent time-varying signals in time-frequency representation (TFR). Good time and frequency resolutions offer superiority in SWWVD to analyze voltage variation signals that consist of variations in magnitude. The separable kernel parameters are estimated from the signal in order to get an accurate TFR. The TFR for various kernel parameters is compared by a set of performance measures. The evaluation shows that different kernel settings are requ

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6

Ma, Ding, Li Hua Shi, Shang Chen Fu, and Hong Fu Cao. "Localization of Lamb Wave Scattering Source Based on Time-Frequency Analysis." Applied Mechanics and Materials 281 (January 2013): 276–81. http://dx.doi.org/10.4028/www.scientific.net/amm.281.276.

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Considering the influence of Lamb wave dispersion on the precision of damage detection, a new detection method of scattering source based on time-frequency curves and ellipse localization method is proposed. Empirical mode decomposition(EMD) is used to decompose the scattering signal into finite narrowband signals, and a modified continuous wavelet transform(CWT) is further used to get the time-frequency distribution(TFD) of the detected signal, and the arriving time of different frequency component is estimated based on TFD. A series of location results can be obtained from different frequenc

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Ponce de León, Jesús, José Ramón Beltrán, and Fernando Beltrán. "Instantaneous frequency estimation and representation of the audio signal through Complex Wavelet Additive Synthesis." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 03 (May 2014): 1450030. http://dx.doi.org/10.1142/s0219691314500301.

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In this work, an improvement of the Complex Wavelet Additive Synthesis (CWAS) algorithm is presented. This algorithm is based on a discrete version of the Complex Continuous Wavelet Transform (CCWT) which analyzes the input signal in a frame-to-frame approach and under variable frequency resolution per octave. After summarizing several Time-Frequency Distributions (TFD), concretely the standard Short Time Fourier Transform (STFT), the Pseudo Wigner–Ville Distribution (PWVD), reassignment and complex wavelets, a comparative study of the accuracy in the instantaneous frequency (IF) estimation is

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8

Park, Gi Young, C. K. Lee, Jung Taek Kim, K. C. Kwon, and Sang J. Lee. "Design of a Time-Frequency Distribution for Vibration Monitoring under Corrosions in the Pipe." Key Engineering Materials 321-323 (October 2006): 1257–61. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.1257.

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To monitor the wear and degradation on a pipe by corrosion during a plant operation, the vibration signals were measured by an accelerometer and analyzed by several analysis techniques. From the conventional methods, it was difficult to identify the wear and degradation on the pipe. And hence, the time-frequency distribution (TFD) and the adaptive cone-kernel distribution (ACKD) devised for reducing the interfering cross-terms are applied to the acquired data. They can provide the distinguishing peak patterns between the normal and corrosion signals.

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9

Jopri, M. H., A. R. Abdullah, T. Sutikno, M. Manap, M. R. Ab Ghani, and M. R. Yusoff. "A Critical Review of Time-frequency Distribution Analysis for Detection and Classification of Harmonic Signal in Power Distribution System." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4603. http://dx.doi.org/10.11591/ijece.v8i6.pp4603-4618.

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<p>This paper presents a critical review of time-frequency distributions (TFDs) analysis for detection and classification of harmonic signal. 100 unique harmonic signals comprise of numerous characteristic are detected and classified by using spectrogram, Gabor transform and S-transform. The rulebased classifier and the threshold settings of the analysis are according to the IEEE Standard 1159 2009. The best TFD for harmonic signals detection and classification is selected through performance analysis with regards to the accuracy, computational complexity and memory size that been used d

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10

Mousa, Allam, and Rashid Saleem. "Using Reduced Interference Distribution to Analyze Abnormal Cardiac Signal." Journal of Electrical Engineering 62, no. 3 (May 1, 2011): 168–72. http://dx.doi.org/10.2478/v10187-011-0028-9.

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Using Reduced Interference Distribution to Analyze Abnormal Cardiac SignalDue to the non-stationary, multicomponent nature of biomedical signals, the use of time-frequency analysis can be inevitable for these signals. The choice and selection of the proper Time-Frequency Distribution (TFD) that can reveal the exact multicomponent structure of biological signals is vital in many applications, including the diagnosis of medical abnormalities. In this paper, the instantaneous frequency techniques using two distribution functions are applied for analysis of biological signals. These distributions

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11

KARTHICK, P. A., G. VENUGOPAL, and S. RAMAKRISHNAN. "ANALYSIS OF SURFACE EMG SIGNALS UNDER FATIGUE AND NON-FATIGUE CONDITIONS USING B-DISTRIBUTION BASED QUADRATIC TIME FREQUENCY DISTRIBUTION." Journal of Mechanics in Medicine and Biology 15, no. 02 (April 2015): 1540028. http://dx.doi.org/10.1142/s021951941540028x.

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In this paper, an attempt has been made to analyze surface electromyography (sEMG) signals under non-fatigue and fatigue conditions using time-frequency based features. The sEMG signals are recorded from biceps brachii muscle of 50 healthy volunteers under well-defined protocol. The pre-processed signals are divided into six equal epochs. The first and last segments are considered as non-fatigue and fatigue zones respectively. Further, these signals are subjected to B-distribution based quadratic time-frequency distribution (TFD). Time frequency based features such as instantaneous median freq

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12

Ahmad, Ashraf Adamu, A. S. Saliu, Abel E. Airoboman, U. M. Mahmud, and S. L. Abdullahi. "Identification of Radar Signals Based on Time-Frequency Agility using Short-Time Fourier Transform." Journal of Advances in Science and Engineering 1, no. 2 (August 14, 2018): 1–8. http://dx.doi.org/10.37121/jase.v1i2.18.

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With modern advances in radar technologies and increased complexity in aerial battle, there is need for knowledge acquisition on the abilities and operating characteristics of intercepted hostile systems. The required knowledge obtained through advanced signal processing is necessary for either real time-warning or in order to determine Electronic Order of Battle (EOB) of these systems. An algorithm was therefore developed in this paper based on a joint Time-Frequency Distribution (TFD) in order to identify the time-frequency agility of radar signals based on its changing pulse characteristics

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13

Zhou, Zibo, Zhihui Wang, Binbin Wang, Saiqiang Xia, and Jianwei Liu. "Clutter Suppression and Rotor Blade Feature Extraction of a Helicopter Based on Time–Frequency Flash Shifts in a Passive Bistatic Radar." Atmosphere 13, no. 8 (August 1, 2022): 1214. http://dx.doi.org/10.3390/atmos13081214.

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This paper presents a passive bistatic radar (PBR) configuration using a global navigation satellite system as an illuminator of opportunity for the rotor blade feature extraction of a helicopter. Aiming at the strong fixed clutter in the surveillance channel of the PBR, a novel iteration clutter elimination method-based singular-value decomposition approach is proposed. Instead of the range elimination method used in the classic extended cancellation algorithm, the proposed clutter elimination method distinguishes the clutter using the largest singular value and by remove this value. At the s

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14

Chicherin, I. V., B. A. Fedosenkov, and D. M. Dubinkin. "Monitoring the current trajectories of autonomous heavy platforms moving along the quarry routes of mining enterprises." Mining Industry Journal (Gornay Promishlennost), no. 5/2021 (November 12, 2021): 76–83. http://dx.doi.org/10.30686/1609-9192-2021-5-76-83.

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In order to obtain information about the generated current trajectories (CT) of unmanned mining dump trucks, in the software and hardware complexes of the computer-aided dispatching system (in the external control subsystem and the autonomous control subsystem) installed on-board of an (AHP), one-dimensional (scalar) continuous signals (hereinafter converted into discrete digital ones) with a time-dependent instantaneous frequency, the so-called chirp signals, are put in accordance with the current trajectories of the AHP. This approach makes it possible to continuously monitor and manage the

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15

Jopri, M. H., A. R. Abdullah, M. Manap, M. R. Yusoff, T. Sutikno, and M. F. Habban. "An Improved Detection and Classification Technique of Harmonic Signals in Power Distribution by Utilizing Spectrogram." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 12. http://dx.doi.org/10.11591/ijece.v7i1.pp12-20.

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This paper introduces an improved detection and classification technique of harmonic signals in power distribution using time-frequency distribution (TFD) analysis which is spectrogram. The spectrogram is an appropriate approach to signify signals in jointly time-frequency domain and known as time frequency representation (TFR). The spectral information of signals can be observed and estimated plainly from TFR due to identify the characteristics of the signals. Based on rule-based classifier and the threshold settings that referred to IEEE Standard 1159 2009, the detection and classification o

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16

Mohamad Basir, Muhammad Sufyan Safwan. "Window Optimisation of Power Quality Signal Detection using Gabor Transform." ASM Science Journal 14 (April 2, 2021): 1–10. http://dx.doi.org/10.32802/asmscj.2020.596.

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This paper presents power quality analysis on different signal characteristics, namely instantaneous sag, momentary sag, temporary sag, instantaneous swell, momentary swell, and temporary swell. Power quality signals were analyzed using linear time-frequency distribution (TFD) namely short-time Fourier transform (STFT) and proposed Gabor transform (GT), and the best technique for power quality detection was determined based on the performance analysis of varied window length. Optimum window length for different signal characteristics which are effective and reliable for developing real-time mo

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17

Seninete, Sara, Mansour Abed, Azeddine Bendiabdellah, Malika Mimi, Adel Belouchrani, Abdelaziz Ould Ali, and Bilal Djamal Eddine Cherif. "On the Use of High-resolution Time-frequency Distribution Based on a Polynomial Compact Support Kernel for Fault Detection in a Two-level Inverter." Periodica Polytechnica Electrical Engineering and Computer Science 64, no. 4 (August 31, 2020): 352–65. http://dx.doi.org/10.3311/ppee.15469.

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Quadratic Time-Frequency Distributions (TFDs) become a standard tool in many fields producing nonstationary signatures. However, these representations suffer from two drawbacks: First, bad time-frequency localization of the signal's autoterms due to the unavoidable crossterms generated by the bilinear form of these distributions. This results on bad estimation of the Instantaneous Frequency (IF) laws and decreases, in our case, the ability to precisely decide the existence of a motor fault. Secondly, the TFD's parameterization is not always straightforward. This paper deals with faults' detect

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18

H. Jopri, M., A. R. Abdullah, M. Manap, T. Sutikno, and M. R. Ab Ghani. "An Identification of Multiple Harmonic Sources in a Distribution System by Using Spectrogram." Bulletin of Electrical Engineering and Informatics 7, no. 2 (June 1, 2018): 244–56. http://dx.doi.org/10.11591/eei.v7i2.1188.

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The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances,

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19

Sabeti, Malihe, Ehsan Moradi, Mahsa Taghavi, Mokhtar Mohammadi, and Reza Boostani. "Time-Frequency Distribution Analysis for Electroencephalogram Signals of Patients With Schizophrenia and Normal Participants." International Clinical Neuroscience Journal 9, no. 1 (February 20, 2022): e11-e11. http://dx.doi.org/10.34172/icnj.2022.11.

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Background: Psychiatrists diagnose schizophrenia based on clinical symptoms such as disordered thinking, delusions, hallucinations, and severe distortion of daily functions. However, some of these symptoms are common with other mental illnesses such as bipolar mood disorder. Therefore, quantitative assessment of schizophrenia by analyzing a physiological-based data such as the electroencephalogram (EEG) signal is of interest. In this study, we analyze the spectrum and time-frequency distribution (TFD) of EEG signals to understand how schizophrenia affects these signals. Methods: In this regard

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20

KOSTYUK, Svetlana, Ivan CHICHERIN, Boris FEDOSENKOV, and Dmitry DUBINKIN. "MONITORING OF THE DYNAMIC STATE OF AUTONOMOUS HEAVY PLATFORMS ON THE QUARRY ROUTES OF MINING ENTERPRISES." Sustainable Development of Mountain Territories 12, no. 4 (December 30, 2020): 600–608. http://dx.doi.org/10.21177/1998-4502-2020-12-4-600-608.

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Purpose of work. The article presents the results of theoretical research and developments obtained at the Kuzbass state technical university on the implementation of current monitoring and bringing about signal processing procedures for the dynamic state of autonomous heavy platforms (AHP) on open pit mine routes. In order to obtain information about the generated current trajectories (CT) of unmanned mining dump trucks, in the software and hardware complexes of the computer-aided dispatching system (in the external control subsystem – ECSS and the autonomous control subsystem – ACSS) install

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Abdullah, Abdul Rahim, N. A. Abidullah, N. H. Shamsudin, N. H. H. Ahmad, and M. H. Jopri. "Performance Verification of Power Quality Signals Classification System." Applied Mechanics and Materials 752-753 (April 2015): 1158–63. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1158.

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Power quality has become a greater concern nowadays. The increasing number of power electronics equipment contributes to the poor quality of electrical power supply. The power quality signals will affect manufacturing process, malfunction of equipment and economic losses. This paper presents the verification analysis of power quality signals classification system. The developed system is based on linear time-frequency distribution (TFD) which is spectrogram that represents the signals jointly in time-frequency representation (TFR). The TFD is very appropriate to analyze power quality signals t

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Jopri, M. H., A. R. Abdullah, M. Manap, M. R. Yusoff, T. Sutikno, and M. F. Habban. "An Improved of Multiple Harmonic Sources Identification in Distribution System with Inverter Loads by Using Spectrogram." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 4 (December 1, 2016): 1355. http://dx.doi.org/10.11591/ijpeds.v7.i4.pp1355-1365.

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This paper introduces an improved of multiple harmonic sources identification that been produced by inverter loads in power system using time-frequency distribution (TFD) analysis which is spectrogram. The spectrogram is a very applicable method to represent signals in time-frequency representation (TFR) and the main advantages of spectrogram are the accuracy, speed of the algorithm and use low memory size such that it can be computed rapidly. The identification of multiple harmonic sources is based on the significant relationship of spectral impedances which are the fundamental impedance (Z1)

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Chicherin, Ivan V., Boris A. Fedosenkov, Ilia S. Syrkin, Vladimir Iu Sadovets, and Dmitrii M. Dubinkin. "Using a wavelet medium for computer-aided controlling the movement of unmanned vehicles along quarry routes." Izvestiya vysshikh uchebnykh zavedenii. Gornyi zhurnal 1 (March 30, 2021): 103–12. http://dx.doi.org/10.21440/0536-1028-2021-2-103-112.

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Introduction. It is established that the most effective tool for monitoring and controlling the dynamics of current trajectories (CT) of unmanned vehicles (UMV) when moving along opencast mine routes in open pit mining is the wavelet transforms technique. Methodology. A detailed analysis of the procedures related to the technology of converting 1D-current trajectory signals (CT-signals) into a multidimensional medium of time-frequency distributions (TFD) is carried out. The Wigner distribution is selected as a working distribution for processing CT-signals. This distribution is considered from

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Jing Wei, Too, Abdul Rahim Bin Abdullah, Norhashimah Binti Mohd Saad, Nursabillilah Binti Mohd Ali, and Tengku Nor Shuhada Binti Tengku Zawawi. "Featureless EMG pattern recognition based on convolutional neural network." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 3 (June 1, 2019): 1291. http://dx.doi.org/10.11591/ijeecs.v14.i3.pp1291-1297.

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In this paper, the performance of featureless EMG pattern recognition in classifying hand and wrist movements are presented. The time-frequency distribution (TFD), spectrogram is employed to transform the raw EMG signals into time-frequency representation (TFR). The TFRs or spectrogram images are then directly fed into convolutional neural network (CNN) for classification. Two CNN models are proposed to learn the features automatically from the images without the need of manual feature extraction. The performance of CNN with different number of convolutional layers is examined. The proposed CN

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Han, Lixun, and Cunqian Feng. "Micro-Doppler-Based Space Target Recognition with a One-Dimensional Parallel Network." International Journal of Antennas and Propagation 2020 (October 5, 2020): 1–10. http://dx.doi.org/10.1155/2020/8013802.

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Space target identification is key to missile defense. Micromotion, as an inherent attribute of the target, can be used as the theoretical basis for target recognition. Meanwhile, time-varying micro-Doppler (m-D) frequency shifts induce frequency modulations on the target echo, which can be referred to as the m-D effect. m-D features are widely used in space target recognition as it can reflect the physical attributes of the space targets. However, the traditional recognition method requires human participation, which often leads to misjudgment. In this paper, an intelligent recognition method

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Razzaq, Huda Saleem, та Zahir M. Hussain. "Instantaneous Frequency Estimation of FM Signals under Gaussian and Symmetric α-Stable Noise: Deep Learning versus Time–Frequency Analysis". Information 14, № 1 (28 грудня 2022): 18. http://dx.doi.org/10.3390/info14010018.

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Deep learning (DL) and machine learning (ML) are widely used in many fields but rarely used in the frequency estimation (FE) and slope estimation (SE) of signals. Frequency and slope estimation for frequency-modulated (FM) and single-tone sinusoidal signals are essential in various applications, such as wireless communications, sound navigation and ranging (SONAR), and radio detection and ranging (RADAR) measurements. This work proposed a novel frequency estimation technique for instantaneous linear FM (LFM) sinusoidal wave using deep learning. Deep neural networks (DNN) and convolutional neur

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Kasim, Rizanaliah, Abdul Rahim Abdullah, Nur Asmiza Selamat, N. A. Abidullah, and Tengku Nor Shuhadah Tengku Zawawi. "Lead Acid Battery Analysis Using Spectogram ." Applied Mechanics and Materials 785 (August 2015): 692–96. http://dx.doi.org/10.4028/www.scientific.net/amm.785.692.

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Renewable energy is an alternative option that can be substituted for future energy demand. Many type of battery are used in commerce to propel portable power and this makes the task of selecting the right battery type is crucial. This paper presents the analysis of voltage charging and discharging for lead acid battery using time-frequency distribution (TFD) which is spectrogram. Spectogram technique is used to represent the signals in the time-frequency representation (TFR). The parameter of a signal such as instantaneous root mean square (RMS) voltage, direct current voltage (VDC) and alter

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Liang, Lin, Lei Shan, Fei Liu, Ben Niu, and Guanghua Xu. "Sparse Envelope Spectra for Feature Extraction of Bearing Faults Based on NMF." Applied Sciences 9, no. 4 (February 21, 2019): 755. http://dx.doi.org/10.3390/app9040755.

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Periodic impulses and the oscillation response signal are the vital feature indicators of rolling bearing faults. However, finding the suitable feature frequency band is usually difficult due to the interferences of other components and multiple resonance regions. According to the characteristics of non-negative matrix factorization (NMF) on a spectrogram, the feature extraction method from a sparse envelope spectrum for rolling bearing faults is proposed in this paper. On the basis of the time–frequency distribution (TFD) of the periodic transient oscillations, the basic matrix can be interpr

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Rahim Abdullah, Abdul, Nur Hafizah Tul Huda Ahmad, N. A. Abidullah, N. H. Shamsudin, and M. H. Jopri. "Performance Evaluation of Real Power Quality Disturbances Analysis Using S-Transform." Applied Mechanics and Materials 752-753 (April 2015): 1343–48. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1343.

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Power quality is main issue because of the impact to electricity suppliers, equipments, manufacturers and user.To solve the power quality problem, an analysis of power quality disturbances is required to identify and rectify any failures on power system. Most of researchers apply fourier transform in power quality analysis, however the ability of fourier transform is limited to spectral information extraction that can be applied on stationary disturbances. Thus, time-frequency analysis is introduced for analyzing the power quality distubances because of the limitation of fourier transform. Thi

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Ahmad, Ashraf Adamu, Abdullahi Daniyan, and David Ocholi Gabriel. "Selection of window for inter-pulse analysis of simple pulsed radar signal using the short time Fourier transform." International Journal of Engineering & Technology 4, no. 4 (November 17, 2015): 531. http://dx.doi.org/10.14419/ijet.v4i4.5139.

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The electronic intelligence (ELINT) system is used by the military to detect, extract information and classify incoming radar signals. This work utilizes short time Fourier transform (STFT) - time frequency distribution (TFD) for inter-pulse analysis of the radar signal in order to estimate basic radar signal time parameters (pulse width and pulse repetition period). Four well-known windows functions of different and unique characteristics were used for the localization of STFT to determine their various effects on the analysis. The window functions are Hamming, Hanning, Bartlett and Blackman

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Lin, Lin, Jia Jin Qi, Nan Tian Huang, and Shi Guang Luo. "Time-Frequency Analysis Methods for Power Quality Disturbances Feature Representation." Key Engineering Materials 439-440 (June 2010): 298–303. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.298.

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Power quality (PQ) analysis is the foundation of power system automation. The premise of power quality analysis is feature representation of power quality events. Time-frequency analysis (TFA) is very suitable for nonstationary signals analysis. The TFA of a PQ signal is to determine the energy distribution along the frequency axis at each time instant. This paper provides a status report of feature representation for PQ events by TFA methods, including short time Fourier transform (STFT), wavelet transform (WT) and S-transform (ST), overview the basic TFA theories for PQ analysis and compare

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Wang, Hui Qi, and Wangyong Lv. "FrFT Angle Division Multiple Access with Optimal Time-Frequency-Angle Resource Distribution." Applied Mechanics and Materials 519-520 (February 2014): 1012–15. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1012.

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In this paper, optimal time-frequency-angle (TFA) resource distribution is proposed. It is achieved by fractional Fourier transform (FrFT) angle division multiple access (ADMA), and multiple data streams can be transmitted in the same frequency and time slot. Comparing with conventional time-frequency (TF) resource based orthogonal frequency division multiplexing (OFDM) system, the exponential base at each sub-channel is replaced by a set of chirp bases, which keep mutually approximately orthogonal. Each base station (BS) can support more move stations (MSs) or cell throughput. Simulations sho

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Liu, Lifeng, Meng Guan, Xiangtao Zhang, Yanhui Zhu, Huaxing Lv, and Chang Meng. "Frequency information extraction based on time-frequency ridges for characterizing thin sand bodies." Journal of Geophysics and Engineering 19, no. 2 (April 2022): 167–77. http://dx.doi.org/10.1093/jge/gxac008.

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Abstract Time-frequency analysis (TFA) is a widely used reservoir prediction technology. During the identification of sand bodies using TFA, abnormally high values in the high-frequency portion of the spectrum usually indicate the presence of thin sand bodies. However, owing to the complexity of the depositional environment, the spatial distribution of thin sand bodies is often variable, and multiple phases of sand bodies—superimposed on each other—can occur with uneven thicknesses. A frequency information extraction technique based on time-frequency ridges (TFRs) is proposed in this study to

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Bačnar, David, Nicoletta Saulig, Irena Petrijevčanin Vuksanović, and Jonatan Lerga. "Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes." Sensors 22, no. 10 (May 13, 2022): 3727. http://dx.doi.org/10.3390/s22103727.

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This paper explores three groups of time–frequency distributions: the Cohen’s, affine, and reassigned classes of time–frequency representations (TFRs). This study provides detailed insight into the theory behind the selected TFRs belonging to these classes. Extensive numerical simulations were performed with examples that illustrate the behavior of the analyzed TFR classes in the joint time–frequency domain. The methods were applied both on synthetic and real-life non-stationary signals. The obtained results were assessed with respect to time–frequency concentration (measured by the Rényi entr

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Manap, M., Nur Sumayyah Ahmad, Abdul Rahim Abdullah, and Norhazilina Bahari. "Comparison of Open and Short-Circuit Switches Faults Voltage Source Inverter (VSI) Analysis Using Time-Frequency Distributions." Applied Mechanics and Materials 752-753 (April 2015): 1164–69. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1164.

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Voltage source inverter (VSI) plays an important roles in electrical drive systems. Consistently, expose to hash environmental condition, the lifespan of the electronic component such as insulated-gate bipolar transistor (IGBT) may shorten and many faults related to the inverter especially switches can be occur. The present of VSI switches faults causing equipment failure and increased the cost of manufacturing process. Therefore, faults detection analysis is mandatory to identify the VSI switches faults. This paper presents the analysis of VSI switches faults using time-frequency distribution

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Al-Fahoum, Amjed S., and Ausilah A. Al-Fraihat. "Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time-Frequency Domains." ISRN Neuroscience 2014 (February 13, 2014): 1–7. http://dx.doi.org/10.1155/2014/730218.

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Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract

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Hou, Yating, Liming Wang, Xiuli Luo, and Xingcheng Han. "Local maximum synchrosqueezes form scaling-basis chirplet transform." PLOS ONE 17, no. 11 (November 29, 2022): e0278223. http://dx.doi.org/10.1371/journal.pone.0278223.

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In recent years, time-frequency analysis (TFA) methods have received widespread attention and undergone rapid development. However, traditional TFA methods cannot achieve the desired effect when dealing with nonstationary signals. Therefore, this study proposes a new TFA method called the local maximum synchrosqueezing scaling-basis chirplet transform (LMSBCT), which is a further improvement of the scaling-basis chirplet transform (SBCT) with energy rearrangement in frequency and can be viewed as a good combination of SBCT and local maximum synchrosqueezing transform. A better concentration in

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Mohseni Saravi, M., A. A. Safdari, and A. Malekian. "Intensity-Duration-Frequency and spatial analysis of droughts using the Standardized Precipitation Index." Hydrology and Earth System Sciences Discussions 6, no. 2 (March 2, 2009): 1347–83. http://dx.doi.org/10.5194/hessd-6-1347-2009.

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Abstract. Precipitation deficit and its daily, seasonal and annual oscillations are inherent characteristics of Iran's climate. Droughts are generally characterized by a prolonged and abnormal moisture deficiency. In drought studies it is important to characterize the start and end of a drought as well as its intensity, duration, frequency and magnitude. The objective of this study was to analyze drought characteristics and to develop drought maps in the Karoon river basin, Iran. The Standardized Precipitation Index (SPI) was used in drought analysis based on the data for meteorological statio

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Huang, Yucheng, Xiaodong Zheng, Yanting Duan, and Yi Luan. "Robust time-frequency analysis of seismic data using general linear chirplet transform." GEOPHYSICS 83, no. 3 (May 1, 2018): V197—V214. http://dx.doi.org/10.1190/geo2017-0145.1.

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Time-frequency analysis (TFA) has been widely used in seismic processing and interpretation. A good time-frequency representation can preferably characterize geologic spatial distribution and detect hydrocarbon reservoir anomalies. This paper applies a robust seismic TFA method based on the general linear chirplet transform (GLCT). The GLCT method is an extended form of LCT, which is a unifying framework encompassing the short time Fourier transform (STFT) and the continuous wavelet transform (CWT) using the chirplet atom as the kernel function instead of the sinusoidal wave or wavelets. By ro

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Ahrenholz, P., D. Falkenhagen, and H. Klinkmann. "A Simplified Procedure to Compute Dialysis Time and Frequency by Means of Urea Kinetics." International Journal of Artificial Organs 11, no. 5 (September 1988): 366–72. http://dx.doi.org/10.1177/039139888801100511.

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A simplified urea model is presented based on the concept of the time-averaged deviation (TAD) of the blood urea concentration and the introduction of an effective urea generation rate. The increase in the interdialytic blood urea concentration Δc is specific for the individual patient and includes the urea generation rate, distribution volume and residual kidney clearance. By measuring Δc of the largest interdialytic interval of the week the treatment frequency and duration can be calculated. Even for larger residual clearances Kr ≤ 5 ml/min this calculated treatment time does not differ by m

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Li, Teng, Zhijie Jiao, Lina Wang, and Yong Mu. "A Method of DC Arc Detection in All-Electric Aircraft." Energies 13, no. 16 (August 13, 2020): 4190. http://dx.doi.org/10.3390/en13164190.

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Arc faults in an aircraft’s power distribution system (PDS) often leads to cable and equipment damage, which seriously threatens the personal safety of the passengers and pilots. An accurate and real-time arc fault detection method is needed for the Solid-State Power Controller (SSPC), which is a key protection equipment in a PDS. In this paper, a new arc detection method is proposed based on the improved LeNet5 Convolutional Neural Network (CNN) model after a Time–Frequency Analysis (TFA) of the DC currents was obtained, which makes the arc detection more real-time. The CNN is proposed to det

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Ding, Yi, Weiwei Fan, Zijing Zhang, Feng Zhou, and Bingbing Lu. "Radio Frequency Interference Mitigation for Synthetic Aperture Radar Based on the Time-Frequency Constraint Joint Low-Rank and Sparsity Properties." Remote Sensing 14, no. 3 (February 7, 2022): 775. http://dx.doi.org/10.3390/rs14030775.

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Synthetic aperture radar (SAR) is susceptible to radio frequency interference (RFI), which becomes especially commonplace in the increasingly complex electromagnetic environments. RFI severely detracts from SAR imaging quality, which hinders image interpretation. Therefore, some RFI mitigation algorithms have been introduced based on the partial features of RFI, but the RFI reconstruction models in these algorithms are rough and can be improved further. This paper proposes two algorithms for accurately modeling the structural properties of RFI and target echo signal (TES). Firstly, an RFI miti

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Chmel, A., V. Smirnov, and A. Panov. "Interplay between linear, dissipative and permanently critical mechanical processes in Arctic sea ice." Cryosphere Discussions 4, no. 3 (August 25, 2010): 1433–48. http://dx.doi.org/10.5194/tcd-4-1433-2010.

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Abstract. Mechanical processes in the Arctic ice pack result in fragmented sea ice cover, the regular geometry of which could be described in main features in terms of the conventional mechanics. However, the size distribution of sea ice floes does not exhibit the random (poissonian-like) statistics and follows the power law typical for self-similar (fractal) structures. The analysis of ice floe oscillations in the frequency range specific for cracking, shearing and stick-slip motion evidences the self-organized dynamics of sea ice fracturing, which manifests itself in scaling distributions of

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Delgado-Arredondo, Paulo Antonio, Arturo Garcia-Perez, Daniel Morinigo-Sotelo, Roque Alfredo Osornio-Rios, Juan Gabriel Avina-Cervantes, Horacio Rostro-Gonzalez, and Rene de Jesus Romero-Troncoso. "Comparative Study of Time-Frequency Decomposition Techniques for Fault Detection in Induction Motors Using Vibration Analysis during Startup Transient." Shock and Vibration 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/708034.

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Induction motors are critical components for most industries and the condition monitoring has become necessary to detect faults. There are several techniques for fault diagnosis of induction motors and analyzing the startup transient vibration signals is not as widely used as other techniques like motor current signature analysis. Vibration analysis gives a fault diagnosis focused on the location of spectral components associated with faults. Therefore, this paper presents a comparative study of different time-frequency analysis methodologies that can be used for detecting faults in induction

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Hyacinth, Hyacinth I., Beatrice E. Gee, Jenifer H. Voeks, Robert J. Adams, and Jacqueline Hibbert. "High Frequency of RBC Transfusions in the STOP Study Was Associated with Reduction in Serum Biomarkers of Neurodegeneration, Vascular Remodeling and Inflammation." Blood 120, no. 21 (November 16, 2012): 244. http://dx.doi.org/10.1182/blood.v120.21.244.244.

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Abstract Abstract 244 Stroke is a major cause of morbidity and mortality among children with sickle cell anemia (SCA). Children with SCA at risk for stroke can be identified by transcranial Doppler (TCD) ultrasound screening for abnormally high cerebral artery blood flow velocity and strokes can be prevented by chronic packed red blood cell (RBC) transfusion. However, the mechanisms that lead to cerebral vasculopathy and stroke in SCA and that explain the beneficial effects of chronic RBC transfusions in stroke prevention are poorly understood. We have previously shown that pre-treatment serum

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Colombatti, Raffaela, Soundrie Padayachee, Corrina Macmahon, Sukhleen Momi, Claire Jane Hemmaway, Maddalena Casale, and Baba Inusa. "Cerebral Blood Flow-Velocity Is Associated with Increased Leukocyte Count and Systolic Blood Pressure in HbSS but Not HbSC." Blood 126, no. 23 (December 3, 2015): 989. http://dx.doi.org/10.1182/blood.v126.23.989.989.

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Abstract BACKGROUND Sickle Cell Disease (SCD) is the most frequent severe genetic disease worldwide. Its frequency is rising in European countries, including Italy and Ireland. In Europe Sickle SC (HbSC) is the second most common form of SCD after sickle cell anaemia (HbSS/HbSB°) and accounts for 25-30% of cases. Neurological events are among the most frequent and disabling complications in children with SCD with an important impact on quality of life, health and educational system costs (DeBaun et al., 2012). Overt and silent stroke are reported in in HbSC disease, although to a lesser extent

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Cheng, L., M. Yaeger, A. Viglione, E. Coopersmith, S. Ye, and M. Sivapalan. "Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses." Hydrology and Earth System Sciences 16, no. 11 (November 26, 2012): 4435–46. http://dx.doi.org/10.5194/hess-16-4435-2012.

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Abstract. The flow duration curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged

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Cheng, L., M. Yaeger, A. Viglione, E. Coopersmith, S. Ye, and M. Sivapalan. "Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses." Hydrology and Earth System Sciences Discussions 9, no. 6 (June 6, 2012): 7001–34. http://dx.doi.org/10.5194/hessd-9-7001-2012.

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Abstract. The Flow Duration Curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged

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Ishola, Titilope, and Charles T. Quinn. "Transcranial Doppler Peak Systolic Velocities Overestimate The Risk Of Stroke In Sickle Cell Anemia." Blood 122, no. 21 (November 15, 2013): 2240. http://dx.doi.org/10.1182/blood.v122.21.2240.2240.

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Abstract Background Children with sickle cell anemia (SCA) have a high risk of stroke that can be estimated by transcranial Doppler ultrasonography (TCD). The gold standard TCD measurement to determine the risk of primary stroke is the time-averaged mean of the maximum velocity (TAMMV) in specific intracranial arteries. Peak systolic velocity (PSV), a different TCD measurement, has been proposed as an alternative method for risk stratification, especially for imaging TCD (TCDi) techniques (Jones et al. 2005). Although PSV has been little studied for this purpose, some centers use PSV in additi

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Islam, Md Riadul, M. A. H. Akhand, Md Abdus Samad Kamal, and Kou Yamada. "Recognition of Emotion with Intensity from Speech Signal Using 3D Transformed Feature and Deep Learning." Electronics 11, no. 15 (July 28, 2022): 2362. http://dx.doi.org/10.3390/electronics11152362.

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Speech Emotion Recognition (SER), the extraction of emotional features with the appropriate classification from speech signals, has recently received attention for its emerging social applications. Emotional intensity (e.g., Normal, Strong) for a particular emotional expression (e.g., Sad, Angry) has a crucial influence on social activities. A person with intense sadness or anger may fall into severe disruptive action, eventually triggering a suicidal or devastating act. However, existing Deep Learning (DL)-based SER models only consider the categorization of emotion, ignoring the respective e

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