Teager Energy Operator: A Signal Processing Approach for Detection and Classification of Power Quality Events

Mahalle, V. S.; Bonde, G. N.; Jadhao, Saurabh S.; Paraskar, Sudhir R.

doi:10.1109/icoei.2018.8553703

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…Teager energy operator is quite efficient in detecting disturbances in signals by calculating the energy of the signal [23]. It is used to estimate the true total energy of the signal that is utilized to extract TECCs.…”

Section: Teager Energy Cepstral Coefficientsmentioning

confidence: 99%

Student’s Health Exercise Recognition Tool for E-Learning Education

Shloul¹,

Gochoo²,

Alsuhibany³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Due to the recently increased requirements of e-learning systems, multiple educational institutes such as kindergarten have transformed their learning towards virtual education. Automated student health exercise is a difficult task but an important one due to the physical education needs especially in young learners. The proposed system focuses on the necessary implementation of student health exercise recognition (SHER) using a modified Quaternion-based filter for inertial data refining and data fusion as the pre-processing steps. Further, cleansed data has been segmented using an overlapping windowing approach followed by patterns identification in the form of static and kinematic signal patterns. Furthermore, these patterns have been utilized to extract cues for both patterned signals, which are further optimized using Fisher's linear discriminant analysis (FLDA) technique. Finally, the physical exercise activities have been categorized using extended Kalman filter (EKF)-based neural networks. This system can be implemented in multiple educational establishments including intelligent training systems, virtual mentors, smart simulations, and interactive learning management methods.

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Section: Teager Energy Cepstral Coefficientsmentioning

confidence: 99%

Student’s Health Exercise Recognition Tool for E-Learning Education

Shloul¹,

Gochoo²,

Alsuhibany³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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“…• Mean Teager energy [9], which is a non-linear operator and used to obtain energy of the signal based on mechanical and physical considerations. The Teager energy operator tracks the amplitude envelopes and instantaneous frequencies of the ECG signal, providing information about its energy content.…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

“…IFOA model uses MLPT and EEMD techniques for signal transformation and decompose the signal. Firefly optimization algorithm (FOA) extracts features using standard deviation, zero crossing rate, mean curve length, Hjorth parameters, mean teager energy, and log energy entropy [5][6][7][8][9] [11]. Feature reduction is also done by IFOA model by using intermittent scale-free search pattern i.e, Lévy flight style for optimal feature selection [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

An Improved Firefly Optimization Algorithm for Analysis of Arrhythmia Types

Sinnoor,

Janardhan

2023

IJRITCC

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Irregular heartbeats rhythm is the result of arrhythmia condition which can be a threat to life if not treated at the early stage. If it is necessary to know the type of arrhythmia to treat the patient appropriately. The traditional method is complex and an efficient algorithm is required to diagnose. An improved firefly optimization algorithm is proposed to analyze arrhythmia types. Four performance measures confirm the model's effectiveness and experimental evaluation shows that it achieves a sensitivity of 86.27%, accuracy of 86.14%, precision of 87.52%, and specificity of 87.37% in arrhythmia-type classification. The algorithm can effectively classify the arrhythmia types with high accuracy and specificity.

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