16 papers · ranked by Valyu relevance
Lukas P. A. Arts, Egon. L. van den Broek
The spectral analysis of signals is currently either dominated by the speed-accuracy trade-off or ignores a signal’s often non-stationary character. Here we introduce an open-source algorithm to calculate the fast continuous wavelet transform (fCWT). The parallel environment of fCWT separates scale-independent and…
Ali. F. Almutairi, A. Krishna
Filtered-orthogonal frequency division multiplexing (F-OFDM) is one of the most protruding multicarrier modulation (MCM) techniques for fifth-generation and beyond wireless communication. However, it possesses a high peak-to-average power ratio (PAPR), which results in its poor performance. Thus, a novel wavelet based…
Xian-Yu Wang, Cong Li, Rui Zhang, Liang Wang + 2 more
'Hai Wang'] At present, electroencephalogram (EEG) signals play an irreplaceable role in the diagnosis and treatment of human diseases and medical research. EEG signals need to be processed in order to reduce the adverse effects of irrelevant physiological process interference and measurement noise. Wavelet transform…
M. S. Priyadarshini, Mohit Bajaj, Lukas Prokop, Milkias Berhanu
Electric power utilities must ensure a consistent and undisturbed supply of power, with the voltage levels adhering to specified ranges. Any deviation from these supply specifications can lead to malfunctions in equipment. Monitoring the quality of supplied power is crucial to minimize the impact of fluctuations in…
Joseph Mathew, Natarajan Sivakumaran, P. A. Karthick, Juan Rafael Orozco-Arroyave
'Juan Rafael Orozco-Arroyave'] In this work, an attempt has been made to develop an automated system for detecting electroclinical seizures such as tonic-clonic seizures, complex partial seizures, and electrographic seizures (EGSZ) using higher-order moments of scalp electroencephalography (EEG). The scalp EEGs of the…
Eric Rawls
Time-frequency (TF) analysis of M/EEG data enables rich understanding of cortical dynamics underlying cognition, health, and disease. There are many algorithms for time-frequency decomposition of M/EEG neural data, but they are implemented in an inconsistent manner and most existing toolboxes either 1) contain only one…
Attiq Ur Rehman, Weidong Jiao, Jianfeng Sun, Muhammad Sohaib + 8 more
'Yonghua Jiang' 'Mahnoor Shahzadi' 'Muhammad Ijaz Khan' 'Ruben Puche-Panadero' 'Javier Martinez-Roman' 'Angel Sapena-Bano' 'Jordi Burriel-Valencia' 'van Khang Huynh'] This paper introduces a novel approach for detecting inter-turn short-circuit faults in rotor windings using wavelet transformation and empirical mode…
Ariel Slepyan, Michael Zakariaie, Trac Tran, Nitish Thakor + 1 more
'Erwin Peiner'] As higher spatiotemporal resolution tactile sensing systems are being developed for prosthetics, wearables, and other biomedical applications, they demand faster sampling rates and generate larger data streams. Sparsifying transformations can alleviate these requirements by enabling compressive sampling…
Rafael F. Pinheiro, Rui Fonseca-Pinto, Andrea Brunello
For preventing health complications and reducing the strain on healthcare systems, early identification of diseases is imperative. In this context, artificial intelligence has become increasingly prominent in the field of medicine, offering essential support for disease diagnosis. This article introduces an algorithm…
Chao Li, Jie Chen, Cheng Yang, Jingjian Yang + 5 more
'Pooya Davari' 'Dong Wang' 'Shilong Sun' 'Changqing Shen'] Fast and accurate fault diagnosis is crucial to transformer safety and cost-effectiveness. Recently, vibration analysis for transformer fault diagnosis is attracting increasing attention due to its ease of implementation and low cost, while the complex…
Marta Walenczykowska, Adam Kawalec, Ksawery Krenc, Janusz Dudczyk + 2 more
'Piotr Samczyński' 'Ram M. Narayanan'] This article analyses the possibility of using the Analytic Wavelet Transform (AWT) and the Convolutional Neural Network (CNN) for the purpose of recognizing the intrapulse modulation of radar signals. Firstly, the possibilities of using AWT by the algorithms of automatic signal…
Rakhi Jadhav, Anurag Mahajan
Title: Highlights 1. • The proposed design has a better compression ratio. 2. • Low reconstruction error. 3. • This design is easy to access, systematic, profitable, and not time-consuming.
Shakila Basheer, Kamred Udham Singh, Vandana Sharma, Surbhi Bhatia + 3 more
'Nilesh Pande' 'Ankit Kumar' 'Jude Hemanth'] Advancements in digital medical imaging technologies have significantly impacted the healthcare system. It enables the diagnosis of various diseases through the interpretation of medical images. In addition, telemedicine, including teleradiology, has been a crucial impact on…
Rajiv Ranjan, Prabhat Kumar, Wei Li
Of late, image compression has become crucial due to the rising need for faster encoding and decoding. To achieve this objective, the present study proposes the use of canonical Huffman coding (CHC) as an entropy coder, which entails a lower decoding time compared to binary Huffman codes. For image compression…
Ruchira Purohit, Satish Kumar, Sameer Sayyad, Ketan Kotecha
Detection of anomalies in network traffic is critical to mitigating cyber threats. This study integrates continuous wavelet transform (CWT), discrete-time Fourier transform (DTFT), short-time Fourier transform (STFT), and autoencoders to identify anomalous network behaviour. It conducts time- frequency analysis of…
Nattapol Aunsri, Prasara Jakkaew, Chanin Kuptametee, S.K.B. Sangeetha
'S.K.B. Sangeetha'] Non-linear and non-stationary signals are analyzed and processed in the time-frequency (TF) domain due to interpretation simplicity. Wigner-Ville distribution (WVD) delivers a very sharp resolution of non-stationary signals in the TF domain. However, cross-terms occur between true frequency modes…