Relevant bibliographies by topics / WAVELET ENHANCED ICA

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'WAVELET ENHANCED ICA'

Author: Grafiati
Published: 11 September 2023
Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'WAVELET ENHANCED ICA.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "WAVELET ENHANCED ICA"

1

Chiu, Chuang-Chien, Bui Huy Hai, Shoou-Jeng Yeh, and Ken Ying-Kai Liao. "RECOVERING EEG SIGNALS: MUSCLE ARTIFACT SUPPRESSION USING WAVELET-ENHANCED, INDEPENDENT COMPONENT ANALYSIS INTEGRATED WITH ADAPTIVE FILTER." Biomedical Engineering: Applications, Basis and Communications 26, no. 05 (2014): 1450063. http://dx.doi.org/10.4015/s101623721450063x.

Full text
Abstract:
Independent component analysis (ICA) has been proven to be a powerful tool for removing artifacts from electroencephalogram (EEG) recordings in the form of blind source separation (BSS). Independent components (ICs) come from undesired sources that are mixed with the useful signal, and the assessment of such ICs allows them to be detected. But the unwanted ICs also can contain some useful information. To overcome this problem, wavelet-enhanced ICA (wICA) can be used, and this method applies a wavelet threshold for each wavelet coefficient to suppress abnormal deformation in each wavelet coeffi
APA, Harvard, Vancouver, ISO, and other styles
2

Ezilarasan, M. R., S. Vishnupriya, Thulasi Arumugam, B. Sakthi Karthi Durai, and S. Manimekalai. "Implementation of Realtime Image Fusion for Biomedical Applications Using ICA And Discrete Wavelet Transform." International Journal of Electrical and Electronics Research 12, no. 3 (2024): 836–41. http://dx.doi.org/10.37391/ijeer.120314.

Full text
Abstract:
Image fusion is an extensively used technique in various areas like computer visualization, enhanced diagnostic imaging, radio therapy, automatic object recognition, image analysis, and remote sensing. The main aim of image fusion is to combine several input images into one image containing more information than the individual images. This type of image fusion results in a new image that is easier for computers and humans to see, making it possible for additional image processing operations like object detection, segmentation, and feature extraction. This paper examines the potential applicati
APA, Harvard, Vancouver, ISO, and other styles
3

Issa, Mohamed F., and Zoltan Juhasz. "Improved EOG Artifact Removal Using Wavelet Enhanced Independent Component Analysis." Brain Sciences 9, no. 12 (2019): 355. http://dx.doi.org/10.3390/brainsci9120355.

Full text
Abstract:
Electroencephalography (EEG) signals are frequently contaminated with unwanted electrooculographic (EOG) artifacts. Blinks and eye movements generate large amplitude peaks that corrupt EEG measurements. Independent component analysis (ICA) has been used extensively in manual and automatic methods to remove artifacts. By decomposing the signals into neural and artifactual components and artifact components can be eliminated before signal reconstruction. Unfortunately, removing entire components may result in losing important neural information present in the component and eventually may distort
APA, Harvard, Vancouver, ISO, and other styles
4

Zhang, Wei, Zhongqiang Luo, Xingzhong Xiong, and Kai Deng. "An Enhanced Impulsive Noise Suppression Method Based on Wavelet Denoising and ICA for Power Line Communication." Infocommunications journal 13, no. 2 (2021): 25–31. http://dx.doi.org/10.36244/icj.2021.2.4.

Full text
Abstract:
Aiming at the problem of noise suppression in power lines, traditional noise suppression methods need to know prior knowledge and other defects. In this paper, blind source separation methods that do not need prior knowledge are selected. In the case of low signal-to-noise ratio, the basic independent component analysis algorithm has poor denoising effect. Therefore, this paper proposes a joint independent component analysis algorithm based on Wavelet denoising and Power independent component analysis (WD-PowerICA). In this work, firstly, the pseudo observation signal is constructed by weighte
APA, Harvard, Vancouver, ISO, and other styles
5

Raju, Burra. "Brain Tumor Detection Using MRI." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48988.

Full text
Abstract:
ABSTRACT - Detecting and classifying tumors in brain MR images is crucial for early diagnosis and effective treatment. Early detection improves long-term survival rates. This paper presents a new approach for accurate brain tumor segmentation and classification. First, the MR images are enhanced using an anisotropic diffusion filter. Then, an active contour model is applied to detect the tumor, providing smooth and precise contours. For classification, features from the tumor images are extracted using 2-D Daubechies wavelet transform (DWT), and the feature dimensions are reduced with Independ
APA, Harvard, Vancouver, ISO, and other styles
6

Leng, Junfa, Penghui Shi, Shuangxi Jing, and Chenxu Luo. "An Enhanced CICA Method and Its Application to Multistage Gearbox Low-frequency Fault Feature Extraction." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 2 (2020): 285–94. http://dx.doi.org/10.2174/2352096512666190130100336.

Full text
Abstract:
Background: The vibration signals acquired from multistage gearbox’s slow-speed gear with localized fault may be directly mixed with source noise and measured noise. In addition, Constrained Independent Component Analysis (CICA) method has strong immunity to the measured noise but not to the source noise. These questions cause the difficulty for applying CICA method to directly extract lowfrequency and weak fault characteristic from the gear vibration signals with source noise. Methods: In order to extract the low-frequency and weak fault feature from the multistage gearbox, the source noise a
APA, Harvard, Vancouver, ISO, and other styles
7

Zima, M., P. Tichavský, K. Paul, and V. Krajča. "Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions." Physiological Measurement 33, no. 8 (2012): N39—N49. http://dx.doi.org/10.1088/0967-3334/33/8/n39.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zia, Zahra, Ahsen Ejaz, Kai Liang Lew, et al. "The Role of Electroencephalography in Advancing Sleep Research." International Journal on Robotics, Automation and Sciences 7, no. 1 (2025): 93–103. https://doi.org/10.33093/ijoras.2025.7.1.11.

Full text
Abstract:
Electroencephalography (EEG) is fundamental in sleep research, providing critical insights into cerebral activity and significantly contributing to the diagnosis of sleep disorders. This study examines recent progress in EEG-based sleep research, emphasizing cutting-edge methods for sleep staging and disease identification. The amalgamation of machine learning and deep learning methodologies, encompassing hybrid models such as CNN-LSTM, has markedly improved the precision of sleep stage categorization and automated analysis. Enhancements in signal quality and dependability, especially by impro
APA, Harvard, Vancouver, ISO, and other styles
9

Abdubrani, Rafiuddin, Mahfuzah Mustafa, and Zarith Liyana Zahari. "A ROBUST FRAMEWORK FOR DRIVER FATIGUE DETECTION FROM EEG SIGNALS USING ENHANCEMENT OF MODIFIED Z-SCORE AND MULTIPLE MACHINE LEARNING ARCHITECTURES." IIUM Engineering Journal 24, no. 2 (2023): 354–72. http://dx.doi.org/10.31436/iiumej.v24i2.2799.

Full text
Abstract:
Physiological signals, such as electroencephalogram (EEG), are used to observe a driver’s brain activities. A portable EEG system provides several advantages, including ease of operation, cost-effectiveness, portability, and few physical restrictions. However, it can be challenging to analyse EEG signals as they often contain various artefacts, including muscle activities, eye blinking, and unwanted noises. This study utilised an independent component analysis (ICA) approach to eliminate such unwanted signals from the unprocessed EEG data of 12 young, physically fit male participants between t
APA, Harvard, Vancouver, ISO, and other styles
10

Ma, Chau Thi, Hieu Nguyen Dinh, Kien Nguyen Minh, and Long Vu Thanh. "Research on Evaluating EEG Signal Processing Methods for the Development of BCI Systems." International Journal of Religion 6, no. 1 (2025): 377–95. https://doi.org/10.61707/s51hjt17.

Full text
Abstract:
This article investigates the evaluation of EEG signal processing methods to enhance the development of Brain-Computer Interface (BCI) systems. Given the critical role of EEG signal quality in determining BCI performance, we explore the impact of various noise types—such as artifacts from eye movements, muscle activity, and electronic interference—on signal integrity. We focus on noise filtering techniques, particularly their effectiveness in preserving essential signal components while eliminating unwanted noise. Our research includes a detailed analysis of several common noise processing met
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "WAVELET ENHANCED ICA"

1

JAMIL, MD DANISH. "EEG DENOISING USING WAVELET ENHANCED ICA." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14846.

Full text
Abstract:
In this work we have presented a new approach towards wavelet enhanced ICA, we have used mMSE and kurtosis to detect the artifactual components automatically, Mahajan et al [28] displayed their performance in terms of sensitivity (90%) and specificity (98%), nMSE is good at recognizing EEG patterns because of its randomness and kurtosis is good at recognizing peaked signal because they have high kurtosis values. We compared our result with ICA based method zeroing ICA in terms of correlation, mutual information and coherence. Our result is far superior to it in all three terms, in correl
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "WAVELET ENHANCED ICA"

1

Rastogi, Aashi, and Vikrant Bhateja. "Pre-processing of Electroencephalography Signals Using Stationary Wavelet Transform-Enhanced Fixed-Point Fast-ICA." In Advances in Intelligent Systems and Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0171-2_37.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

La Foresta Fabio, Mammone Nadia, Inuso Giuseppina, Morabito Francesco C., and Azzerboni Andrea. "Multiresolution Minimization of Renyi's Mutual Information for fetal-ECG Extraction." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2009. https://doi.org/10.3233/978-1-58603-984-4-50.

Full text
Abstract:
Fetal electrocardiogram (fECG) monitoring yields important information about the fetus condition during pregnancy and it consists in collecting electrical signals by some sensors on the body of the mother. In literature, Independent Component Analysis (ICA) has been exploited to extract fECG. Wavelet-ICA (WICA), a technique that merges Wavelet decomposition and INFOMAX algorithm for Independent Component Analysis, was recently proposed to enhance fetal ECG extraction. In this paper, we propose to enhance WICA introducing MERMAID as the algorithm to perform independent component analysis becaus
APA, Harvard, Vancouver, ISO, and other styles
3

Zhou Nan, Huang Lei, Huang Jifeng, Pan Tao, Ni Yepeng, and Shan Lianhai. "Non-Contact Heart Rate Measurement Based on Facial Video." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2018. https://doi.org/10.3233/978-1-61499-927-0-818.

Full text
Abstract:
Heart rate measurement is an important means of monitoring the physiological status of the human body. A non-contact heart rate measurement method is proposed by analyzing the change of pixels. Multi-filter and sub-region method are adopted to solve the problem of the complex heart rate signal extraction result. As the independence of the RGB color model, the green component signals can be taken from the mixed signals by using Fast ICA. The main peak noise is removed by the wavelet filtering and the band-pass filter, and the heart rate is obtained in the analysis of the energy spectrum by usin
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "WAVELET ENHANCED ICA"

1

Sun, Peixuan, and Jinglin Zhou. "K-Medoids-based ICA and Wavelet-Enhanced Multi-resolution Convolutional Network for Motor Imagery EEG." In 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). IEEE, 2025. https://doi.org/10.1109/ddcls66240.2025.11065446.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Paradeshi, K. P., Research Scholar, and U. D. Kolekar. "Removal of ocular artifacts from multichannel EEG signal using wavelet enhanced ICA." In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017. http://dx.doi.org/10.1109/icecds.2017.8390150.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Mahajan, Ruhi, and Bashir I. Morshed. "Sample Entropy enhanced wavelet-ICA denoising technique for eye blink artifact removal from scalp EEG dataset." In 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2013. http://dx.doi.org/10.1109/ner.2013.6696203.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Jenkal, Wissam, Rachid Latif, Ahmed Toumanari, Azdine Dliou, and Oussama El B'charri. "Enhanced algorithm for QRS detection using discrete wavelet transform (DWT)." In 2015 27th International Conference on Microelectronics (ICM). IEEE, 2015. http://dx.doi.org/10.1109/icm.2015.7437982.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'WAVELET ENHANCED ICA' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography