Search Results - signal detection algorithm

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  1. 1

    Signal detection algorithm for cognitive radio using singular value decomposition by Omar, Mohd Hasbullah, Hassan, Suhaidi, Amphawan, Angela, Awang Nor, Shahrudin

    Published 2011
    “…This paper highlights an algorithm for detecting the presence of wireless signal using the Singular Value Decomposition (SVD) technique.We simulated the algorithm to detect common digital signals in wireless communication to test the performance of the signal detector.The SVD-based signal detector was found to be more efficient in detecting a signal without knowing the properties of the transmitted signal.The performance of the algorithm is better compared to the favorable energy detection.The algorithm is suitable for blind spectrum sensing where the properties of the signal to be detected are unknown.This is also the advantage of the algorithm since any signal would interfere and subsequently affect the quality of service (QoS) of the IEEE 802.22 connection.Furthermore, the algorithm performed better in the low signalto-noise ratio (SNR) environment.…”
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    Conference or Workshop Item
  2. 2

    A novel algorithm to detect a QPSK signal with the minimum number of samples by Mohammed, Saleh, Hilmi, Sanusi, Abubakar, Adamu, Haruna, Chiroma, Edi, Sutoyo, Mungad, Mu, Tutut, Herawan

    Published 2015
    “…The results showed that the algorithm is capable of detecting a QPSK signal with minimum Bit Error Rate (BER) at signal-to-noise ratio of 7.57 dB and maximum phase distortion of PI/8.…”
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    Proceeding Paper
  3. 3

    An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition by Mohd. Hasbullah, Omar

    Published 2011
    “…The detection algorithm was developed analytically by applying the Signal Detection Theory (SDT) and the Random Matrix Theory (RMT). …”
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    Thesis
  4. 4

    Amplitude independent versus amplitude dependent muscle activity detection algorithms: a comparative study by Khalid Hameed, Husamuldeen, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

    Published 2020
    “…The amplitude dependent muscle activity detection algorithms of the surface electromyography (sEMG) signals are very sensitive to the changes in the background noise levels and the performance of these amplitude-based methods is highly deteriorated when the Signal to Noise ratio (SNR) of the sEMG signal is low. sEMG signals of deep and small muscles as well as sEMG signals recorded from patients that have neuromuscular diseases may not meet this SNR requirement which motivates the need for amplitude independent algorithms that can detect weak muscle activities. …”
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    Article
  5. 5
  6. 6

    Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

    Published 2022
    “…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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    Undergraduates Project Papers
  7. 7

    Fetal R-Wave detection in the ambulatory monitoring of maternal abdominal signal by Mohd Alauddin Mohd Ali, Crowe, J.A., Hayes-Gill, B.R.

    Published 1995
    “…The reliability of the R-wave detection is determined from information tagged to the measured R-R intervals indicating the signal condition at the time of detection. …”
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    Article
  8. 8

    Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2018
    “…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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    Article
  9. 9

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2017
    “…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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    Proceeding Paper
  10. 10

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2018
    “…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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    Article
  11. 11

    Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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    Article
  12. 12

    Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation by Moghavvemi, M., Mehrkanoon, S.

    Published 2009
    “…BSS algorithm is used to demix the EEG signal into signals with independent features. …”
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    Article
  13. 13

    Amplitude independent muscle activity detection algorithm of soft robotic glove system for hemiparesis stroke patients using single sEMG channel by Hameed, Husamuldeen Khalid

    Published 2020
    “…Many algorithms have been developed in the literature to detect muscle activities; however, most of these algorithms depend on amplitude features in the detection process. …”
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    Thesis
  14. 14

    Detection of micro emboli using signal energy and discrete fourier transform / Basil Mathew Panamkuttiyil by Basil Mathew , Panamkuttiyil

    Published 2011
    “…The designed algorithm was able to detect presence of emboli with considerable accuracy. …”
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    Thesis
  15. 15

    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

    Published 2016
    “…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
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    Article
  16. 16

    SVD-based signal detector for cognitive radio networks by Omar, Mohd. Hasbullah, Hassan, Suhaidi, Amphawan, Angela, Awang Nor, Shahrudin

    Published 2011
    “…This paper examines the implementation of the Singular Value Decomposition (SVD) method to detect the presence of wireless signal.The method is used to find the maximum and minimum eigenvalues.We simulated the algorithm using common digital signal in wireless communication namely rectangular pulse shape, raised cosine and root-raised cosine to test the performance of the signal detector.The SVD-based signal detector was found to be more efficient in sensing signal without knowing the properties of the transmitted signal.The execution time is acceptable compared to the favorable energy detection.The computational complexity of SVD-based detector is medium compared to the energy detector.The algorithm is suitable for blind spectrum sensing where the properties of the signal to be detected are unknown. …”
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    Conference or Workshop Item
  17. 17

    Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. …”
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    Article
  18. 18

    Driver drowsiness detection using different classification algorithms by Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami

    Published 2020
    “…Hence, this paper present and prove the reliability of ECG signal for drowsiness detection in classifying high accuracy ECG data using different classification algorithms.…”
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    Proceeding Paper
  19. 19

    Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

    Published 2021
    “…Thus, this project aimed to study the emotion detection through EEG signal and proposed the right algorithm to process the signal. …”
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    Final Year Project
  20. 20

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2017
    “…The resulting average accuracy is 83% for the FHR detection. The detection of the FHR from the maternal abdominal signal by the developed algorithm has also been compared with a short-term monitoring commercial instrument IFM-500 for the assessment of the reliability of the algorithm. …”
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    Article