Search Results - (( java implication based algorithm ) OR ( using ((sparse using) OR (phase using)) algorithm ))

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  1. 1
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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  2. 2
    An improved public key cryptography based on the elliptic curve

    An improved public key cryptography based on the elliptic curve by Al-Daoud, Essam Faleh

    Published 2002
    “…Moreover, the new formula can be used more efficiently when it is combined with the suggested sparse elements algorithms. …”
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  3. 3
    On the spectra efficiency of low-complexity and resolution hybrid precoding and combining transceivers for mmWave MIMO systems

    On the spectra efficiency of low-complexity and resolution hybrid precoding and combining transceivers for mmWave MIMO systems by Uwaechia, Anthony Ngozichukwuka, Mahyuddin, Nor Muzlifah, Mohd Fadzil, Ain, Abdul) Latiff, Nurul Muazzah, Za'bah, Nor Farahidah

    Published 2019
    “…While energy-efficient hybrid analog/digital precoders and combiners designs can subdue the high pathloss inherent in mmWave channels, they assume the use of infinite- (or high-) resolution phase shifters to realize the analog precoder and combiner pair which results in high hardware cost and power consumption. …”
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  4. 4
    Evaluation of sparsifying algorithms for speech signals

    Evaluation of sparsifying algorithms for speech signals by Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya

    Published 2012
    “…Sparse representations of signals have been used in many areas of signal and image processing. …”
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    Proceeding Paper
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  5. 5
    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Moreover, sparse coding has been commonly used in recent years for the purposes of retrieving and identifying images. …”
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  6. 6
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…The research results suggested that SOM has a limitation of poor performance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). …”
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  7. 7
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…The research results suggested that SOM has a limitation of poor perfonnance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). …”
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  8. 8
    Bayesian Framework based Brain Source Localization Using High SNR EEG Data

    Bayesian Framework based Brain Source Localization Using High SNR EEG Data by Jatoi, M.A., Kamel, N., Gaho, A.A., Dharejo, F.A.

    Published 2019
    “…The localization involves two phases: forward modeling and inverse modeling. The forward modeling is carried out to model the head using various numerical techniques. …”
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  9. 9
    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field

    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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  10. 10
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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  11. 11
    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems

    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…However, such information is seldom available a priori and needs to beestimated. CS uses the prior knowledge that many physical signals are sparse and acquire them with few measurements. …”
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  12. 12
    Color video denoising using epitome and sparse coding

    Color video denoising using epitome and sparse coding by Lee, H.Y., Hoo, W.L., Chan, C.S.

    Published 2015
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  13. 13
    Removing mixture of Gaussian and Impulse noise of images using sparse coding

    Removing mixture of Gaussian and Impulse noise of images using sparse coding by Mahsa Malekzadeh, Saeed Meshgini, Reza Afrouzian, Ali Farzamnia, Sobhan Sheykhivand

    Published 2020
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  14. 14
    Rain streaks removal using total variation and sparse coding based on case based reasoning approach

    Rain streaks removal using total variation and sparse coding based on case based reasoning approach by Shorman S.M., Salam R.A., Sakinah Ali Pitchay

    Published 2024
    journal::journal article
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  15. 15
    Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm

    Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Zaharuddin, Mohamed

    Published 2024
    “…In contemporary industrial applications, the complexity of systems often makes it challenging to create precise models using first-principle approaches. Consequently, researchers have turned to data-driven modeling, which offers the key advantage of developing a mathematical model of the system entirely from the input–output data captured from an actual plant. …”
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  16. 16
    BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS

    BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS by MUNSIF, ALI JATOI

    Published 2017
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  17. 17
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  18. 18
    Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost

    Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost by Sim, Hong Seng, Ling, Wendy Shin Yie, Leong, Wah June, Chen, Chuei Yee

    Published 2023
    “…The efficiency of the algorithm is demonstrated using real stock data and the model is promising in portfolio selection in terms of generating higher expected return while maintaining good level of sparsity, and thus minimizing transaction cost.…”
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  19. 19
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…In some cases, they are quite distant and sparseness. This uniqueness of Y-STR data has become problematic in partitioning the data using the existing partitional clustering algorithms. …”
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  20. 20
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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