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  1. 1
    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
    “…Hence, a new fusion framework namely, Collaborative Framework of Algorithms (CoFA) is proposed, to pursue accurate recovery of the sparse signals from few linear measurements. …”
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  2. 2
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…The simulated results and analysis demonstrate an excellent agreement between the proposed algorithm and non-Newtonian fluids flow attributes. …”
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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
    “…In addition, simulation results also reveal that the achievable rate of the proposed LrHPC algorithm is higher than those of the existing algorithms under consideration.…”
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  4. 4
    Robust correlation feature selection based support vector machine approach for high dimensional datasets

    Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

    Published 2025
    “…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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  5. 5
    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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  6. 6
    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks

    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks by Saleh, Ahmed Mohammed Shamsan

    Published 2012
    “…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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  7. 7
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…These weights are in turn used to develop new impurity functions for selecting optimal splits for each tree in a forest. …”
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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
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  17. 17
    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
    “…Therefore, this study introduced data-driven modeling for continuous-time Hammerstein models in the presence of sparse measurement data. The analysis employed the random average marine predators algorithm (RAMPA) with a tunable step-size adaptive coefficient (CF) (RAMPA-TCF), which offers significant advantages over the conventional MPA by preventing stagnation in the local optima and enhancing the balance between the exploration and exploitation stages. …”
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  18. 18
    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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  19. 19
    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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  20. 20
    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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