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An improved self organizing map using jaccard new measure for textual bugs data clustering
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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Thesis -
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An improved self organizing map using jaccard new measure for textual bugs data clustering
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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3
Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
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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Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems
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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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Counting roots of the Polynomial systems by using mixed volume of the Newton polytopes / Nur Suhailah Norazhar, Nur Ain Sofiya Zainuri and Nor Suhada Mohd Rosdi
Published 2024“…These sparse matrices are then used to generate the determinant by using Maple 2015. …”
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Student Project -
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
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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Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels
Published 2019“…Thus, a new algorithm namely, generalized quasi-block simultaneous orthogonal matching pursuit (gQBSO), is introduced to solve the problem by providing sparse signal reconstruction solution. …”
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Article -
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A Spectral Proximal Methodforsparse Optimisation On Underdetermined Linear Systems
Published 2022“…Using the Lagrangian method, this problem is transformed into an unconstrained optimisation problem. …”
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Final Year Project / Dissertation / Thesis -
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Quantum Processing Framework And Hybrid Algorithms For Routing Problems
Published 2010“…The designed hybrid architecture and framework were tested using the above quantum algorithms and the existing quantum algorithms. …”
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Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…High performance computing is widely use in diverse industries and well known as an efficient solver of grand challenge problems. …”
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Book Section -
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Speech enhancement in non-stationary noise using compressive sensing
Published 2016“…Compressive sensing using GPSR technique is then incorporated by randomly selected the sparse signal of unconstrained problem with suitable basis and reconstruct the noiseless distortion to the enhanced speech. …”
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Proceeding Paper -
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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