Search Results - (( java implementation success algorithm ) OR ( using sparse using algorithm ))
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1
An improved public key cryptography based on the elliptic curve
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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Thesis -
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Evaluation of sparsifying algorithms for speech signals
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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Pairwise testing tools based on hill climbing algorithm (PTCA)
Published 2014“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Undergraduates Project Papers -
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…Java Media Framework library and the RTP protocol for audio transmission were used as development tools.The developed system designed in this thesis together with experimental results proved that the system could be implemented successfully. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Moreover, sparse coding has been commonly used in recent years for the purposes of retrieving and identifying images. …”
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Article -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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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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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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9
Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field
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
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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Rain streaks removal using total variation and sparse coding based on case based reasoning approach
Published 2024journal::journal article -
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Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm
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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An approach for cross-site scripting detection and removal based on genetic algorithms.
Published 2014“…The proposed approach is, so far, only implemented and validated on Java-based Web applications, although it can be implemented in other programming languages with slight modifications. …”
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Conference or Workshop Item -
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Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost
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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Article -
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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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20
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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