Search Results - (( java implementation path algorithm ) OR ( using ((sparse using) OR (phase using)) algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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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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On the spectra efficiency of low-complexity and resolution hybrid precoding and combining transceivers for mmWave MIMO systems
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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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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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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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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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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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
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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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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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
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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Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems
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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Rain streaks removal using total variation and sparse coding based on case based reasoning approach
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Identification of the continuous-time Hammerstein models with sparse measurement data using improved marine predators algorithm
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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