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  1. 1
    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.

    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

    Published 2022
    “…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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  2. 2
    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering

    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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  3. 3
    A parallel-model speech emotion recognition network based on feature clustering

    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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  4. 4
    Parallel form of the pipelined intermediate architecture for two-dimensional discrete wavelet transform

    Parallel form of the pipelined intermediate architecture for two-dimensional discrete wavelet transform by Koko I., Saeed, H., Agustiawan

    Published 2009
    “…In this paper, we explore parallelism in order to best meet real-time applications of 2-D DWT with demanding requirements in terms of speed, throughput, and power consumption. …”
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  5. 5
    Parallel batch self-organizing map on graphics processing unit using CUDA

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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  6. 6
    Parallel batch self-organizing map on graphics processing unit using CUDA

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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  7. 7
    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network

    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

    Published 2005
    “…The efficient combination of simulated annealing algorithm with the best heuristic algorithms gave much better result in a very minimal time. …”
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  8. 8
    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance.

    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance. by Mohammad Alkhatib, Jaafar, Azmi, Md Said, Mohamad Rushdan, Ahmad Zukarnain, Zuriati

    Published 2012
    “…Hardware implementations with target FPGA for GF (p) Montgomery ECC are also presented. The best performance level was achieved when parallelizing Montgomery ECC computations to eight parallel multipliers (PM) using homogeneous coordinates. …”
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  9. 9
    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance.

    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance. by Alkhatib, Mohammad, Jaafar, Azmi, Md Said, Mohamad Rushdan, Ahmad Zulkarnain, Zuriati

    Published 2013
    “…Hardware implementations with target FPGA for GF (p) Montgomery ECC are also presented. The best performance level was achieved when parallelizing Montgomery ECC computations to eight parallel multipliers (PM) using homogeneous coordinates. …”
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  10. 10
    Enhancing Secure Sockets Layer Bulk Data Trnsfer Phase Performance With Parallel Cryptography Algorithm

    Enhancing Secure Sockets Layer Bulk Data Trnsfer Phase Performance With Parallel Cryptography Algorithm by Mohammed Alaidaros, Hashem

    Published 2007
    “…Based on the performance simulations, the new parallel algorithm gained speedup of 1.74 with 85% efficiency over the current sequential algorithm. …”
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  11. 11
    Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory

    Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory by Vel Arjunan, Satya Nanda

    Published 2003
    “…In order to reduce the computational demand when training with large data of proteins, an interface was developed using the data parallel approach to parallelize the training phase of the classifier and other accompanying methods such as data clustering algorithms. …”
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  12. 12
    An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System

    An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System by Mahmoud, Thair Sh.

    Published 2009
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  13. 13
    Design and performance evaluation of parallel elliptic curve cryptosystem with GF(P) projective coordinates

    Design and performance evaluation of parallel elliptic curve cryptosystem with GF(P) projective coordinates by Hussein Fayiz, Mohammad Al-Khatib

    Published 2012
    “…The best performance level was achieved using homogeneous coordinates. …”
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  14. 14
    Parallel processing in Compute Unified Device Architecture (CUDA) for energy saving glass

    Parallel processing in Compute Unified Device Architecture (CUDA) for energy saving glass by Shibghatullah, Abdul Samad, Xia, Khoo Wen, Azmin, Farah Ayuni, Mohd Johar, Fauzi

    Published 2014
    “…One way to allow more useful signals to go through the glass is by using complex shape coating structure. …”
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  15. 15
    Accelerating DNA sequence alignment based on smith waterman algorithm using recursive variable expansion / Muhamad Faiz Ismail

    Accelerating DNA sequence alignment based on smith waterman algorithm using recursive variable expansion / Muhamad Faiz Ismail by Ismail, Muhamad Faiz

    Published 2014
    “…Finally, we validate the proposed DP framework using the Smith-Waterman (SW) algorithm, which is a widely used, computation and data intensive application in bioinformatics. …”
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  16. 16
    The feature parallelism model of visual recognition

    The feature parallelism model of visual recognition by Hassan, Marwa Yousif, Shuriye, Abdi Omar, Hassan Abdalla Hashim, Aisha, Salami, Momoh Jimoh Eyiomika, Khalifa, Othman Omran

    Published 2017
    “…First, its accuracy rate and training time were compared to those of DeepFace, a leading industry algorithm for face recognition. Both models were trained using ImageNet object recognition dataset. …”
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  17. 17
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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  18. 18
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…The best-performing classifiers were then combined in an ensemble, using probabilistic voting for decision combination. …”
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  19. 19
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. This study integrates the Black-winged Kite Algorithm (BKA), Finite Element Analysis (FEA), Backpropagation Neural Network (BPNN), and response surface optimization techniques. …”
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  20. 20
    CUDA implementation of fractal image compression

    CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

    Published 2023
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