Search Results - (( probable distribution sensor algorithm ) OR ( parameter realization path algorithm ))*

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  1. 1
    All-pass filtered x least mean square algorithm for narrowband active noise control

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications.…”
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  2. 2
    Optimization algorithms for multipath transfer over asymmetric paths using concurrent multipath transfer stream control transmission protocol

    Optimization algorithms for multipath transfer over asymmetric paths using concurrent multipath transfer stream control transmission protocol by Abass, Abdulridha Hanash

    Published 2016
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  3. 3
    Energy Efficient LEACH (EE-LEACH) Routing Algorithm for Wireless Sensor Networks

    Energy Efficient LEACH (EE-LEACH) Routing Algorithm for Wireless Sensor Networks by Pillay, Kosheila Sundram

    Published 2019
    “…Therefore, this research work proposes an energy-efficient LEACH (EE-LEACH) algorithm to elect CHs based on residual energy, RSSI, and random probability to distribute the load evenly among the CHs. …”
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  4. 4
    Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance

    Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance by Akbari, M., Reza, A.W., Noordin, K.A., Dimyati, K., Manesh, M.R., Hindia, M.N.

    Published 2016
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  5. 5
    Energy efficient cluster head distribution in wireless sensor networks

    Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

    Published 2013
    “…For network clustering, the distribution of CH selection directly influences the networks lifetime. …”
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  6. 6
    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel

    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel by Zamri, Ruzaidi

    Published 2016
    “…For the purpose of this study, multiple ANFIS or MANFIS have been selected to predict optimum parameter for polishing parameters. Polishing parameter data can be generated by using MANFIS to predict optimum polishing parameters such as grit size, polishing time and polishing force in order to perform polishing process. …”
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  7. 7
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In comparison, WISDM utilizes an accelerometer sensor embedded in Android smartphone. Meanwhile, PAMAP2 utilizes an accelerometer sensor equipped with three Inertial Measurement Unit (IMU) devices attached to three different placements. …”
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  8. 8
    EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS

    EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS by ARSHAD, MUHAMMAD AYAZ ARSHAD

    Published 2011
    “…Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. …”
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  9. 9
    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels

    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels by Uwaechia, Anthony Ngozichukwuka, Mahyuddin, Nor Muzlifah, Ain, Mohd Fadzil, Abdul Latiff, Nurul Muazzah, Za'bah, Nor Farahidah

    Published 2019
    “…., modified CE-SBEM) can improve the resolution of the angles of departures (AoDs) information to represent the downlink with far fewer parameter dimensions, since the AoDs are much slower than path gains. …”
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  10. 10
    Prediction of rice biomass using machine learning algorithms

    Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

    Published 2022
    “…The Q-TESI, C-TESI, and L-TESI overcame the LN-TESI in retaining the features’ original probability distribution, minimising the augmentation loss, reducing the VIF, increasing the rs, and decreasing the DNN under- and overfitting. …”
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