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  • Open Access


    Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check

    Attia Irum1, Abdul Muiz Fayyaz1, Sara Ayub2, Mudassar Raza3, Majed Alhaisoni4, Muhammad Attique Khan5, Abdullah Alqahtani6, Heebum Kim7, Byeong-Gwon Kang7,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1265-1276, 2023, DOI:10.32604/csse.2023.032861

    Abstract An effective communication application necessitates the cancellation of Impulsive Noise (IN) from Orthogonal Frequency Division Multiplexing (OFDM), which is widely used for wireless applications due to its higher data rate and greater spectral efficiency. The OFDM system is typically corrupted by Impulsive Noise, which is an unwanted short-duration pulse with random amplitude and duration. Impulsive noise is created by humans and has non-Gaussian characteristics, causing problems in communication systems such as high capacity loss and poor error rate performance. Several techniques have been introduced in the literature to solve this type of problem, but they… More >

  • Open Access


    Image Enhancement Using Adaptive Fractional Order Filter

    Ayesha Heena1,*, Nagashettappa Biradar1, Najmuddin M. Maroof2, Surbhi Bhatia3, Arwa Mashat4, Shakila Basheer5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1409-1422, 2023, DOI:10.32604/csse.2023.029611

    Abstract Image enhancement is an important preprocessing task as the contrast is low in most of the medical images, Therefore, enhancement becomes the mandatory process before actual image processing should start. This research article proposes an enhancement of the model-based differential operator for the images in general and Echocardiographic images, the proposed operators are based on Grunwald-Letnikov (G-L), Riemann-Liouville (R-L) and Caputo (Li & Xie), which are the definitions of fractional order calculus. In this fractional-order, differentiation is well focused on the enhancement of echocardiographic images. This provoked for developing a non-linear filter mask for image… More >

  • Open Access


    Early Detection of Heartbeat from Multimodal Data Using RPA Learning with KDNN-SAE

    A. K. S. Saranya1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 545-562, 2023, DOI:10.32604/csse.2023.029975

    Abstract Heartbeat detection stays central to cardiovascular an electrocardiogram (ECG) is used to help with disease diagnosis and management. Existing Convolutional Neural Network (CNN)-based methods suffer from the less generalization problem thus; the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed. In contrast, this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders (KDNN-SAE) that computes the disease before the exact heart rate by combining features from multiple ECG Signals. Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error… More >

  • Open Access


    Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

    Bilal Shoaib1, Yasir Javed2, Muhammad Adnan Khan3,*, Fahad Ahmad4, Rizwan Majeed5, Muhammad Saqib Nawaz1, Muhammad Adeel Ashraf6, Abid Iqbal2, Muhammad Idrees7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1413-1427, 2021, DOI:10.32604/cmc.2021.015099

    Abstract For the unforced dynamical non-linear statespace model, a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article. The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems. With the help of an ortho-normal triangularization method, which relies on numerically stable givens rotation, matrix inversion causes a computational burden, is reduced. Matrix computation possesses many excellent numerical properties such as singularity, symmetry, skew symmetry, and triangularity is achieved by using this algorithm. The proposed method is validated for the prediction of stationary and… More >

  • Open Access


    Fuzzy Adaptive Filtering-Based Energy Management for Hybrid Energy Storage System

    Xizheng Zhang1,2,*, Zhangyu Lu1, Chongzhuo Tan1, Zeyu Wang1

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 117-130, 2021, DOI:10.32604/csse.2021.014081

    Abstract Regarding the problem of the short driving distance of pure electric vehicles, a battery, super-capacitor, and DC/DC converter are combined to form a hybrid energy storage system (HESS). A fuzzy adaptive filtering-based energy management strategy (FAFBEMS) is proposed to allocate the required power of the vehicle. Firstly, the state of charge (SOC) of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state, and fuzzy rules are designed to adaptively adjust the filtering time constant, to realize reasonable power allocation. Then, the positive… More >

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