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  • Open Access

    ARTICLE

    FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

    Khakoo Mal1,2,*, Tayab Din Memon1,3, Imtiaz Hussain Kalwar4, Bhawani Shankar Chowdhry5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3351-3370, 2023, DOI:10.32604/cmc.2023.032940

    Abstract It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle. The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars. In this paper, the development of simulation model of extended Kalman filter (EKF) in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track. Due to concurrent in nature, the Xilinx® System-on-Chip Zynq Field Programmable Gate Array (FPGA) device is chosen to check the onboard estimation of wheel-rail interaction parameters by using the National Instruments (NI) myRIO®More >

  • Open Access

    ARTICLE

    Medical Image Demosaicing Based Design of Newton Gregory Interpolation Algorithm

    E. P. Kannan1,*, S. S. Vinsley2, T. V. Chithra3

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1675-1691, 2022, DOI:10.32604/iasc.2022.022707

    Abstract In this paper, Field-Programmable Gate Array (FPGA) implementation-based image demosaicing is carried out. The Newton Gregory interpolation algorithm is designed based on FPGA frame work. Interpolation is the method of assessing the value of a function for any in-between value of self-regulating variable, whereas the method of computing the value of the function outside the specified range is named extrapolation. The natural images are collected from Kodak image database and medical images are collected from UPOL (University of Phoenix Online) database. The proposed algorithm is executed on using Xilinx ISE (Integrated Synthesis Environment) Design Suite 14.2 and is confirmed on… More >

  • Open Access

    ARTICLE

    FPGA Implementation of Elliptic-Curve Diffie Hellman Protocol

    Sikandar Zulqarnain Khan1,*, Sajjad Shaukat Jamal2, Asher Sajid3, Muhammad Rashid4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1879-1894, 2022, DOI:10.32604/cmc.2022.028152

    Abstract This paper presents an efficient crypto processor architecture for key agreement using ECDH (Elliptic-curve Diffie Hellman) protocol over . The composition of our key-agreement architecture is expressed in consisting of the following: (i) Elliptic-curve Point Multiplication architecture for public key generation (DESIGN-I) and (ii) integration of DESIGN-I with two additional routing multiplexers and a controller for shared key generation (DESIGN-II). The arithmetic operators used in DESIGN-I and DESIGN-II contain an adder, squarer, a multiplier and inversion. A simple shift and add multiplication method is employed to retain lower hardware resources. Moreover, an essential inversion operation is operated using the Itoh-Tsujii… More >

  • Open Access

    ARTICLE

    FPGA Implementation of 5G NR Primary and Secondary Synchronization

    Aytha Ramesh Kumar1,*, K. Lal Kishore2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1585-1600, 2022, DOI:10.32604/cmc.2022.021573

    Abstract The 5G communication systems are widely established for high-speed data processing to meet users demands. The 5G New Radio (NR) communications comprise a network of ultra-low latency, high processing speeds, high throughput and rapid synchronization with a time frame of 10 ms. Synchronization between User Equipment (UE) and 5G base station known as gNB is a fundamental procedure in a cellular system and it is performed by a synchronization signal. In 5G NR system, Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS) are used to detect the best serving base station with the help of a cell search procedure.… More >

  • Open Access

    ARTICLE

    FPGA Implementation of Deep Leaning Model for Video Analytics

    P. N. Palanisamy*, N. Malmurugan

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921

    Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of… More >

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