Browsing by Author "Rahul, R."

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    Hardware Accelerator for Object Detection using Tiny YOLO-v3
    (Institute of Electrical and Electronics Engineers Inc., 2021) Sharma, M.; Rahul, R.; Madhusudan, S.; Deepu, S.P.; Sumam David, S.
    For applications that require object detection to be performed in real-time, this paper presents a custom hardware accelerator, implementing state of the art Tiny YOLO-v3 algorithm. The proposed architecture achieves a reasonable tradeoff between the speed of computation (measured in frames per second or FPS) and the hardware resources required. Each CNN layer is pipelined and parameterized to make the complete design re-configurable. The proposed hardware accelerator was synthesized using the SCL(Semi-Conductor Laboratory, India) 180 nm CMOS process and also using Vivado Xilinx software with Virtex Ultrascale+ FPGA as the target device. The pipelined architecture, along with other architectural novelties, provided a higher frame-rate of 32.1 FPS and a performance of 166.4 GOPS at 200 MHz clock frequency. © 2021 IEEE.
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    Sensor Fusion for Operational Mode Shape Analysis of Multi DoF Systems
    (2018) Rahul, R.; Rajpal, R.; Aditya, Raman, Kuchibhatla, S.; Gangadharan, K.V.
    This paper presents an experimental approach to study the dynamic behavior of a multi DOF system by sensor fusion technique. An experimental model is designed and developed to simulate real dynamic problem. Frequency response function (FRF) is obtained by conducting impact hammer test from which natural frequencies of the system are identified. Mode shapes are analyzed using forced vibration test at selected frequency zones. This study illustrates the benefits of using sensor fusion for the study of behavior of complex dynamic systems. � 2018 Elsevier Ltd.
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    Sensor Fusion for Operational Mode Shape Analysis of Multi DoF Systems
    (Elsevier Ltd, 2018) Rahul, R.; Rajpal, R.; Kuchibhatla, S.A.R.; Gangadharan, K.V.
    This paper presents an experimental approach to study the dynamic behavior of a multi DOF system by sensor fusion technique. An experimental model is designed and developed to simulate real dynamic problem. Frequency response function (FRF) is obtained by conducting impact hammer test from which natural frequencies of the system are identified. Mode shapes are analyzed using forced vibration test at selected frequency zones. This study illustrates the benefits of using sensor fusion for the study of behavior of complex dynamic systems. © 2018 Elsevier Ltd.