This work explores the age of information (AoI) in a two-user Rayleigh faded multiple input single output (MISO) Gaussian interference channel. Each transmitter samples the data from a sensor and transmits the data wi...
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ISBN:
(数字)9798331536015
ISBN:
(纸本)9798331536022
This work explores the age of information (AoI) in a two-user Rayleigh faded multiple input single output (MISO) Gaussian interference channel. Each transmitter samples the data from a sensor and transmits the data with some random probability. The evolution of AoI is modeled using a Discrete Time Markov Chain (DTMC). Average AoI is characterized in the case of two prominent interference mitigation schemes namely treating interference as noise (TIN) and successive interference cancellation (SIC). Additionally, the impact of multiple transmit antennas and random access probability on the average AoI at the receiver is analyzed.
The movement changes the underlying spatial representation of the participated mobile objects or nodes. In real world scenario, such mobile nodes can be part of any biological network, transportation network, social n...
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The scheduling community has long been interested in educational timetabling. Particularly in academia, since timetabling dictates the day to day operation of Universities, great effort has been exercised to produce h...
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Cancer continues to be a global health challenge, demanding innovative solutions to improve early detection and treatment outcomes. This research project harnesses the power of deep learning in the field of medical im...
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This paper presents a comparative study of various decision models for detecting SQL injection attacks. SQL injection remains one of the most pervasive and critical security threats to web applications, allowing attac...
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This study presents a CNN architecture aimed at increasing the accuracy of skin lesion detection by incorporating advanced techniques such as batch normalization data augmentation, dropout layers and data balancing te...
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Book flipping videos present a distinctive challenge for information extraction, requiring the identification of frames with clear text visibility during dynamic page turns. This paper introduces a novel approach to f...
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The medical education in India urgently needs advanced training tools like virtual reality (VR) to improve Objective Structured Clinical Exams (OSCEs) and National Exit Test (NExT) assessments. The SimX Virtual Maniki...
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In this work, we propose a dynamical function exchange Convolutional Neural Networks (CNN) accelerator architecture named Adaptive CNN engine (ACNNE) that can reconfigure specific convolution layer hardware blocks acc...
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ISBN:
(数字)9798350330991
ISBN:
(纸本)9798350331004
In this work, we propose a dynamical function exchange Convolutional Neural Networks (CNN) accelerator architecture named Adaptive CNN engine (ACNNE) that can reconfigure specific convolution layer hardware blocks according to model parameters at runtime. We mainly focus on exploiting reconfigurability for inferencing large-scale CNN on resource- constrained FPGAs. The proposed ACNNE can accelerate the process of convolution layers based on a nested-loop algorithm while a data buffering scheme is presented to reduce the iterations of memory accesses. As a study case, the VGG16 model was implemented on Xilinx ZU3EG MPSoC that can achieve 21.09 giga operations per second in the frequency of 100 MHz with a device resource utilization of 25% to 35%. Experiments show a single-image inference can be completed in 2.5 seconds with an average power consumption of 2.23 W, corresponding to a power efficiency of 9.46 GOPS/W.
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