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Electrical Engineering: Recent submissions

  • Quantifying spatial domain explanations in BCI using earth mover's distance 
    Rajpura, Param; Cecotti, Hubert; Meena, Yogesh Kumar (Cornell University Library, 2024-05)
    Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are not fully integrated into clinical and ...
  • Towards optimising EEG decoding using post-hoc explanations and domain knowledge 
    Rajpura, Param; Meena, Yogesh Kumar (Cornell University Library, 2024-05)
    Decoding EEG during motor imagery is pivotal for the Brain-Computer Interface (BCI) system, influencing its overall performance significantly. As end-to-end data-driven learning methods advance, the challenge lies in ...
  • FeFET-based mirrorBit cell for high-density NVM storage 
    Meihar, Paritosh; Srinu, Rowtu; Saraswat, Vivek; Lashkare, Sandip; Mulaosmanovic, Halid; Singh, Ajay Kumar; Dunkel, Stefan; Beyer, Sven; Ganguly, Udayan (Institute of Electrical and Electronics Engineers (IEEE), 2024-04)
    The HfO2-based ferroelectric field-effect transistor (FeFET) has become a center of attraction for nonvolatile memory application because of their low power, fast switching speed, high scalability, and CMOS compatibility. ...
  • FP-ATM: a flexible floating point NOR adder tree macro for in-memory computing 
    Attuluri, Yathin Kumar; Chudasama, Ruchit; Prasad, Kailash; Mekie, Joycee (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    In-Memory computing (IMC) has emerged as a promising approach to address the von Neumann bottleneck in deep learning applications. This work proposes FP-ATM, a 6T SRAM-based all-digital design for multiply-accumulate (MAC) ...
  • FP-BMAC: efficient approximate floating-point bit-parallel MAC processor using IMC 
    Gajawada, Saketh; Gupta, Aryan; Prasad, Kailash; Mekie, Joycee (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    In-memory computing (IMC) has emerged as a promising solution to address the energy and performance bottlenecks of traditional von Neumann architectures. This paper presents FP-BMAC, a novel bit-parallel in-memory computing ...
  • Analysis of differential spacecraft charging using suprathermal GEO plasma particles 
    Chakrabarty, Surup; Chakrabarty, Soumyabrata; Bhattacharjee, Anirban (Institute of Electrical and Electronics Engineers (IEEE), 2023-12-11)
    This paper presents the method to analyze the differential spacecraft charging using q-non extensive Tsallis distribution to take into account the higher energy tails of suprathermal GEO space plasma particles. The work ...
  • COMPRIZE: assessing the fusion of quantization and compression on DNN hardware accelerators 
    Patel, Vrajesh; Shah, Neel; Krishna, Aravind; Issac, Tom Glint; Ronak, Abdul; Mekie, Joycee (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    The fast advancement in complex Deep Neural Network (DNN) models, along with the availability of large amounts of training data, has created a huge demand for computational resources. When these novel workloads are offloaded ...
  • Hybrid CMOS-memristor logic for boosting the power-efficiency in error tolerant applications 
    Pokharia, Monika; Prasad, Kailash; Hegde, Ravi S.; Mekie, Joycee (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    Physical unclonable functions (PUFs) based on static random access memory (SRAM) are essential in security applications, generating unique challenge-response pairs (CRPs) from manufacturing randomness. These CRPs serve as ...
  • SDR-PUF: sequence-dependent reconfigurable SRAM PUF with an exponential CRP space 
    Prasad, Kailash; Shah, Neel; Dagli, Jinay; Mekie, Joycee (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    Approximate computing is a promising paradigm for improving the power efficiency of electronic systems for error-tolerant applications such as multimedia processing, image multiplication, and machine learning. In approximate ...
  • K-means clustering with ANN based classification to predict current-voltage characteristics of advanced FETs 
    Maheshwari, Om; Vyas, Dev; Mohapatra, Nihar Ranjan (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-06)
    In this work, we proposed a novel data-based methodology using artificial neural network (ANN) based classifier to predict current-voltage (I-V) characteristics of advanced FETs. The K-means clustering is employed to cluster ...
  • Enhanced bias-compensated NLMS for adaptive DOA estimation 
    Joel, S.; Yadav, Shekhar Kumar; George, Nithin V. (Institute of Electrical and Electronics Engineers (IEEE), 2024-04)
    Adaptive techniques for estimating the direction of arrival (DOA) of signals using an array of sensors function by passing the array's captured signals through an adaptive filter. However, the input signals received by the ...
  • Chance-constrained co-optimization of peer-to-peer energy trading and distribution network operations 
    Suthar, Sachinkumar; Pindoriya, Naran M. (Elsevier, 2024-06)
    Peer-to-Peer (P2P) energy markets enable participants to trade locally produced electrical energy at a mutually agreed-upon price. Distributed Energy Resources (DERs) and flexible loads are fundamental components of P2P ...
  • Parasitic capacitance in nanosheet FETs: extraction of different components and their analytical modeling 
    Singh, Aishwarya; Maheshwari, Om; Mohapatra, Nihar Ranjan (Institute of Electrical and Electronics Engineers (IEEE), 2024-04)
    This work presents an approach to extract and analytically model the components of the parasitic capacitance in the Nanosheet FETs. The model comprehensively accounts for parallel, fringing, and junction capacitance between ...
  • Ferroelectric mirrorbit-integrated field-programmable memory array for the TCAM, storage, and in-memory computing applications 
    Meihar, Paritosh; Srinu, Rowtu; Lashkare, Sandip; Singh, Ajay Kumar; Mulaosmanovic, Halid; Deshpande, Veeresh; Dunkel, Stefan; Beyer, Sven; Ganguly, Udayan (Institute of Electrical and Electronics Engineers (IEEE), 2024-05)
    In-memory computing (IMC) on a reconfigurable architecture is the emerging field that performs an application-based resource allocation for computational efficiency and energy optimization. In this work, we propose a ...
  • Deep-learning empowered multi-objective antenna design: a polygon patch antenna case study 
    Singh, Praveen; Panda, Soumyashree S.; Hegde, Ravi S. (Institute of Electrical and Electronics Engineers (IEEE), 2024-02-28)
    We present a multi-objective inverse design approach for rapidly synthesizing antennas, leveraging a deep-learning-assisted evolutionary algorithm. A convolutional neural network (CNN) surrogate prediction model has been ...
  • A current-excitation based circuit for resistive sensors with lead resistance compensation 
    Jain, Akshit; Wani, Mohamad Idris; Lashkare, Sandip; Malik, Shahid (Institute of Electrical and Electronics Engineers (IEEE), 2024-01-22)
    IoT-assisted measurement systems form the backbone of any kind of automation system. Resistive sensors in such systems are indispensable due to the ease with which they can be interfaced and integrated with an IoT-based ...
  • Comprehensive analysis of sheet thickness scaling on the performance of nanosheet nFETs 
    Kaur, Ramandeep; Mohapatra, Nihar Ranjan (Institute of Electrical and Electronics Engineers (IEEE), 2024-03)
    In this study, we have evaluated the impact of sheet thickness scaling on the device performance of n-type nanosheet FETs (NsFETs) using k.p and Boltzmann transport equation (BTE) simulations. We have observed improved ...
  • False data injection in distribution system: attacker's perspective 
    Bhattar, Poornachandratejasvi Laxman; Pindoriya, Naran M.; Sharma, Anurag (Elsevier, 2024-07)
    The distribution system is digitizing and occupying cyberspace with the help of information and communication technologies (ICTs). It is vulnerable to cyber-attacks like false data injection (FDI) and denial-of-services ...
  • Green synthesis derived carbon nano-particles from Syzygium cumini and Ocimum tenuiflorum 
    Singh, Parul; Nair, Sreelakshmi; Jose, Ancelina; Kaushal, Charli; Sankaranarayanan, Subramanian; Saha, Jhuma (Society of Photographic Instrumentation Engineers (SPIE), 2024-01-27)
    Green chemistry of fluorescent carbon nanoparticles (CNPs) from common sources such as leaves has gained significant interest due to their strong optical properties, and high photo stability. This paper highlights a ...
  • Machine learning based source and load forecasting for efficient microgrid energy management system 
    Mehta, Pavan; Bharadwaj, Pallavi (Institute of Electrical and Electronics Engineers (IEEE), 2023-12-10)
    Globally microgrids are becoming more successful for uninterrupted power, power access in remote areas, better power quality and low carbon emissions due to integration of renewable energy sources. The major renewable ...

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