G.NagaJyothi

@asst.professor

Asst.Professor and ECE
Madanapalle Institute of Technology and Science

G.NagaJyothi


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https://researchid.co/gnagajyothi
working as Asst. Professor in the ECE department at Madanapalle Institute of Technology and Science. She completed her full-time Ph.D. in VIT in 2020. She has around 16 national and International Scopus and SCI journals.

EDUCATION

Institute of Technology
M.Tech-2008-Vellore Institute of Technology
B.Tech-2006-JNTU-Ananatapore

RESEARCH, TEACHING, or OTHER INTERESTS

Hardware and Architecture, Engineering, Speech and Hearing, Electrical and Electronic Engineering
29

Scopus Publications

458

Scholar Citations

13

Scholar h-index

16

Scholar i10-index

Scopus Publications

  • Exploring the landscape of approximate subtraction methods in ASIC platform
    M. Priyadharshni, Rajermani Thinakaran, Grande Naga Jyothi, Vijayakumar Varadarajan, C. Srinivasa Murthy
    International Journal of Reconfigurable and Embedded Systems, 2025
    <p>Approximate computing has emerged as a crucial technique in modern computing, offering significant benefits for error-resilient applications. Error resilient applications include signal, image, audio processing, and multimedia. These applications will accept the errored results with some degree of tolerance. This approach allows these applications to process and embrace data that may deviate slightly from perfect accuracy. The utility of approximate computing extends to both hardware and software domains. In hardware, arithmetic units are particularly important, among that approximate subtractors have gained attention for their role in these units. A comparative study was conducted on various approximate subtractors from existing literature, considering structural analysis in all scenarios. These approximate subtractors are coded in Verilog hardware description language (HDL) and synthesized in Synopsys electronic design automation (EDA) Tool using Taiwan Semiconductor Manufacturing Company (TSMC) 65 nm technology. Out of the available choices, approximate subtractor 3 is particularly well-suited for processing higher bit data due to its reduced hardware complexity and minimal error. Notably, it outperforms exact subtractors by achieving a notable reduction of 20% in the area delay product (ADP) and 15% in the power delay product (PDP) as process innovation. These improvements highlight the efficiency and effectiveness of approximate subtractor 3, making it a compelling option for various computing applications which accept the inaccurate results.</p>
  • AA-TransDeeplabv3 + : a novel semantic segmentation framework for aerial images using adaptive and attentive based Transdeeplabv3 + with hybrid optimization technique
    P. Anilkumar, P. Venugopal, K. Lokesh, G. NagaJyothi, M. Nanda kumar
    Signal Image and Video Processing, 2025
  • Deep learning classification of diabetic retinopathy using ResNet-101 convolutional neural networks
    R. Ravindraiah, Grande Naga Jyothi, J. Pavan Royal, B. Nagavardhan Reddy, B. Nithish Kumar
    Convergence of Internet of Medical Things Iomt and Generative AI, 2025
    Diabetic Retinopathy (DR) patients suffer from chronically excessive blood sugar, which impairs retinal features. Diabetic sufferers are extra prone to this difficulty, which may cause vision loss unless caught and handled early. It is the world's sixth most common cause of eyesight loss. Therefore, in-depth studies have been demanded in this vicinity to locate new approaches to diagnosing DR ranges. Initially, dedicated fundus image recognition techniques and computational algorithms were used to identify DR, however, their usefulness in real-time clinical practice became inadequate. Convolutional Neural Networks (CNNs), one type of deep learning model, are better at predicting the prognosis of DR. The goal of this research work is to understand the overall performance of a deep-gaining knowledge model, ResNet, a deep-stage neural network, in detecting non-prescriptive and exclusive varieties of suggestible DR.
  • Enhanced diabetic retinopathy classification using inception net V3: A deep learning approach
    R. Ravindraiah, Grande Naga Jyothi, Nukala Bharath Kumar, B. Ganesh, D. Badri
    Convergence of Internet of Medical Things Iomt and Generative AI, 2025
    This study employes a novel approach for the automatic classification of Diabetic Retinopathy (DR) through a customized Inception Net V3 Convolutional Neural Network (CNN) method. DR is leading reason for visual impairment and necessitates early and accurate diagnosis for effective intervention. Leveraging deep learning, the proposed CNN model demonstrates remarkable proficiency in discerning diverse stages of DR from retinal images. The network is trained on a comprehensive dataset meticulously annotated with DR stages, ensuring robust learning and generalization. Through an extensive evaluation, this model exhibits superior performance in classifying DR severity levels, showcasing its potential as a valuable diagnostic tool. The proposed CNN architecture not only enhances classification accuracy but also facilitates interpretability, shedding light on the critical features contributing to each classification. The proposed design has been implemented in MATLAB 2023(a)
  • Energy Efficient CAM Design Using FinFET for IoT Applications
    Sandhya Pagadala, Naga Jyothi Grande
    2025 IEEE International Conference on Advanced Computing Technologies Icact 2025, 2025
    The proposed CAM architecture offers enhanced energy efficiency, making it well-suited for IoT environments like network routers, memory controllers, and data filtering systems. CAM cell has storage and comparison unit and consists of word lines, bit lines, search lines, match lines which makes less power consumption and less delay in searching data. To overcome this a new CAM cell is designed by replacing the conventional MOSFETs with the FinFETs using Gate Diffusion Technique (GDI) which helps in improving power and speed. The proposed design has been implemented in Cadence TSMC 45nm technology. The proposed design has less area and power consumption when compared with the existing designs.
  • Design and Analysis of a Super Source Follower-Based Multipath Fully Differential Operational Trans Conductance Amplifier
    Bukke Gayathri, Grande Naga Jyothi
    2025 IEEE International Conference on Advanced Computing Technologies Icact 2025, 2025
    This work presents about the development and evaluation of a multipath fully differential operational transconductance amplifier (OTA) implemented in 45nm CMOS technology, focusing on enhancing gain, speed, accuracy bandwidth, and addressing the needs of modern analog, bio-medical and mixed-signal applications. By using the super source follower in the structure to improve the important features like bandwidth, larger dc gain, linearity, higher gain, by using multi path these can be reducing the distortion power consumption while saving the power. The super source follower is employed to provide low output impedance and high buffering make the architecture is suitable for high speed and analog signal processing applications. Simulations shows better linearity, higher band width, and improved CMR value as compared to the traditional OTA design. The OTA operates from a 1V supply voltage and achieve high gain 65 dB, -3 dB bandwidth of 250MHz. this makes the amplifier a great selection for modern low power and high-speed applications like Analog to digital converter, medical applications.
  • Automatic Analysis and Detection of Multi-Channel ECG Signals Using Neural Network
    G. Naga Jyothi, R. Kiran Kumar, B. Subbarayudu
    Lecture Notes in Networks and Systems, 2025
  • CNN-Based Voice Recognition by Self-Governing Robots to Improve Computer-Human Communication
    Ben Sujin. B
    Advances in Nonlinear Variational Inequalities, 2025
    Robots must have the ability to recognize human emotions to engage with individuals and to plan their movements autonomously. Nonverbal signals encompassing pitch, loudness, spectrum, and speech speed are successful methods for transmitting emotions to most individuals. Provided this situation, a machine could have the capability of qualified figure out emotions by deploying the traits of spoken communication, and these potentially propagate vital information concerning the speaker's emotional state. More precisely, a combination of numerous facial action units can be employed to describe a human's emotion. In this paper, we propose a deep Convolutional Neural Network-based system that can identify sentiments in real-time and with a high accuracy rate. This investigation establishes an entirely novel speech-emotion detection system founded on Convolutional Neural Networks (CNNs). With the support of a top-tier GPU, a model is developed and nourished raw speech from a specific set for training, classification, and testing purposes. We further analyze the speech data and incorporate the information from the visual and audio sources to enhance the recognition system's accuracy. The benefits of the proposed method for emotion identification and the implications of blending visual and aural suggestions are made clear by the experimental results. Convolutional neural networks (CNNs) are taught on grayscale images from the softmax dataset in the present work. To acquire the best accuracy, we experimented with different baselines and max pooling layers, finally acquiring 89.98% accuracy. Dropout is one approach we have used to ward off overfitting.
  • Energy Efficient Compact Approximate Multiplier for Error-Resilient Applications
    Charan Kumar G, Naga Jyothi Grande, Vijetha Kura, Sai Sandeep Boksam, Bharath Kumar Gooty
    International Conference on Intelligent Communication Networks and Computational Techniques Icicnct 2025, 2025
    In error-resilient applications like image processing, machine learning, and the Internet of Things, where small computational errors are tolerable in exchange for lower power and latency, approximate multipliers are being used more and more. It is difficult for traditional multipliers to balance accuracy, power, and performance. In this paper, a CarryOptimized Approximate Multiplier utilising Carry Approximation Circuits(CAC) and Approximate Carry Masking Logic Cells (ACMLC) is presented. While CAC further optimises carry computation at higher-order stages, ACMLC minimises critical route delay by masking carry propagation in partial products. When combined, these methods reduce hardware complexity without sacrificing accuracy noticeably. When compared to traditional multipliers, simulation and synthesis results demonstrate notable improvements in power consumption, latency, and area. With reasonable error measurements for applications involving approximation computation, the solution was able to reduce crucial delay by 25 % and save up to 30 % to 40 % on power. The suggested design is ideal for low-power, high- speed approximation computing systems because it effectively strikes a compromise between accuracy and efficiency.
  • Development and Assessment of a Four-Element Ultra-Wideband (UWB) MIMO Antenna System for 5G Implementations
    G.Mahammed Rafi, NagaJyothi. Grande, K. Naveen, R. Harish, P. Venkatesh
    2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024
    In this paper, we provide a new method for building a dual-entry, dual-output Ultra-wide band (UWB) Multiple Input Multiple Output (MIMO) antenna in this paper. The primary goal of the research is to examine the characteristics built into this specific UWB antenna design. In order to guarantee optimal MIMO system performance with the least amount of space between radiating components, the study places a strong emphasis on the application of an isolation technique. The design also attempts to maintain a small overall size while optimizing the performance of both antennas. A well-designed meta-material is incorporated into the suggested technique decrease the connection between the antennas. To improve a number of metrics, including as S parameters, radiation characteristics, Multivariate Efficiency Diversity Gain Envelope Correlation Coefficient (ECC), splitring resonators (SRR) are positioned strategically on the antenna patch plane. The transmission rate is increased when SRR is used.
  • BINAURAL HEARING AID NOISE REDUCTION USING AN EXTERNAL MICROPHONE
    Innovations in Computational Intelligence Big Data Analytics and Internet of Things, 2024
  • Utilization of IoT-assisted computational strategies in wireless sensor networks for smart infrastructure management
    K. M Karthick Raghunath, Manjula Sanjay Koti, R. Sivakami, V. Vinoth Kumar, Grande NagaJyothi, V. Muthukumaran
    International Journal of System Assurance Engineering and Management, 2024
  • Enhancing Network Forensic and Deep Learning Mechanism for Internet of Things Networks
    J. Avanija, K. E. N. Kumar, Ch Usha Kumari, G. N. Jyothi, Srujan Raju, Reddy Madhavi
    Journal of Scientific and Industrial Research, 2023
  • High-Speed Low Area 2D FIR Filter Using Vedic Multiplier
    Grande Nagajyothi, G. Pavan Kumar, Budati Suresh Kumar, B. P. Deepak Kumar, A. K. Damodaram
    Lecture Notes in Networks and Systems, 2023
  • Breast Cancer Detection Using Deep Learning Model
    Aliya Thaseen, Raheem Unnisa, Naheed Sultana, K. Reddy Madhavi, Grande. NagaJyothi, S. Kirubakaran
    Lecture Notes in Networks and Systems, 2023
  • Multiple Degradation Skilled Network for Infrared and Visible Image Fusion Based on Multi-Resolution SVD Updation
    Gunnam Suryanarayana, Vijayakumar Varadarajan, Siva Ramakrishna Pillutla, Grande Nagajyothi, Ghamya Kotapati
    Mathematics, 2022
  • Designing a Fuzzy Q-Learning Power Energy System Using Reinforcement Learning
    Avanija J., Suneetha Konduru, Vijetha Kura, Grande NagaJyothi, Bhanu Prakash Dudi, Mani Naidu S.
    International Journal of Fuzzy System Applications, 2022
  • ASIC implementation of linear equalizer using adaptive FIR filter
    Grande Naga Jyothi, Anusha Gorantla, Thirumalesu Kudithi
    International Journal of E Collaboration, 2020
  • ASIC implementation of distributed arithmetic based FIR filter using RNS for high speed DSP systems
    Grande Naga Jyothi, Kishore Sanapala, A. Vijayalakshmi
    International Journal of Speech Technology, 2020
  • High speed low area OBC DA based decimation filter for hearing aids application
    Grande NagaJyothi, Sriadibhatla Sridevi
    International Journal of Speech Technology, 2020
  • ASIC Implementation of Fixed-Point Iterative, Parallel, and Pipeline CORDIC Algorithm
    Grande Naga Jyothi, Kundu Debanjan, Gorantla Anusha
    Advances in Intelligent Systems and Computing, 2020
  • High speed and low area decision feed-back equalizer with novel memory less distributed arithmetic filter
    Grande NagaJyothi, Sriadibhatla Sridevi
    Multimedia Tools and Applications, 2019
  • Low power design of 2–4 and 4–16 line decoders
    Grande Naga Jyothi, , Gorantla Anusha, Debanjan Kunda, , and
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • ASIC implementation of low power, area efficient adaptive FIR filter using pipelined DA
    Grande Naga Jyothi, Sridevi Sriadibhatla
    Lecture Notes in Electrical Engineering, 2019
  • High Speed FinFET Traff Comparator Based Function Generator
    Debanjan Kundu, Sonali Guin, Grande NagaJyothi, Sriadibhatla Sridevi
    7th IEEE International Conference on Computation of Power Energy Information and Communication Iccpeic 2018, 2018
  • A low power 10 bit 50-MS/s sample and hold OTA amplifier
    R. Sakthivel, Grande Naga Jyothi, N. Dilip Kumar
    ACM International Conference Proceeding Series, 2018
  • Low power, low area adaptive finite impulse response filter based on memory less distributed arithmetic
    Grande Naga Jyothi, Sriadibhatla Sridevi
    Journal of Computational and Theoretical Nanoscience, 2018
  • ASIC implementation of shared LUT based distributed arithmetic in FIR Filter
    Naga Jyothi Grande, Sriadibhatla Sridevi
    2017 International Conference on Microelectronic Devices Circuits and Systems Icmdcs 2017, 2017
  • Distributed arithmetic architectures for FIR filters-A comparative review
    Grande NagaJyothi, Sriadibhatla SriDevi
    Proceedings of the 2017 International Conference on Wireless Communications Signal Processing and Networking Wispnet 2017, 2017

RECENT SCHOLAR PUBLICATIONS

  • Design and Analysis of a Super Source Follower-Based Multipath Fully Differential Operational Trans Conductance Amplifier
    B Gayathri, GN Jyothi
    2025 IEEE International Conference on Advanced Computing Technologies (ICACT) , 2026
    2026
    Citations: 1
  • Energy Efficient CAM Design Using FinFET for IoT Applications
    S Pagadala, NJ Grande
    2025 IEEE International Conference on Advanced Computing Technologies (ICACT … , 2026
    2026
    Citations: 1
  • Energy Efficient Compact Approximate Multiplier for Error-Resilient Applications
    C Kumar G, NJ Grande, V Kura, SS Boksam, BK Gooty
    2025 International Conference on Intelligent Communication Networks and … , 2025
    2025
    Citations: 1
  • Exploring the landscape of approximate subtraction methods in ASIC platform
    M. Priyadharshni, Vijayakumar Varadarajan,Grande Naga Jyothi
    International Journal of Reconfigurable and Embedded Systems (IJRES) 14 (2 … , 2025
    2025
  • Automatic Analysis and Detection of Multi-Channel ECG Signals Using Neural Network
    G Naga Jyothi, RK Kumar, B Subbarayudu
    International Conference on Innovations in Bio-Inspired Computing and … , 2025
    2025
  • AA-TransDeeplabv3+: a novel semantic segmentation framework for aerial images using adaptive and attentive based Transdeeplabv3+ with hybrid optimization technique
    P Anilkumar, P Venugopal, K Lokesh, G NagaJyothi, M Nanda Kumar
    Signal, Image and Video Processing 19 (3), 225 , 2025
    2025
    Citations: 3
  • Novel Synchronous Counters Using Flip Flops for Low Power Applications
    A Swathi, T Devaraju, K Sandeep Kumar, K Bhavya, Y Poornima, ...
    International Conference on Intelligent Healthcare and Computational Neural … , 2025
    2025
  • A Novel Low Complexity SLM for PAPR Reduction in OFDM
    D Bhavana, SP Devulapalli, G Naga Jyothi, TN Prasad, J Rajyalakshmi
    International Conference on Intelligent Healthcare and Computational Neural … , 2025
    2025
    Citations: 1
  • Real Time structural Health Monitoring System Using IOT and AI
    GN Jyothi
    Patent , 2025
    2025
  • Deep Learning Classification of Diabetic Retinopathy Using ResNet-101 Convolutional Neural Networks
    R Ravindraiah, GN Jyothi, JP Royal, BN Reddy, BN Kumar
    Convergence of Internet of Medical Things (IoMT) and Generative AI, 417-438 , 2025
    2025
  • Enhanced Diabetic Retinopathy Classification Using Inception Net V3: A Deep Learning Approach
    R Ravindraiah, GN Jyothi, NB Kumar, B Ganesh, D Badri
    Convergence of Internet of Medical Things (IoMT) and Generative AI, 267-290 , 2025
    2025
  • CNN based Voice Recognition by self governing Robots to Improve computer-Human Communication
    DGNJ M.Sakthivel
    Advances in Nonlinear Variational Inequalities 28 (2), 128-134 , 2025
    2025
  • Development and Assessment of a Four-Element Ultra-Wideband (UWB) MIMO Antenna System for 5G Implementations
    GM Rafi, NJ Grande, K Naveen, R Harish, P Venkatesh
    2024 3rd International Conference on Artificial Intelligence For Internet of … , 2024
    2024
  • Binaural Hearing aid Noise Reduction Using an External Microphone
    GN Jyothi, K Vijetha, KR Madhavi, K Suneetha, SS Chakravarthi
    2024
  • Utilization of IoT-assisted computational strategies in wireless sensor networks for smart infrastructure management
    KM Karthick Raghunath, MS Koti, R Sivakami, V Vinoth Kumar, ...
    International Journal of System Assurance Engineering and Management 15 (1 … , 2024
    2024
    Citations: 59
  • Enhancing network forensic and deep learning mechanism for internet of things networks
    J Avanija, KEN Kumar, CU Kumari, GN Jyothi, KS Raju, KR Madhavi
    Journal of Scientific & Industrial Research (JSIR) 82 (05), 522-528 , 2023
    2023
    Citations: 28
  • High-speed low area 2D FIR filter using vedic multiplier
    G Nagajyothi, GP Kumar, BS Kumar, BPD Kumar, AK Damodaram
    Proceedings of Third International Conference on Advances in Computer … , 2023
    2023
    Citations: 23
  • Breast cancer detection using deep learning model
    A Thaseen, R Unnisa, N Sultana, KR Madhavi, G NagaJyothi, ...
    Proceedings of Third International Conference on Advances in Computer … , 2023
    2023
    Citations: 24
  • Multiple degradation skilled network for infrared and visible image fusion based on multi-resolution svd updation
    G Suryanarayana, V Varadarajan, SR Pillutla, G Nagajyothi, G Kotapati
    Mathematics 10 (18), 3389 , 2022
    2022
    Citations: 14
  • Designing a fuzzy Q-learning power energy system using reinforcement learning
    J Avanija, S Konduru, V Kura, G NagaJyothi, BP Dudi
    International Journal of Fuzzy System Applications (IJFSA) 11 (3), 1-12 , 2022
    2022
    Citations: 10

MOST CITED SCHOLAR PUBLICATIONS

  • Distributed arithmetic architectures for fir filters-a comparative review
    G NagaJyothi, S SriDevi
    2017 International Conference on Wireless Communications, Signal Processing … , 2017
    2017
    Citations: 69
  • Utilization of IoT-assisted computational strategies in wireless sensor networks for smart infrastructure management
    KM Karthick Raghunath, MS Koti, R Sivakami, V Vinoth Kumar, ...
    International Journal of System Assurance Engineering and Management 15 (1 … , 2024
    2024
    Citations: 59
  • ASIC implementation of distributed arithmetic based FIR filter using RNS for high speed DSP systems
    GN Jyothi, K Sanapala, A Vijayalakshmi
    International Journal of Speech Technology, 1-6 , 2020
    2020
    Citations: 49
  • High speed and low area decision feed-back equalizer with novel memory less distributed arithmetic filter
    G NagaJyothi, S Sridevi
    Multimedia Tools and Applications 78 (23), 32679-32693 , 2019
    2019
    Citations: 36
  • Enhancing network forensic and deep learning mechanism for internet of things networks
    J Avanija, KEN Kumar, CU Kumari, GN Jyothi, KS Raju, KR Madhavi
    Journal of Scientific & Industrial Research (JSIR) 82 (05), 522-528 , 2023
    2023
    Citations: 28
  • High speed low area OBC DA based decimation filter for hearing aids application
    G NagaJyothi, S Sridevi
    International Journal of Speech Technology 23 (1), 111-121 , 2020
    2020
    Citations: 27
  • Breast cancer detection using deep learning model
    A Thaseen, R Unnisa, N Sultana, KR Madhavi, G NagaJyothi, ...
    Proceedings of Third International Conference on Advances in Computer … , 2023
    2023
    Citations: 24
  • High-speed low area 2D FIR filter using vedic multiplier
    G Nagajyothi, GP Kumar, BS Kumar, BPD Kumar, AK Damodaram
    Proceedings of Third International Conference on Advances in Computer … , 2023
    2023
    Citations: 23
  • Asic implementation of low power, area efficient adaptive fir filter using pipelined da
    G Naga Jyothi, S Sriadibhatla
    Microelectronics, Electromagnetics and Telecommunications: Proceedings of … , 2018
    2018
    Citations: 22
  • Asic implementation of shared lut based distributed arithmetic in fir filter
    NJ Grande, S Sridevi
    2017 International conference on microelectronic devices, Circuits and … , 2017
    2017
    Citations: 20
  • Asic implementation of linear equalizer using adaptive fir filter
    GN Jyothi, A Gorantla, T Kudithi
    International Journal of e-Collaboration (IJeC) 16 (4), 59-71 , 2020
    2020
    Citations: 18
  • Low power, low area adaptive finite impulse response filter based on memory less distributed arithmetic
    GN Jyothi, S Sridevi
    Journal of Computational and Theoretical Nanoscience 15 (6-7), 2003-2008 , 2018
    2018
    Citations: 15
  • Multiple degradation skilled network for infrared and visible image fusion based on multi-resolution svd updation
    G Suryanarayana, V Varadarajan, SR Pillutla, G Nagajyothi, G Kotapati
    Mathematics 10 (18), 3389 , 2022
    2022
    Citations: 14
  • ASIC implementation of fixed-point iterative, parallel, and pipeline CORDIC algorithm
    G Naga Jyothi, K Debanjan, G Anusha
    Soft Computing for Problem Solving: SocProS 2018, Volume 1, 341-351 , 2019
    2019
    Citations: 11
  • Designing a fuzzy Q-learning power energy system using reinforcement learning
    J Avanija, S Konduru, V Kura, G NagaJyothi, BP Dudi
    International Journal of Fuzzy System Applications (IJFSA) 11 (3), 1-12 , 2022
    2022
    Citations: 10
  • High speed finfet traff comparator based function generator
    D Kundu, S Guin, G NagaJyothi, S Sridevi
    2018 International Conference on Computation of Power, Energy, Information … , 2018
    2018
    Citations: 10
  • Design of FINFET based DRAM cell for low power applications
    GN Jyothi, G Anusha, ND Kumar, D Kundu
    Computer-Aided Developments: Electronics and Communication, 35-43 , 2019
    2019
    Citations: 7
  • A low power 10 bit 50-ms/s sample and hold ota amplifier
    R Sakthivel, GN Jyothi, ND Kumar
    Proceedings of the 2018 International Conference on Communication … , 2018
    2018
    Citations: 4
  • AA-TransDeeplabv3+: a novel semantic segmentation framework for aerial images using adaptive and attentive based Transdeeplabv3+ with hybrid optimization technique
    P Anilkumar, P Venugopal, K Lokesh, G NagaJyothi, M Nanda Kumar
    Signal, Image and Video Processing 19 (3), 225 , 2025
    2025
    Citations: 3
  • Low Power Design of 2–4 and 4–16 Line Decoders
    GNJ Debanjan K, G Anusha
    International Journal of Innovative Technology and Exploring Engineering … , 2019
    2019
    Citations: 3