Kumari Jyoti

ORCID: 0009-0003-9370-9229
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About
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Research Areas
  • Advanced Memory and Neural Computing
  • Neural dynamics and brain function
  • Photoreceptor and optogenetics research
  • Crystallization and Solubility Studies
  • X-ray Diffraction in Crystallography
  • Neuroscience and Neural Engineering
  • Data Mining Algorithms and Applications
  • Advanced biosensing and bioanalysis techniques
  • CCD and CMOS Imaging Sensors
  • Machine Learning in Healthcare
  • Synthesis of Tetrazole Derivatives
  • Metal-Organic Frameworks: Synthesis and Applications
  • Metal complexes synthesis and properties
  • 2D Materials and Applications
  • Artificial Intelligence in Healthcare
  • Gas Sensing Nanomaterials and Sensors

Indian Institute of Technology Indore
2019-2024

From the last decade, development of a generic model for memristive systems which simulates biologically inspired nervous system living beings, is one most attracting aspects. More specifically, develop has capability to resolve problems in field artificial neural network. Here, generic, non-linear analytical model, based on interfacial switching mechanism, been discussed. The proposed simulate high-density network biological synapses that regulates communication efficacy among neurons and...

10.1088/1361-6463/ac07dd article EN Journal of Physics D Applied Physics 2021-06-03

Here, we report the fabrication of Y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> -based memristive crossbar array (MCA) by utilizing dual ion beam sputtering system, which shows high cyclic stability in resistive switching behavior. Further, obtained experimental results are validated with an analytical MCA based model, exhibits extremely well fitting corresponding data. Moreover,...

10.1109/tetc.2023.3318303 article EN IEEE Transactions on Emerging Topics in Computing 2023-09-28

Artificial synapses are the key units for information processing in neuromorphic systems. Memristive systems frequently used as an artificial synapse because of their simple structures, gradually changing conductance and high-density integration. In this work, a non-linear analytical model Y<inf>2</inf>O<inf>3</inf>-based memristive system with new parabolic window function has been discussed applications. Moreover, resistive switching characteristic synaptic plasticity properties modelled...

10.1109/icee50728.2020.9777072 article EN 2020-11-26
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