rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: COMPUTATIONAL TECHNIQUES IN NEUROSCIENCE
  name:
    name part: Malik, Kamal.
  name:
    name part: Sadawarti, Harsh.
  name:
    name part: Sharma, Moolchand.
  name:
    name part: Gupta, Umesh.
  name:
    name part: Tiwari, Prayag.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    place:
      place term: S.l.]
    publisher: CRC PRESS
    date issued: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience.Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using articial intelligence, deep learning, and other machine learning techniques to ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
  note: Dr. Kamal Malik is currently working as a Professor in CSE in the School of Engineering and Technology at CTU Ludhiana, Punjab, India. She has published Scientific Research Publications in reputed International Journals, including SCI and Scopus indexed Journals such as Adhoc and senior Wireless Networks, 50, Engineering, Technology and Applied Sciences Research, Journals of Advanced Research in Engineering, Research Journal of Applied Sciences of Engineering & Technology(RJASET- Maxwell Sciences), SSRN-Electronic Journal, Design Engineering, Indian Journal of Science and Technology(IJST), International Journal of Computer Applications(IJCA), and many more. She has also attended many National and International Conferences of repute like Springer, and Elsevier in India. Her major research areas are Artificial Intelligence, Machine Learning and Deep Learning, Data Analytics, Computational Neurosciences, and bio-inspired computing. She has more than 13 years of rich Academic and Research experience. She has guided 3 research scholars and currently guiding 8 research Scholars at CT University, Ludhiana. She has worked in renowned Institutes and Universities like RIMT Mandigobindgarh, Maharishi Markandeshwar University, Mullana, GNA University, Phagwara. She has also chaired various sessions in Springer and Elsevier. She has also been awarded with the preeminent researcher award from Green Thinkerz society at CII, Chandigarh. She has completed her Doctorate of Philosophy in Computer Science from IKGPTU Kapurthala in 2017, her Masters and Graduation from Kurukshetra University, Kurukshetra in 2009 and 2006 respectively. Dr. Harsh Sadawarti is currently working as Vice Chancellor of CT University and Professor of Computer Science and Engineering in School of Engineering and Technology at CTU Ludhiana, Punjab India. He has published Scientific research Publications in reputed International Journals including SCI indexed and Scopus indexed Journals such as Journal of Intelli…
  note: He has several publications in top journals and conferences, including Neural Networks, Information Fusion, IPM, IJCV, IEEE TNNLS, IEEE TFS, IEEE TII, IEEE JBHI, IEEE IOTJ, IEEE BIBM, ACM TOIT, CIKM, SIGIR, AAAI, etc. His research interests include Machine Learning, Deep Learning, Quantum Machine Learning, Information Retrieval, Healthcare, and IoT. He is also associated with one Funded-based project named "Data Literacy for Responsible Decision-Making" Short title (STN LITERACY/Marttinen). He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences.
  subject:
    topic: Neurosciences
    topic: Data processing
  subject:
    topic: Machine learning
  subject:
    topic: Machine Learning
  subject:
    topic: Apprentissage automatique
  subject:
    topic: TECHNOLOGY / Electronics / General
  subject:
    topic: Machine learning
  subject:
    topic: Neurosciences
    topic: Data processing
  classification: RC337
  classification: 612.8028563
  related item:
    title info:
      title: Computational methods for industrial applications
  related item:
    identifier: (OCoLC)1380686681
  identifier: 9781000994148
  identifier: 1000994147
  identifier: 9781003398066
  identifier: 1003398065
  identifier: 9781000994216
  identifier: 100099421X
  identifier: 1032461284
  identifier: 9781032461281
  identifier: 9781003398066 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 230930
    record change date: 20241108165442.2
    record identifier: in00005519152
    language of cataloging:
      language term: eng