Special Issue on Fractional Order Implementation of Neural Networks

Submission Deadline: Feb. 20, 2020

This special issue currently is open for paper submission and guest editor application.

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Special Issue Flyer (PDF)

  • Special Issue Editor
    • Nasir Ali Kant
      Department of Electronics, University of Kashmir, Srinagar, Jammu and Kashmir, India
    Guest Editors play a significant role in a special issue. They maintain the quality of published research and enhance the special issue’s impact. If you would like to be a Guest Editor or recommend a colleague as a Guest Editor of this special issue, please Click here to fulfill the Guest Editor application.
  • Introduction

    Fractional calculus which is the basically the generalization of integer-order calculus, has a history of about 300 years. However, owing to its computational complexity and lack of intuitive physical and geometric explanations, it failed to attract the interest of researchers in its earlier stages. Recently, fractional calculus has been proven to be a valuable tool in the modeling of many applications in physics, electronic circuits, bio-materials, and electrochemistry and the researchers have discovered that using fractional calculus to describe many natural phenomena will be more accurate, such as biomedical engineering, fractional control, and specific physical problems.
    Recently, many generalized (fractional-order) theorems have been introduced from which existing conventional theorems arise as special cases. As a generalized case the application of the fundamentals of fractional calculus into many of the physics problems, engineering applications showing the advantages of the resulting systems compared to conventional integer-order systems, has been the priority for many of the researchers recently. Extensive research activity in this area has been on-going as more potential real-world applications are highlighted and investigated.
    In recent years, the research of artificial neural networks based on fractional calculus has attracted much attention. A lot of work in this field can be seen in the open literature. It has been seen that the fraction-order implementation is resulting in mimicking the natural neural networks to the greater extend compared to their integer-order counterpart. Furthermore, the fractional calculus model is considered as an excellent tool to describe the hereditary and memory characteristics of various processes due to a memory term in the model, which is proving to be one of the key factors in the modeling of the neural networks.

    Aims and Scope:

    1. Non-Linear Dynamics
    2. Fractional Calculus
    3. Neural Network Design
    4. Real Life Applications
    5. Mathematical Modeling of Neural Networks
    6. VLSI implementation of Neural Networks

  • Guidelines for Submission

    Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.

    Papers should be formatted according to the guidelines for authors (see: http://www.ajnna.org/submission). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.

  • Published Papers

    The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.

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