Neuromorphic Devices and Brain-Inspired Intelligent Systems: Applications and Prospects

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: 15 March 2026 | Viewed by 739

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School of Artificial Intelligence, Xidian University, Xi’an 710071, China
Interests: artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Academy of Advanced Disciplinary Research, Xidian University, Xi’an 710071, China
Interests: artificial intelligence; medical imaging; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neuromorphic devices and brain-inspired intelligent systems are at the forefront of innovation in artificial intelligence and computing. Inspired by the structure and functionality of biological neural systems, these technologies hold immense potential for revolutionizing areas such as edge computing, robotics, IoT, and artificial general intelligence. Neuromorphic devices, including spiking neural networks and brain-like processors, offer energy-efficient solutions for complex computations and real-time decision-making.

The aim of this Special Issue on “Neuromorphic Devices and Brain-Inspired Intelligent Systems: Applications and Prospects” is to foster the exchange of ideas and research findings on the design, simulation, and application of neuromorphic systems and devices. It encourages contributions that bridge the gap between theory and practice in this rapidly evolving field.

The main topics of this Special Issue include, but are not limited to:

  • Neuromorphic device design and modeling;
  • Spiking neural networks and their hardware implementations;
  • Novel materials and fabrication techniques for neuromorphic computing;
  • Energy-efficient AI chips for brain-inspired systems;
  • Hardware–software co-design for neuromorphic systems;
  • Applications of neuromorphic computing in robotics, IoT, and edge AI;
  • Simulation tools for brain-inspired intelligent systems;
  • Real-world deployment and testing of neuromorphic systems under diverse conditions.

We look forward to receiving your contributions and insights into these transformative technologies.

Dr. Zhen Cao
Dr. Zhang Guo
Guest Editors

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Keywords

  • neuromorphic devices
  • spiking neural networks
  • brain-inspired computing
  • neuromorphic computing
  • artificial intelligence

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Published Papers (1 paper)

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Research

15 pages, 897 KB  
Article
It Is Simple to Program with Spiking Neurons
by Christian Huyck and Fayokunmi Obisesan
Electronics 2025, 14(22), 4397; https://doi.org/10.3390/electronics14224397 - 12 Nov 2025
Viewed by 398
Abstract
Neural and synaptic models that are relatively biologically accurate are easy to use to run efficient and distributed programs. The mechanism described in this paper uses these models to develop cell assemblies with a small number of neurons that persist indefinitely unless stopped. [...] Read more.
Neural and synaptic models that are relatively biologically accurate are easy to use to run efficient and distributed programs. The mechanism described in this paper uses these models to develop cell assemblies with a small number of neurons that persist indefinitely unless stopped. These in turn can be used to implement finite state automata and many other useful components, including cognitive maps and natural language parsers. These components support the development of, among other things, agents in virtual environments. Two spiking neuron agents are described, both able to run using either a standard neural simulator or using neuromorphic hardware. Examples of their behavior are described touching the individual spike level. The component model supports step-wise development, and the example of extending the cognitive mapping mechanism from the simple agent to the full agent is described. Spiking nets support parallelism, use on neuromorphic platforms, and engineering and exploration of multiple subsystems, which in turn can help explore the neural basis of cognitive phenomena. Relationships between these spiking nets and biology are discussed. The code is available to ease reuse by other researchers. Full article
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