Neural Sensor Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (10 January 2021) | Viewed by 517
Special Issue Editor
2. Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia
Interests: computational neuroscience; spiking neuron networks; neurointerfaces; neurocontrol; biomorphic robotics; nonlinear dynamics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue on neural sensor networks is devoted to trends and achievements in the design of sensors based on multisite neural networks and intellectual signal processing. Neural networks based on artificial neurons can theoretically implement any logical function and, hence, can be applied in many areas of science and technology. Neural sensor networks being supplied with signal processing, decision making, and control lead to intellectual cyberphysical systems supporting robotic devices, human–machine interfaces, multimodal neurointerfaces and avatars, biometric collecting systems, and many others. In addition, fundamental search of new strategies in learning and processing principles of neural networks involves biologically relevant networks based on spiking neurons and synaptic connections, e.g., spiking neuron networks. In particular, such networks should reproduce mechanisms and principles of brain functions in information processing and control.
Potential topics include but are not limited to the following:
- Neural sensor networks in robotic devices;
- Multimodal signal classification in human–machine interfaces;
- EEG/EMG-based sensor networks in rehabilitation;
- Spiking neuron network in sensor design;
- Learning principles for spiking neuron networks;
- Multimodal sensors for biometric data collection and classification.
Prof. Victor B. Kazantsev
Guest Editor
Manuscript Submission Information
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Keywords
- neuron network
- robotics
- human–machine interface
- neurointerface
- spiking neuron networks
- learning
