Design and development of opto-neural processors for simulation of
neural networks trained in image detection for potential implementation in
hybrid robotics
- URL: http://arxiv.org/abs/2401.10289v1
- Date: Wed, 17 Jan 2024 04:42:49 GMT
- Title: Design and development of opto-neural processors for simulation of
neural networks trained in image detection for potential implementation in
hybrid robotics
- Authors: Sanjana Shetty
- Abstract summary: Living neural networks offer advantages of lower power consumption, faster processing, and biological realism.
This work proposes a simulated living neural network trained indirectly by backpropagating STDP based algorithms using precision activation by optogenetics.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Neural networks have been employed for a wide range of processing
applications like image processing, motor control, object detection and many
others. Living neural networks offer advantages of lower power consumption,
faster processing, and biological realism. Optogenetics offers high spatial and
temporal control over biological neurons and presents potential in training
live neural networks. This work proposes a simulated living neural network
trained indirectly by backpropagating STDP based algorithms using precision
activation by optogenetics achieving accuracy comparable to traditional neural
network training algorithms.
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