Implementation of artificial intelligence cognitive neuroscience neuron cell using adaptive velocity threshold particle swarm optimization (AVT-PSO) on FPGA
| Autor: | Sunita Prasad, Divya Singh, Sandeep Srivastava |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Network architecture Artificial neural network business.industry Computer science Particle swarm optimization Cognitive neuroscience ComputingMethodologies_ARTIFICIALINTELLIGENCE Swarm intelligence 03 medical and health sciences 030104 developmental biology 0302 clinical medicine medicine.anatomical_structure Adaptive system medicine Artificial intelligence Neuron business Field-programmable gate array 030217 neurology & neurosurgery |
| Zdroj: | 2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). |
| DOI: | 10.1109/icrito.2017.8342488 |
| Popis: | This paper presents the hardware development and implementation of artificial intelligence based neuron cell using swarm intelligence based algorithm (AVT-PSO) where the functionality of the architecture is tested by implementing four bit addition based on cognitive science neural network employing five neuron cell (sort of a model emulating function of a neuron cell in the brain) trained using an adaptive velocity threshold particle swarm optimization on Spartan-3e XC3S100E Field Programmable Gate Arrays (FPGA). Each neuron cell represents a processing element which is trained using swarm intelligence. Adaptive velocity threshold PSO algorithm is used in evolving threshold values to train the weights of neural cells. Implemented system is flexible in design, allowing the possibility to add or remove neurons to generate new network architectures. |
| Databáze: | OpenAIRE |
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