VHDL DESIGN AND HARDWARE REALIZATION OF HYBRIDARTIFICIAL INTELLIGENCE ARCHITECTURE
Rajeswaran Nagalingam1, Tenneti Madhu2 & Munagala Suryakalavathi3 Show affiliations
- Department of ECE, SNS College of Technolgoy, Coimbatore, Tamilnadu, India
- Principal, Swarnandhra Institute of Engg. and Tech., Narasapur Andhrapradesh, India
- Department of EEE, Jawaharlal Nehru Technological University, Hyderabad Andhrapradesh, India
American Journal of Applied Sciences, Volume 11, Issue 5, pp. 782–788 · doi.org/10.3844/ajassp.2014.782.788
Abstract
Evolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficiently compute the function value in less time. In this study the weight optimization of the Artificial Neural Net-work (ANN), using the Back Propagation Network (BPN), is tested and presented with GA. The combined architecture of Neuro-Genetic (Hybrid Artificial Intelligence) approach is proposed and simulated results are provided along with device Utilization, Simulation time, Timing analysis and power analysis by using very high speed integrated circuits Hardware Description Language (HDL).
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Nagalingam, R., Madhu, T. & Suryakalavathi, M. (2014). VHDL DESIGN AND HARDWARE REALIZATION OF HYBRIDARTIFICIAL INTELLIGENCE ARCHITECTURE. American Journal of Applied Sciences, 11(5), 782–788. https://doi.org/10.3844/ajassp.2014.782.788
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