@article {10.3844/ajassp.2014.782.788,
article_type = {journal},
title = {VHDL DESIGN AND HARDWARE REALIZATION OF HYBRIDARTIFICIAL INTELLIGENCE ARCHITECTURE},
author = {Nagalingam, Rajeswaran and Madhu, Tenneti and Suryakalavathi, Munagala},
volume = {11},
year = {2014},
month = {Feb},
pages = {782-788},
doi = {10.3844/ajassp.2014.782.788},
url = {https://thescipub.com/abstract/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).},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}