Document Type
Original Study
Abstract
The use Artificial Neural Networks (ANN) can be a form of Artificial Intelligence (AI). The feed forward neural network has a wide application area such as pattern recognition, image compression, and classification problem. Two models of a feed forward neural network are proposed and implemented using the schematic editor of the Xilinx FPGA foundation series 2.1i. Model-1 consists of two layers and specializes in solving a linear problem. Model-2 is a modified copy from Model-1 and consists of three layers and it's responsible for classifying the non-linear problems. Each model is designed and implemented in five stages without using the finite state machine. The flexibility, low costly, and real-time operation are the main features of the proposed design take in considered. Model-1 execution time is 2.935us and model-2 execution time is 2.96µs, while the costs of two models are 1927 CLBs and 2017 CLBs respectively. These features compare extremely well with other existing designs with good advantages.
How to Cite This Article
Mohammed, Waleed A. and A., Monther
(2006)
"Design and Implementation of Two Feed Forward Neural Network Models Using FPGAs Schematic Editor .,"
Iraqi Journal of Computers, Communications, Control and Systems Engineering: Vol. 6:
Iss.
3, Article 10.
Available at:
https://ijccce.researchcommons.org/journal/vol6/iss3/10