Title :
A simple design and implementation of reconfigurable neural networks
Author :
El-Bakry, Hazem M. ; Mastorakis, Nikos
Author_Institution :
Fac. of Comput. Sci. & Inf. Syst., Mansoura Univ., Mansoura, Egypt
Abstract :
There are some problems in hardware implementation of digital combinational circuits. In contrast, analog design has the advantages of both economy and easy to implement compared with the digital design. In this paper, a simple design and implementation of analog reconfigurable artificial neural network is presented. A novel design of arithmetic unit that including full-adder, full-subtractor, 2-bit digital multiplier and 2-bit digital divider is introduced. The proposed neural network has been realized by hardware components and the results are simulated using H-SPICE program. Practical results confirm the theoretical considerations.
Keywords :
adders; analogue circuits; combinational circuits; dividing circuits; multiplying circuits; neural nets; 2-bit digital divider; 2-bit digital multiplier; H-SPICE program; analog design; analog reconfigurable artificial neural network; arithmetic unit; digital combinational circuits; full-adder; full-subtractor; hardware implementation; word length 2 bit; Artificial neural networks; Biological neural networks; Digital arithmetic; Integrated circuit interconnections; Network topology; Neural network hardware; Neural networks; Neurons; Resistors; Switches;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2009.5178600