Title :
System of Interconnected Reconfigurable Linear Threshold Circuits
Author :
Ohlmiller, Scott ; Hudson, Tina
Author_Institution :
Dept. of Electr. & Comput. Eng., Rose-Hulman Inst. of Technol., Terre Haute, IN
Abstract :
We have developed and fabricated a reconfigurable system based on Linear Threshold Elements (LTEs) that perform a variety of common logic operations using one basic structure. A single LTE compares a sum of weighted-inputs to a threshold and produces a Boolean output This operation is equivalent to the basic functions defined for artificial neural networks (ANNs). The reconfigurable structure was created by incorporating memory in the LTE and combining multiple LTEs together to produce a wider range of possible functions. The LTE structure presented in this paper is explicitly programmed by a host for logic tasks spanning multiple LTEs. However, the possibility exists to implement supervised learning or other neural network learning algorithms to train the LTE network for the desired operation.
Keywords :
learning (artificial intelligence); neural nets; threshold elements; Boolean output; artificial neural networks; interconnected reconfigurable linear threshold circuits; logic operations; logic tasks spanning multiple LTE; neural network learning algorithms; supervised learning; Artificial neural networks; Biological neural networks; Biological system modeling; Equations; Integrated circuit interconnections; Logic programming; Nervous system; Neurons; Reconfigurable logic; Supervised learning;
Conference_Titel :
Circuits and Systems, 2006. MWSCAS '06. 49th IEEE International Midwest Symposium on
Conference_Location :
San Juan
Print_ISBN :
1-4244-0172-0
Electronic_ISBN :
1548-3746
DOI :
10.1109/MWSCAS.2006.382287