Title :
Square Wave Artificial Neuron (SWAN)
Author :
Ellis, D. ; Imamura, Kousuke
Author_Institution :
Comput. Sci. Dept., Eastern Washington Univ., Cheney, WA, USA
Abstract :
We developed a square wave based artificial neuron to take advantage of inexpensive and readily available Field Programmable Gate Array technologies. While conventional neurons require computationally intensive floating point arithmetic to determine the output, our artificial neuron converts inputs into square waves and the time that these waves require to produce a predetermined bit pattern is used to determine the output value. The behavior of this neuron was successfully simulated by software to demonstrate that the Square Wave Artificial Neuron is software implementable.
Keywords :
field programmable gate arrays; neural nets; SWAN; field programmable gate array technologies; floating point arithmetic; square wave based artificial neuron; Biological neural networks; Biological system modeling; Equations; Field programmable gate arrays; Mathematical model; Neurons; Software; FPGA; learning; neural network; neuron;
Conference_Titel :
Digital Information and Communication Technology and it's Applications (DICTAP), 2014 Fourth International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4799-3723-3
DOI :
10.1109/DICTAP.2014.6821654
