Novel systematic mathematical computation based on the spiking frequency gate (SFG): Innovative organization of spiking computer

Abstract The idea that the brain is composed of logical gates similar to IP cores of today's computers were provided by McCulloch and Pitts in 1943. In this paper, six structures for the interaction of dynamic neurons have been proposed to create neural circuits with spike coding that operate similarly to Boolean gates. It was concluded that the network of the dynamic model of spiking neurons and synapses called spiking frequency gates (SFG) can emulate the operations of digital gates AND, OR, NOT, NOR, XOR, and NAND. Also, an attempt was made to construct complex spiking circuits like full-adder, multiplexer, and arithmetic-logic-unit using cascade connections of SFGs. Extending simple designs to more complex spiking circuits can continue in order to access sophisticated computing tools based on SFGs. SFGs are not limited to zero and one and respond to the continuous range of spike train frequencies. Therefore, the information coding of SFGs is more powerful than Boolean gates. This paper illustrates a novel Boolean computation platform in a neural-like manner, which can provide a potential and clear horizon for designing neural circuits with complex applications. We hope that our results will lead to a deeper comprehension of the brain's functionalities and the development of new systematic methods based on the proposed spiking approach of Boolean logic gates.

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