Abstract
A class of Petri nets (PNs), high level Petri nets (HPNs), are powerful and versatile tools for modeling, simulating, analyzing, designing and controlling complex asynchronous concurrent systems. An initial attempt is made to model biological neural networks (BNNs) with HPNs, since the interactions among neurons is basically asynchronous concurrent in nature. Even though there are many types of HPNs reported in literature, none have the constructs to model BNNs. Hence, a new class of HPNs is proposed. With this aim the analogies between BNNs and HPNs are explored. The detailed procedure of Petri net (PN) modeling is elucidated by modeling the mammalian olfactory bulb. >
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