Abstract
When implementing dynamical systems for information processing, a well-defined set of computational primitives should be constructed to represent the state space. Based on the specific collective behavior of Freeman’s computational model of the olfactory cortex, we study the computation of reduced KII networks by using the synchronization of output channels. The design of coupling coefficients in the network for obtaining a desired output state response is presented. We demonstrate the computational power of reduced KII networks by two applications that address logic computation and associative memory, respectively. © 2006 Wiley Periodicals, Inc.
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