This paper presents results concerning a full digital implementation of the KII and KIII model proposed by Freeman to explain and model the chaotic behavior of the mammalian's Olfactory Cortex . The environment used for the task is a commercial neural network package. The immediate goal is to offer a computational efficient alternative to Runge-Kutta methods of solving the system's differential equations. To accomplish the goal the differential equations impulse response were sampled and decomposed over the gamma basis  Both models, KII and KIII, are presently working as associative memories, where stored patterns can be recalled from an input pattern . 1. Introduction The systems described in this paper are known as the KII and the KIII models . We will be emphasizing here the dynamic behavior of these models for information processing. Both models are based on the same single element, a second order dynamic equation with forcing inputs. These inputs (static or time v..
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