Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation).
A first phase in the development of temporal neural networks is characterized by architectures based on classical models, but locally modified so as to take the ...
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Dec 7, 2001 · Unnikrishnan, K. P., Hopfield, J. J., & Tank, D. W. (1991). Connected-digit speaker-dependent speech recognition using a neural network with ...
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important.
an information-processing version of Scalar Timing Theory has been useful for explaining the ability of animals to estimate the duration of an interval ...
Abstract. Two connectionist frameworks, GRAIN (J. L. McClelland, 1993) and brain-state-in-a-box (J. A. Anderson, 1991), and R. Ratcliff's (1978) diffusion model ...
Abstract: In this paper, we review extant computational models of time perception to elucidate the need for developing connectionist/neural networks models ...
These three models are the Interactive Activation model of letter recognition (McClelland & Rumelhart, 1981; Rumelhart and McClelland, 1982),. Rumelhart and ...
The main part of this article, a classification of temporal neural models, is introduced by a short presentation of basic connectionist models. This ...
Connectionist simulations of children's acquisition of distance (d), time (t), and velocity (v) concepts using a generative ...