摘要
In this paper we consider the problem of sequential processing and present a sequen-tial model based on the back-propagation algorithm. This model is intended to deal with intrinsically sequential problems, such as word recognition, speech recognition,natural language understanding. This model can be used to train a network to learn the sequence of input patterns, in a fixed order or a random order. Besides, this mod-el is open- and partial-associative, characterized as 'recognizing while accumulating',which, as we argue, is mental cognition process oriented.
In this paper we consider the problem of sequential processing and present a sequen-tial model based on the back-propagation algorithm. This model is intended to deal with intrinsically sequential problems, such as word recognition, speech recognition,natural language understanding. This model can be used to train a network to learn the sequence of input patterns, in a fixed order or a random order. Besides, this mod-el is open- and partial-associative, characterized as 'recognizing while accumulating',which, as we argue, is mental cognition process oriented.
