Abstract. This paper examines the generalization capability in learning multiple temporal patterns by the recurrent neural network with parametric bias (RNNPB). Our simulation expe...
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
A speech separation system is described in which sources are represented in a joint interaural time difference-fundamental frequency (ITD-F0) cue space. Traditionally, recurrent t...
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...