889 search results - page 30 / 178 » Probabilistic Neural Network Models for Sequential Data |
DMSN
2008
ACM
13 years 10 months ago
2008
ACM
When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two ...
ENVSOFT
2008
13 years 8 months ago
2008
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
NIPS
1997
13 years 9 months ago
1997
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
ICML
2004
IEEE
14 years 9 months ago
2004
IEEE
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
ICANN
2003
Springer
14 years 1 months ago
2003
Springer
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...