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» Probabilistic Neural Network Models for Sequential Data
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JMLR
2008
188views more  JMLR 2008»
13 years 7 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
ICANN
2005
Springer
14 years 1 months ago
Accurate and Robust Image Superresolution by Neural Processing of Local Image Representations
Image superresolution involves the processing of an image sequence to generate a still image with higher resolution. Classical approaches, such as bayesian MAP methods, require ite...
Carlos Miravet, Francisco de Borja Rodrígue...
MSWIM
2006
ACM
14 years 2 months ago
Analysis of soft handover measurements in 3G network
A neural network based clustering method for the analysis of soft handovers in 3G network is introduced. The method is highly visual and it could be utilized in explorative analys...
Kimmo Raivio
EUSFLAT
2007
183views Fuzzy Logic» more  EUSFLAT 2007»
13 years 9 months ago
Soft Computing in Wireless Sensors Networks
The embedded soft computing approach in wireless sensor networks is suggested. This approach means a combination of embedded fuzzy logic and neural networks models for information...
Alexey N. Averkin, A. G. Belenki
ICASSP
2011
IEEE
12 years 11 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...