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ESANN
2008
13 years 9 months ago
Conditional prediction of time series using spiral recurrent neural network
Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
Huaien Gao, Rudolf Sollacher
ICANN
1997
Springer
13 years 11 months ago
Spatio-Temporal Pattern Recognition with Neural Networks: Application to Speech
The processing or the recognition of non stationary process with neural networks is a challenging and yet unsolved issue. The paper discuss the general pattern recognition framewor...
Jean Rouat
ICRA
1998
IEEE
142views Robotics» more  ICRA 1998»
13 years 11 months ago
Lagrangian Relaxation Neural Networks for Job Shop Scheduling
Abstract--Manufacturing scheduling is an important but difficult task. In order to effectively solve such combinatorial optimization problems, this paper presents a novel Lagrangia...
Peter B. Luh, Xing Zhao, Yajun Wang
OL
2011
177views Neural Networks» more  OL 2011»
12 years 10 months ago
Exploiting vector space properties to strengthen the relaxation of bilinear programs arising in the global optimization of proce
In this paper we present a methodology for finding tight convex relaxations for a special set of quadratic constraints given by bilinear and linear terms that frequently arise in ...
Juan P. Ruiz, Ignacio E. Grossmann
EVOW
2009
Springer
13 years 11 months ago
Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks
In this paper the node-level decision unit of a self-learning anomaly detection mechanism for office monitoring with wireless sensor nodes is presented. The node-level decision uni...
Markus Wälchli, Torsten Braun