1421 search results - page 17 / 285 » Resampling methods for input modeling |
ESANN
2004
13 years 8 months ago
2004
Spiking neurons model a type of biological neural system where information is encoded with spike times. In this paper, a new method for decoding input spikes according to their abs...
ESANN
2008
13 years 8 months ago
2008
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
WSC
2004
13 years 8 months ago
2004
Bayesian methods are now used in a variety of ways in discrete-event simulation. Applications include input modeling, response surface modeling, uncertainty analysis, and experime...
NIPS
2004
13 years 8 months ago
2004
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
IJSYSC
1998
13 years 7 months ago
1998
This paper presents a new analysis and design method for model reference adaptive control(MRAC) with arbitrary bounded input nonlinearities. The adaptive algorithm ensures that th...