15-10-2010, 10:41 AM
[attachment=6111]
PROCESSING METHODS AND CHOICE OF INPUT SIGNALS FOR SIGNAL ARTIFICIAL NEURAL NETWORK FOR LARGE SYSTEMS
T.Anu Prasanth , K.S.Bhaskar
the neural net control the system in normal operation but it will control that system during unforeseen occurrences..
We can start with the training using Time domain signals, event inputs and observe the network response in detecting or not detecting the parameter correctly, noting the percentage of the number of inputs for best inference
Gabor transform was shown as useful for NMR signal network for chemical identification better
for more ::_>>\
http://studentbank.in/report-artificial-...?pid=26981
PROCESSING METHODS AND CHOICE OF INPUT SIGNALS FOR SIGNAL ARTIFICIAL NEURAL NETWORK FOR LARGE SYSTEMS
T.Anu Prasanth , K.S.Bhaskar
the neural net control the system in normal operation but it will control that system during unforeseen occurrences..
We can start with the training using Time domain signals, event inputs and observe the network response in detecting or not detecting the parameter correctly, noting the percentage of the number of inputs for best inference
Gabor transform was shown as useful for NMR signal network for chemical identification better
for more ::_>>\
http://studentbank.in/report-artificial-...?pid=26981
