A STUDY OF TRACK FINDING WITH A NEURAL NETWORK ALGORITHM
1992 ◽
Vol 03
(supp01)
◽
pp. 303-308
Keyword(s):
We have investigated the problem of track finding with a recurrent neural network algorithm based on the Hopfield model and considered the possibility of a hardware implementation with DSP’s. Starting from a set of signal points we define track segments and set a cut on the length to keep the size of the network reasonable. Those segments surviving the cut are associated to neurons. A geometric coupling of neighbouring segments is used to select smooth combinations of them. Given random initial conditions the network converges to a solution. The method may be applied to a variety of curves.
Keyword(s):
Keyword(s):
2021 ◽
Vol 15
(4)
◽
pp. 516
2021 ◽
Vol 13
(1)
◽
pp. 1
2021 ◽
Vol 245
◽
pp. 118021
◽
2018 ◽
Vol 339
(5)
◽
pp. 358-362
◽