  We show that neural network classifiers can be helpful to discriminate Higgs
production from background at LHC in the Higgs mass range M= 200 GeV. We employ
a common feed-forward neural network trained by the backpropagation algorithm
for off-line analysis and the neural chip Totem, trained by the Reactive Tabu
Search algorithm, which could be used for on-line analysis.
