  The possibility to use Neural Networks for reconstruction of the energy
deposited in the calorimetry system of the CMS detector is investigated. It is
shown that using feed - forward neural network, good linearity, Gaussian energy
distribution and good energy resolution can be achieved. Significant
improvement of the energy resolution and linearity is reached in comparison
with other weighting methods for energy reconstruction.
