A method of the core area replaced by the optimum Gaussian mode area was proposed when calculating the effective stimulated Brillouin scattering gain coefficient. Then, the effect of steady-state Stimulated Brillouin Scattering (SBS) in a long multimode gain fiber was studied based on the coupled differential equations on beam intensity. The results show that the residual pumping power becomes saturated, and the Stokes power increases linearly with the launching power for whether the first-order or second-order SBS process. This study also shows that the second-order Stokes power is relatively weaker, and the effective length of the fiber decreases gradually with the increase of the launching power.

A novel classification measure based on matrix volume according to the high dimensional geometry theory is proposed for face recognition. Many two dimensional PCA (2DPCA)-based face recognition methods almost pay much attention to the feature extraction, and the classification measure is little investigated. The typical classification measure used in 2DPCA is the sum of the Euclidean distance between two feature vectors in feature matrix, called traditional Distance Measure (DM). However, this proposed method is to compute the matrix volume. To test its performance,experiments are done based on ORL and AR face databases. The experimental results show the Matrix Volume Measure (MVM) is more efficient than the DM in 2DPCA-based face recognition.