Fast signal subspace tracking using two-layer linear neural network learning

In this paper, we present an orthonormal version of the new information criterion (NIC) algorithm for fast estimation and tracking of signal subspace using a two-layer linear neural network (NN). The fast orthonormal NIC referred as to FONIC algorithm guarantees the orthonormality of the weight matrix at each iteration. The proposed FONIC algorithm has a linear complexity which makes it efficient in real time applications. The FONIC algorithm provides a fast on-line learning of the optimum weights for the two-layer linear. Simulation results show better performance of FONIC algorithm than the NIC algorithm.