  This paper studies the statistical models of the noise-robust normalized
subband adaptive filter (NR-NSAF) algorithm in the mean and mean square
deviation senses involving transient-state and steady-state behavior by
resorting to the method of the vectorization operation and the Kronecker
product. The analysis method does not require the Gaussian input signal.
Moreover, the proposed analysis removes the paraunitary assumption imposed on
the analysis filter banks as in the existing analyses of subband adaptive
algorithms. Simulation results in various conditions demonstrate the
effectiveness of our theoretical analysis. For a special form of the algorithm,
the proposed steady-state expression is also better accurate than the previous
analysis.
