Quantization to maximize SNR in non-orthogonal subband coders

Recent research in the design of filter banks has shown that nonorthogonal filter banks can potentially provide higher coding gains over orthogonal filter banks. The use of non-orthogonal filter banks, however, poses a difficulty in the quantization of subband signals. The conventional nearest-neighbor (NN) encoding rule for the quantization of subband signals is no longer optimal. In this paper, we propose two schemes for the quantization of subband signals in non-orthogonal subband coders. An optimal scheme for quantization of subband signals is proposed first. The complexity of the optimal quantization scheme is shown to grow exponentially with the length of the synthesis filters, which motivates the development of low-complexity quantization schemes when the length of the filters in the synthesis filter bank is large. The second quantization technique uses an iterative method to quantize the subband signals such that the mean square error between the input and the reconstructed output signals is minimized.