Optimal buffer-constrained source quantization and fast approximations

The description of the buffer-constrained quantization problem is formalized. For a given set of admissible quantizers for coding a discrete nonstationary signal sequence in a buffer-constrained environment, and for any global distortion minimization criterion that is additive over the individual elements of the sequence, the optimal solution and slightly suboptimal but much faster approximations are formulated. The problem is first defined as one of constrained, discrete optimization, and its equivalence to some problems in integer programming is established. Dynamic programming using the Viterbi algorithm is shown to provide a way of computing the optimal solution. A heuristic algorithm based on Lagrangian optimization and using an operational rate-distortion framework that, with much-reduced computing complexity, approaches the optimally achievable SNR is provided