This paper describes a new class of multi-pulse coders based on bounded-error identification. Multi-pulse coders provide effective representations of speech signals by extracting linear prediction parameters and approximating the effect of excitation signals with strategic sparse impulse sequences. These sparse impulses can be derived according to a set-membership optimization set volume reduction strategy. The proposed method offers the added benefit of improved scalar quantization through the choice of coder parameters from a feasibility set.