  A variation of the classic vector quantization problem is considered, in
which the analog-to-digital (A2D) conversion is not constrained by the
cardinality of the output but rather by the number of comparators available for
quantization. More specifically, we consider the scenario in which a vector
quantizer of dimension d is comprised of k comparators, each receiving a linear
combination of the inputs and producing zero/one when this signal is
above/below a threshold. Given a distribution of the inputs and a distortion
criterion, the value of the linear combinations and thresholds are to be
configured so as to minimize the distortion between the quantizer input and its
reconstruction. This vector quantizer architecture naturally arises in many A2D
conversion scenarios in which the quantizer's cost and energy consumption are
severely restricted. For this novel vector quantizer architecture, we propose
an algorithm to determine the optimal configuration and provide the first
performance evaluation for the case of uniform and Gaussian sources.
