Single-Bit Oversampled A/D Conversion with Exponential Accuracy in the Bit-Rate
DCC '00 Proceedings of the Conference on Data Compression
On simple oversampled A/D conversion in L2(R)
IEEE Transactions on Information Theory
Distributed sampling for dense sensor networks: a "Bit-conservation principle"
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Behavior of the quantization operator for bandlimited, nonoversampled signals
IEEE Transactions on Information Theory
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The problem of reconstructing a pi-bandlimited signal $f$ from its quantized samples taken at an irregular sequence of points $t_k, k=...-2,1,0,1...$ arises in oversampled analog-to-digital conversion. The input signal can be reconstructed from the quantized samples $f(t_k)$ by estimating samples $f(n/lambda),n=...-2,-1,0,1,...$ where lambda is the average uniform density of the sequence $(t_k)$, assumed here to be greater than one, followed by linear low-pass filtering. We study three techniques for estimating samples $f(n/lambda)$ from quantized irregular samples $f(t_k)$, including Lagrangian interpolation, and two other techniques which result in a better overall accuracy of oversampled A/D conversion.