Title :
Reconstruction of oversampled band-limited signals from ΣΔ encoded binary sequences
Author :
Hein, Søren ; Zakhor, Avideh
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
fDate :
4/1/1994 12:00:00 AM
Abstract :
Considers the application of ΣΔ modulators to analog-to-digital conversion. The authors have previously shown that for constant input signals, optimal nonlinear decoding can achieve large gains in signal-to-noise ratio (SNR) over linear decoding. The present paper shows a similar result for band-limited input signals. The new nonlinear decoding algorithm is based on projections onto convex sets (POCS), and alternates between a time-domain operation and a band limitation to find a signal invariant under both. The time-domain operation results in a quadratic programming problem. The band limitation can be based on singular value decomposition of a certain matrix. The authors show simulation results for the SNR performance of a POCS-based decoder and a linear decoder for the single loop, double loop and two-stage ΣΔ modulators and for a specific fourth-order interpolative modulator. Depending on the modulator and the oversampling ratio, improvements in SNR of up to 10-20 dB can be achieved
Keywords :
analogue-digital conversion; binary sequences; block codes; codecs; decoding; delta modulation; modulators; quadratic programming; time-domain analysis; ΣΔ encoded binary sequences; POCS; POCS-based decoder; SNR performance; analog-to-digital conversion; band limitation; double loop ΣΔ modulator; fourth-order interpolative modulator; matrix; nonlinear decoding algorithm; oversampled band-limited signals; oversampling ratio; projections onto convex sets; quadratic programming problem; signal invariant; signal-to-noise ratio; single loop ΣΔ modulator; singular value decomposition; time-domain operation; two-stage ΣΔ modulators; Analog-digital conversion; Binary sequences; Circuits; Decoding; Matrix decomposition; Signal to noise ratio; Singular value decomposition; Speech; Time domain analysis; Very large scale integration;
Journal_Title :
Signal Processing, IEEE Transactions on