DocumentCode :
1028809
Title :
Granular quantization noise in the first-order delta-sigma modulator
Author :
Galton, Ian
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Volume :
39
Issue :
6
fYear :
1993
fDate :
11/1/1993 12:00:00 AM
Firstpage :
1944
Lastpage :
1956
Abstract :
A unified approach to analyzing the granular quantization error of the first-order ΔΣ modulator is presented. The approach handles many of the previously analyzed input sequences in addition to a large class of new input sequences. By averaging over the arbitrarily small amount of circuit noise assumed to be present at the analog input to the ΔΣ modulator, a simple expression for the autocorrelation of the quantization error is derived. Each term in the expression is formally equal to the quantization error of a nonoverloaded uniform quantizer operating upon a finite partial sum of consecutive input sequence samples. Hence, existing results concerning uniform quantizers are directly applicable in evaluating the autocorrelation expression for specific input sequences. The theory is also applicable to deterministic input sequences, and has been applied to obtain a new closed-form result for sinusoidal input sequences. Ergodic results which assert that, under mild conditions, the autocorrelation equals the time-average autocorrelation in probability are presented
Keywords :
analogue-digital conversion; correlation theory; delta modulation; modulators; noise; probability; analog input; autocorrelation; averaging; circuit noise; closed-form result; deterministic input sequences; ergodic results; finite partial sum; first-order delta-sigma modulator; granular quantization error; granular quantization noise; input sequence samples; nonoverloaded uniform quantizer; probability; sinusoidal input sequences; time-average autocorrelation; uniform quantizers; Additive noise; Analog-digital conversion; Circuit noise; Delta modulation; Low pass filters; Nonlinear systems; Performance analysis; Quantization; Sampling methods; Very large scale integration;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/18.265502
Filename :
265502
Link To Document :
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