I'm trying to think of a way to understand sigma-delta ADCs in time domain. Up to my understanding, two key technology of sigma-delta ADCs are oversampling and noise shaping. In frequency domain, oversampling evenly spreads the square(delta)/12 quantization noise between 0 and samping frequency fs. Then with the help of decimation filter, we can remove the noise out of baseband fB. So, the remaining noise is just 1/OSR of the quantization noise. This understanding works well in freqency domain. But I cannot relate this to time domain understanding. Why averaging more 1s and -1s means pushing noise to higher frequency...I think maybe when the samples are denser,the digital output are more similar to the original analog input. This seems reasonable, but too simple or general... Also, for noise shaping, I can just simply think the negative feedback forces the output to equal the input... Can anybody here give me some advice on time domain understanding of sigma-delta ADCs? Thank you very much~

# how to understand sigma-delta adc in time domain?

Started by ●November 11, 2008

Reply by ●November 11, 20082008-11-11

On Nov 11, 7:42�pm, "lxx.helen" <lxx.he...@gmail.com> wrote:> I'm trying to think of a way to understand sigma-delta ADCs in time > domain. > > Up to my understanding, two key technology of sigma-delta ADCs are > oversampling and noise shaping. In frequency domain, oversampling evenly > spreads the square(delta)/12 quantization noise between 0 and samping > frequency fs. Then with the help of decimation filter, we can remove the > noise out of baseband fB. So, the remaining noise is just 1/OSR of the > quantization noise. This understanding works well in freqency domain. But I > cannot relate this to time domain understanding. Why averaging more 1s and > -1s means pushing noise to higher frequency...I think maybe when the > samples are denser,the digital output are more similar to the original > analog input. This seems reasonable, but �too simple or general... > > Also, for noise shaping, I can just simply think the negative feedback > forces the output to equal the input... > > Can anybody here give me some advice on time domain understanding of > sigma-delta ADCs? > > Thank you very much~I have extensive slide presentations on this topic, which I will be happy to share. Bob Adams

Reply by ●November 11, 20082008-11-11

On Nov 11, 9:30�pm, Robert Adams <robert.ad...@analog.com> wrote:> On Nov 11, 7:42�pm, "lxx.helen" <lxx.he...@gmail.com> wrote: > > > > > I'm trying to think of a way to understand sigma-delta ADCs in time > > domain. > > > Up to my understanding, two key technology of sigma-delta ADCs are > > oversampling and noise shaping. In frequency domain, oversampling evenly > > spreads the square(delta)/12 quantization noise between 0 and samping > > frequency fs. Then with the help of decimation filter, we can remove the > > noise out of baseband fB. So, the remaining noise is just 1/OSR of the > > quantization noise. This understanding works well in freqency domain. But I > > cannot relate this to time domain understanding. Why averaging more 1s and > > -1s means pushing noise to higher frequency...I think maybe when the > > samples are denser,the digital output are more similar to the original > > analog input. This seems reasonable, but �too simple or general... > > > Also, for noise shaping, I can just simply think the negative feedback > > forces the output to equal the input... > > > Can anybody here give me some advice on time domain understanding of > > sigma-delta ADCs? > > > Thank you very much~ > > I have extensive slide presentations on this topic, which I will be > happy to share. >i wouldn't sneeze at an offer like that coming from this person. hey Bob, if this is already conveniently zipped or otherwize encapsulated, wanna send send me some of it? r b-j

Reply by ●November 11, 20082008-11-11

robert bristow-johnson wrote:> On Nov 11, 9:30 pm, Robert Adams <robert.ad...@analog.com> wrote: >> On Nov 11, 7:42 pm, "lxx.helen" <lxx.he...@gmail.com> wrote: >> >> >> >>> I'm trying to think of a way to understand sigma-delta ADCs in time >>> domain. >>> Up to my understanding, two key technology of sigma-delta ADCs are >>> oversampling and noise shaping. In frequency domain, oversampling evenly >>> spreads the square(delta)/12 quantization noise between 0 and samping >>> frequency fs. Then with the help of decimation filter, we can remove the >>> noise out of baseband fB. So, the remaining noise is just 1/OSR of the >>> quantization noise. This understanding works well in freqency domain. But I >>> cannot relate this to time domain understanding. Why averaging more 1s and >>> -1s means pushing noise to higher frequency...I think maybe when the >>> samples are denser,the digital output are more similar to the original >>> analog input. This seems reasonable, but too simple or general... >>> Also, for noise shaping, I can just simply think the negative feedback >>> forces the output to equal the input... >>> Can anybody here give me some advice on time domain understanding of >>> sigma-delta ADCs? >>> Thank you very much~ >> I have extensive slide presentations on this topic, which I will be >> happy to share. >> > > i wouldn't sneeze at an offer like that coming from this person. > > hey Bob, if this is already conveniently zipped or otherwize > encapsulated, wanna send send me some of it?If it's no trouble, may I see it too? Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������

Reply by ●November 11, 20082008-11-11

lxx.helen@gmail.com Thank you very very much~>On Nov 11, 7:42=A0pm, "lxx.helen" <lxx.he...@gmail.com> wrote: >> I'm trying to think of a way to understand sigma-delta ADCs in time >> domain. >> >> Up to my understanding, two key technology of sigma-delta ADCs are >> oversampling and noise shaping. In frequency domain, oversamplingevenly>> spreads the square(delta)/12 quantization noise between 0 and samping >> frequency fs. Then with the help of decimation filter, we can removethe>> noise out of baseband fB. So, the remaining noise is just 1/OSR of the >> quantization noise. This understanding works well in freqency domain.But=> I >> cannot relate this to time domain understanding. Why averaging more 1san=>d >> -1s means pushing noise to higher frequency...I think maybe when the >> samples are denser,the digital output are more similar to the original >> analog input. This seems reasonable, but =A0too simple or general... >> >> Also, for noise shaping, I can just simply think the negative feedback >> forces the output to equal the input... >> >> Can anybody here give me some advice on time domain understanding of >> sigma-delta ADCs? >> >> Thank you very much~ > >I have extensive slide presentations on this topic, which I will be >happy to share. > > >Bob Adams >

Reply by ●November 11, 20082008-11-11

On Nov 11, 10:00�pm, Jerry Avins <j...@ieee.org> wrote:> robert bristow-johnson wrote: > > On Nov 11, 9:30 pm, Robert Adams <robert.ad...@analog.com> wrote: > >> On Nov 11, 7:42 pm, "lxx.helen" <lxx.he...@gmail.com> wrote: > > >>> I'm trying to think of a way to understand sigma-delta ADCs in time > >>> domain. > >>> Up to my understanding, two key technology of sigma-delta ADCs are > >>> oversampling and noise shaping. In frequency domain, oversampling evenly > >>> spreads the square(delta)/12 quantization noise between 0 and samping > >>> frequency fs. Then with the help of decimation filter, we can remove the > >>> noise out of baseband fB. So, the remaining noise is just 1/OSR of the > >>> quantization noise. This understanding works well in freqency domain. But I > >>> cannot relate this to time domain understanding. Why averaging more 1s and > >>> -1s means pushing noise to higher frequency...I think maybe when the > >>> samples are denser,the digital output are more similar to the original > >>> analog input. This seems reasonable, but �too simple or general... > >>> Also, for noise shaping, I can just simply think the negative feedback > >>> forces the output to equal the input... > >>> Can anybody here give me some advice on time domain understanding of > >>> sigma-delta ADCs? > >>> Thank you very much~ > >> I have extensive slide presentations on this topic, which I will be > >> happy to share. > > > i wouldn't sneeze at an offer like that coming from this person. > > > hey Bob, if this is already conveniently zipped or otherwize > > encapsulated, wanna send send me some of it? > > If it's no trouble, may I see it too? > > Jerry > -- > Engineering is the art of making what you want from things you can get. > �����������������������������������������������������������������������- Hide quoted text - > > - Show quoted text -Sure, if you guys send me your email addresses I will attach some ppt's; I'm at robert.adams@analog.com Bob

Reply by ●November 12, 20082008-11-12

On Tue, 11 Nov 2008 18:42:20 -0600, lxx.helen wrote:> I'm trying to think of a way to understand sigma-delta ADCs in time > domain. > > Up to my understanding, two key technology of sigma-delta ADCs are > oversampling and noise shaping. In frequency domain, oversampling evenly > spreads the square(delta)/12 quantization noise between 0 and samping > frequency fs. Then with the help of decimation filter, we can remove the > noise out of baseband fB. So, the remaining noise is just 1/OSR of the > quantization noise. This understanding works well in freqency domain. > But I cannot relate this to time domain understanding. Why averaging > more 1s and -1s means pushing noise to higher frequency...I think maybe > when the samples are denser,the digital output are more similar to the > original analog input. This seems reasonable, but too simple or > general... > > Also, for noise shaping, I can just simply think the negative feedback > forces the output to equal the input... > > Can anybody here give me some advice on time domain understanding of > sigma-delta ADCs? > > Thank you very much~While you're waiting for Robert's slides, here's something to ponder: You have it a bit wrong; the front end of a delta-sigma modulator is designed to shape the noise more or less during the sampling process, so you can't really separate the sampling from the noise shaping. What it does is to take the output of a 1-bit DAC that follows the train of 1's and 0's that come out of the comparator, and uses that as feedback to a loop that contains an integrator. Since an integrator has higher gain the lower the frequency gets, the noise _must_ be reduced at these lower frequencies. IIRC the article that I wrote on sigma-delta techniques covers the time- domain aspect of this -- see http://www.wescottdesign.com/articles/ sigmadelta.html and follow the link. -- Tim Wescott Wescott Design Services http://www.wescottdesign.com Do you need to implement control loops in software? "Applied Control Theory for Embedded Systems" gives you just what it says. See details at http://www.wescottdesign.com/actfes/actfes.html