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发表于 2015-4-3 14:51:48
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- %Code density/histofgram test to calculate INL and DNL require a large number of samples.
- %Step 1: Apply a close to full-scale sine wave (but not clipping) and find the mid-code for the applied signal.
- %Step 2: Apply the same sine wave input, but slightly larger amplitude to clip the ADC slightly.
- %Run the following program, enter the number of samples, resolution and mid-code from Step 1and continue.
- %Copyright Au/Hofner, Maxim Integrated Products, 120 San Gabriel Drive, Sunnyvale, CA94086
- %This program is believed to be accurate and reliable. This program may get altered without prior notification.
- filename=input('Enter File Name: ');
- if isempty(filename)
- filename = 'listing';
- end
- fid=fopen(filename,'r');
- numpt=input('Enter Number of Data Points: ');
- numbit=input ('Enter ADC Resolution: ');
- mid_code=input('Enter Mid-Code (Mean Code): ');
- for i=1:13,
- fgetl(fid);
- end
- [v1,count]=fscanf(fid,'%f',[2,numpt]);
- fclose(fid);
- v1=v1';
- code=v1(:,2);
- code_count=zeros(1,2^numbit);
- for i=1:size(code),
- code_count(code(i)+1)=code_count(code(i)+1) + 1;
- end
- if code_count(1) == 0 | code_count(2^numbit) == 0 | ...
- (code_count(1) < code_count(2)) | (code_count(2^numbit-1) > code_count(2^numbit))
- disp('ADC not clipping ... Increase sinewave amplitude!');
- break;
- end
- A=max(mid_code,2^numbit-1-mid_code)+0.1;
- vin=(0:2^numbit-1)-mid_code;
- sin2ramp=1./(pi*sqrt(A^2*ones(size(vin))-vin.*vin));
- while sum(code_count(2:2^numbit-1)) < numpt*sum(sin2ramp(2:2^numbit-1))
- A=A+0.1;
- sin2ramp=1./(pi*sqrt(A^2*ones(size(vin))-vin.*vin));
- end
- disp('You Have Applied a Sine Wave of (dBFS): ');
- Amplitude=A/(2^numbit/2)
- figure;
- plot([0:2^numbit-1],code_count,[0:2^numbit-1],sin2ramp*numpt);
- title('CODE HISTOGRAM - SINE WAVE');
- xlabel('DIGITAL OUTPUT CODE');
- ylabel('COUNTS');
- axis([0 2^numbit-1 0 max(code_count(2),code_count(2^numbit-1))]);
- code_countn=code_count(2:2^numbit-1)./(numpt*sin2ramp(2:2^numbit-1));
- figure;
- plot([1:2^numbit-2],code_countn);
- title('CODE HISTOGRAM - NORMALIZED')
- xlabel('DIGITAL OUTPUT CODE');
- ylabel('NORMALIZED COUNTS');
- dnl=code_countn-1;
- inl=zeros(size(dnl));
- for j=1:size(inl')
- inl(j)=sum(dnl(1:j));
- end
- %End-Point fit INL
- %[p,S]=polyfit([1,2^numbit-2],[inl(1),inl(2^numbit-2)],1);
- %Best-straight-line fit INL
- [p,S]=polyfit([1:2^numbit-2],inl,1);
- inl=inl-p(1)*[1:2^numbit-2]-p(2);
- disp('End Points Eliminated for DNL and INL Calculations');
- figure;
- plot([1:2^numbit-2],dnl);
- grid on;
- title('DIFFERENTIAL NONLINEARITY vs. DIGITAL OUTPUT CODE');
- xlabel('DIGITAL OUTPUT CODE');
- ylabel('DNL (LSB)');
- figure;
- plot([1:2^numbit-2],inl);
- grid on;
- title('INTEGRAL NONLINEARITY vs. DIGITAL OUTPUT CODE');
- xlabel('DIGITAL OUTPUT CODE');
- ylabel('INL(LSB)');
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