# Accumulator Error Feedback

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 Revision as of 19:02, 29 January 2018 (edit) (→links)← Previous diff Revision as of 19:13, 29 January 2018 (edit) (undo)Next diff → Line 9: Line 9: % CSUM Sum of elements using a compensated summation algorithm. % CSUM Sum of elements using a compensated summation algorithm. % % - % For large vectors, the native sum command in Matlab does + % This Matlab code implements Kahan's compensated - % not appear to use a compensated summation algorithm which + - % can cause significant roundoff errors. + - % + - % This Matlab code implements a variant of Kahan's compensated + % summation algorithm (1964) which often takes about twice as long, % summation algorithm (1964) which often takes about twice as long, % but produces more accurate sums when the number of % but produces more accurate sums when the number of Line 57: Line 53: y = x(i) + e; y = x(i) + e; s_hat = s_hat_old + y; s_hat = s_hat_old + y; - e = (s_hat_old - s_hat) + y; %calculate difference first (Higham) + e = y - (s_hat - s_hat_old); %calculate parentheses first end end return return

## Revision as of 19:13, 29 January 2018

csum() in Digital Signal Processing terms: z-1 is a unit delay,
Q is a 64-bit floating-point quantizer. Algebra represents neither a sequence of instructions or algorithm. It is only meant to remind that an imperfect accumulator introduces noise into a series.
qi represents error due to quantization (additive by definition).
```function s_hat = csum(x)
% CSUM Sum of elements using a compensated summation algorithm.
%
% This Matlab code implements Kahan's compensated
% summation algorithm (1964) which often takes about twice as long,
% but produces more accurate sums when the number of
% elements is large. -David Gleich
%
% Also see SUM.
%
% % Matlab csum() Example:
% clear all
% csumv=0;  rsumv=0;
% while csumv <= rsumv
%    v = randn(13e6,1);
%    rsumv = abs(sum(v) - sum(v(end:-1:1)));
%    disp(['rsumv = ' num2str(rsumv,'%18.16f')]);
%    [~, idx] = sort(abs(v),'descend');
%    x = v(idx);
%    csumv = abs(csum(x) - csum(x(end:-1:1)));
%    disp(['csumv = ' num2str(csumv,'%18.16e')]);
% end

s_hat=0; e=0;
for i=1:numel(x)
s_hat_old = s_hat;
y = x(i) + e;
s_hat = s_hat_old + y;
e = (s_hat_old - s_hat) + y;  %calculate difference first (Higham)
end
return
```

### sorting

Sorting is not integral above because the commented Example (inspired by Higham) would then display false positive results.
In practice, input sorting should begin the csum() function to achieve the most accurate summation:

```function s_hat = csum(x)
s_hat=0; e=0;
[~, idx] = sort(abs(x),'descend');
x = x(idx);
for i=1:numel(x)
s_hat_old = s_hat;
y = x(i) + e;
s_hat = s_hat_old + y;
e = y - (s_hat - s_hat_old);  %calculate parentheses first
end
return
```

Even in complete absence of sorting, csum() can be more accurate than conventional summation by orders of magnitude.

### links

For multiplier error feedback, see: