Accumulator Error Feedback
From Wikimization
(Difference between revisions)
Line 18: | Line 18: | ||
% | % | ||
% clear all | % clear all | ||
- | % % v=sort(randn(13e6,1),'descend'); %better when sorted | + | % % v = sort(randn(13e6,1),'descend'); %better when sorted |
- | % v=randn(13e6,1); | + | % v = randn(13e6,1); |
% rsumv = abs(sum(v) - sum(v(end:-1:1))); | % rsumv = abs(sum(v) - sum(v(end:-1:1))); | ||
% disp(['rsumv = ' num2str(rsumv,'%18.16f')]); | % disp(['rsumv = ' num2str(rsumv,'%18.16f')]); |
Revision as of 18:23, 25 September 2017
function s_hat=csum(x) % CSUM Sum of elements using a compensated summation algorithm. % % For large vectors, the native sum command in Matlab does % not appear to use a compensated summation algorithm which % can cause significant roundoff errors. % % This code implements a variant of Kahan's compensated % summation algorithm which often takes about twice as long, % but produces more accurate sums when the number of % elements is large. -David Gleich % % See also SUM % % clear all % % v = sort(randn(13e6,1),'descend'); %better when sorted % v = randn(13e6,1); % rsumv = abs(sum(v) - sum(v(end:-1:1))); % disp(['rsumv = ' num2str(rsumv,'%18.16f')]); % csumv = abs(csum(v) - csum(v(end:-1:1))); % disp(['csumv = ' num2str(csumv,'%18.16f')]); % % vsumv = sum(vpa(v)) - sum(vpa(v(end:-1:1))); %vpa toolbox 32GB RAM % % disp(['vsumv = ' char(vsumv)]) 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
links
Accuracy and Stability of Numerical Algorithms 2e, ch.4.3, Nicholas J. Higham, 2002
For multiplier error feedback, see:
Implementation of Recursive Digital Filters for High-Fidelity Audio
Comments on Implementation of Recursive Digital Filters for High-Fidelity Audio