small updates from work pc
try to implement kalman filter for MPI mitigation
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@@ -101,29 +101,6 @@ classdef FFE_FFDCAVG < handle
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end
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x = [zeros(floor(obj.order/2),1); x; zeros(obj.order,1)];
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if showviz
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f = figure(111);
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subplot(2,2,1:2);
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hold on
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a = scatter(1:numel(x),x,1,'.');
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a2 = scatter(1,1,1,'.');
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a3 = scatter(1,1,2,'.');
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a4 = xline(1);
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ylim([-3 3])
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xlim([0 length(x)]);
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% subplot(2,2,3)
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% dplot = x(1:1+500);
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% b = scatter(1:numel(dplot),dplot,5,'x');
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% xline(1)
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% xline(obj.order)
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% ylim([-3 3])
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% xlim([0 500]);
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subplot(2,2,3:4)
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c = stem(obj.e);
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ylim([-1 1])
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drawnow
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end
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for epoch = 1 : epochs
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@@ -185,19 +162,7 @@ classdef FFE_FFDCAVG < handle
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normalizationfactor = (U.' * U);
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obj.e = obj.e - err(symbol) * U / normalizationfactor; % Weight update rule of NLMS
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end
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if mod(sample,100) == 1 && showviz
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a2.XData = 1:2*numel(y);
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a2.YData = repelem(y, 2);
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a3.XData = 1:2*numel(d_hat);
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a3.YData = repelem(d_hat, 2);
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a4.Value = sample;
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% b.YData = x(symbol:symbol+500);
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c.YData = obj.e;
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drawnow;
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end
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obj.error(epoch,symbol) = err(symbol) * err(symbol)'; % Instantaneous square error
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