smoothing filter matlab code
x.^2)/(2sigma^2)); gaussianKernel = gaussianKernel / sum(gaussianKernel); % Normalize % Apply convolution y_smooth_gaussian = conv(y, gaussianKernel, 'same'); % Plot results figure; plot(x, y, 'b.', 'DisplayName'
Articles tagged with smoothing.
x.^2)/(2sigma^2)); gaussianKernel = gaussianKernel / sum(gaussianKernel); % Normalize % Apply convolution y_smooth_gaussian = conv(y, gaussianKernel, 'same'); % Plot results figure; plot(x, y, 'b.', 'DisplayName'
- K * H) * P_pred; end % Backward RTS smoothing x_smooth = x; P_smooth = P; for k = N-1:-1:1 A = P(:,:,k) * F' / (F * P(:,:,k) * F' + Q); x_smooth(:,k) = x(:,k) + A * (x_smooth(:,k+1) - F * x(:,k)); P_smooth(:,:,k) = P(:,:,k