Closed VegardIversen closed 2 years ago
Your a
object should be a 2d array, not a 1d array. Please study https://github.com/matousc89/Python-Adaptive-Signal-Processing-Handbook/blob/master/notebooks/padasip_adaptive_filters_basics.ipynb. Especially the chapter: Construction of Input Vectors (Input Matrix) from a Time Series
Your
a
object should be a 2d array, not a 1d array. Please study https://github.com/matousc89/Python-Adaptive-Signal-Processing-Handbook/blob/master/notebooks/padasip_adaptive_filters_basics.ipynb. Especially the chapter:Construction of Input Vectors (Input Matrix) from a Time Series
But why does it need to be 2d? And when I use input_from_history I loose some of the length and then the lenght doesnt matchup anymore.
Of course the length does not match up. You can imagine the input construction as a rolling window - check out for example these pictures: https://www.mathworks.com/help/econ/rolling-window-estimation-of-state-space-models.html
Hi,
I am working witch some ecg data and want to try and remove some motion artifacts from the signal using the accelerometers data. I am following this paper, which is written in matlab code. What I tried now is this
Where a is a list of the summation of the accelerometer data and ecg is a list of ecg data (added some of it if someone want to test). I keep getting a typeError when running Hd.run(a,ecg) (TypeError: object of type 'numpy.int64' has no len())
I am a bit unsure if it is the paper I have misunderstood or the use of the adaptive filter here, but if someone has any inputs that would be nice.