Adaptive filtering in STFT domain example seems broken.
See original GitHub issuesmth like this should do the trick
time_indx = 0
for n in range(num_blocks):
# update filter with new samples
adaptive_filters.update(X_concat[:, n], Y_concat[:, n])
aec_out[time_indx: time_indx + hop] = stft_out.synthesis(Y_concat[:, n] - np.diag(np.dot(adaptive_filters.W.conj().T, adaptive_filters.X)))
time_indx += hop
Issue Analytics
- State:
- Created a year ago
- Comments:6
Top Results From Across the Web
pyroomacoustics/adaptive_filter_stft_domain.py at master
In this example, we will run adaptive filters for system. identification, but in the frequeny domain. """ from __future__ import division, print_function.
Read more >Application of Adaptive Filtering Based on Variational Mode ...
Aiming at this problem, this paper proposes the least mean square adaptive filtering interpolation denoising method based on variational modal decomposition ( ...
Read more >Adaptive Filtering — Pyroomacoustics 0.6.0 documentation
First, an adaptive filter object is created and all the relevant options can be set (step size, regularization, etc). Then, the update function...
Read more >Frequency-domain and multirate adaptive filtering
(finite impulse response) filter coefficients are needed to achieve the desired level of performance in channel.
Read more >Acoustic feedback cancellation in hearing aids using dual ...
In this paper, we propose a probe signal-based adaptive filtering method for acoustic feedback cancellation (AFC) in hearing aids.
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
I can close this issue, thanks !
it looks good to me !