Deconvolution: Inverse Convolution [DSP #12]
✅ Check out the related article on TheWolfSound.com: https://www.thewolfsound.com/deconvol... ✅ Sign up for WolfSound's newsletter: https://thewolfsound.com/newsletter/ ✅ Please subscribe to WolfSound to let the little Wolf 🐺 grow: / @wolfsoundaudio 🎧 Listen to my music: https://thewolfofficial.com/ Deconvolution is a process of inverting the effect of convolution given the output signal and one of the input signals. If both input signals are unknown, we deal with blind deconvolution. In this video, we are discussing 4 methods of non-blind deconvolution: 1. Deconvolution Using Frequency-Domain Division. 2. Deconvolution Via (Pseudo-)Inverse of the Convolution Matrix. 3. Wiener Filtering (Wiener Deconvolution). 4. Deconvolution Using Complex Cepstrum Liftering. In case of any doubt in understanding, please, refer to the article above 🙂 00:00 Introduction 00:44 Deconvolution definition 01:44 Deconvolution for loudspeaker measurement 03:01 Deconvolution Using Frequency-Domain Division 04:15 Deconvolution in Python (scipy.signal) and Matlab 05:00 Deconvolution Via (Pseudo-)Inverse of the Convolution Matrix 07:15 Wiener Filtering (Wiener Deconvolution) 10:18 Deconvolution Using Complex Cepstrum Liftering 12:21 Summary #dsp #deconvolution
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Julian Storer: Creator of JUCE C++ Framework | WolfTalk #032

the true reason C++ always wins

Blind Deconvolution Using Unconventional Beamforming

What is convolution? This is the easiest way to understand
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