Frequency domain blind separation method and system with low complexity
A low-complexity, blind separation technology, applied in the field of low-complexity frequency-domain blind separation methods and systems, can solve problems such as weakening inter-frequency correlations
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0093] Embodiment 1 of the present invention provides a low-complexity frequency-domain blind separation system, and the system specifically includes:
[0094] Such as figure 1 as shown, figure 1It is a block diagram of a signal mixing and separation system, including a mixing system module 101 and a separation system module 102 . Each sound source signal reaches the microphone through different transmission paths, and the microphone receives the mixed observation signal, and then passes through the separation system to obtain the estimation of the sound source.
[0095] The hybrid system module 101 is to combine N sound source signals s 1 (t),s 2 (t),...,s N (t) and room impulse response h ji (t) (representing the FIR impulse response of length P between the i-th sound source and the j-th microphone) is convoluted and combined to obtain M observation signals x 1 (t),x 2 (t),...,x M (t).
[0096] The separation system module 102 is to observe the signal x through the ...
Embodiment 2
[0150] Embodiment 2 of the present invention provides a low-complexity frequency-domain blind separation method, which specifically includes:
[0151] Step 1) performing short-time Fourier transform on the mixed signal collected by the microphone array to obtain a frequency domain signal, and independently using the complex ICA algorithm to separate the sound source at each frequency point; obtaining the separated signal of each frequency point;
[0152] Step 1-1) Receive observation signal x from M microphones j (t) After the short-time Fourier transform with a window length of Q point, the frequency domain signal X is obtained j (l,f), t is the time; 1≤j≤M, l is the time index, 1≤l≤B, B represents the total number of frames processed by the mixed data frame; f is the frequency index, f s is the sampling frequency; x(l,f)=[X 1 (l,f),X 2 (l,f),...,X M (l,f)] T is the observed signal frequency domain vector;
[0153] Step 1-2) Use the frequency domain ICA algorithm to i...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com