KSVD-algorithm-based multi-channel audio processing method

A sound and audio signal technology, which is applied in the field of compressed sensing technology and multi-channel audio processing, can solve the problem that the sparse basis cannot be well adapted to various signals, achieve high probability of downsampling processing, reduce storage space, and improve The effect of refactoring speed

Inactive Publication Date: 2018-02-16
TIANJIN UNIV
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the shortcomings of common sparse bases that cannot be well adapted to various signals, the K-SVD dictionary algorithm came into being

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • KSVD-algorithm-based multi-channel audio processing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] Embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0019] The overall train of thought of the present invention is to adopt the method based on K-SVD dictionary algorithm.

[0020] Such as figure 1 As shown, the overall process of the multi-channel audio processing method based on the KSVD algorithm of the present invention comprises the following steps:

[0021] Step 101, collect representative Dolby Digital 5.1 surround sound test audio to form the sample data set of the present invention; filter the audio signal in the sample data set, and use professional software to intercept it to make it into an audio signal with the same length files for post-processing;

[0022] Step 102, set initial dictionary D 0 ∈ R n×K , so that the subsequent solution to X and the continuous update of the dictionary, let the dictionary be D j , where j represents the number of updates to the dictionary; R n×...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a KSVD-algorithm-based multi-channel audio processing method. The method comprises the following steps: step 101, forming a sample dataset; step 102, setting an initial dictionary D0 belonging to R<n*K>; step 103, carrying out sparse coding on the sample dataset; step 104, updating a dictionary atom and updating one column of dK each time; step 105, updating a correspondingexpression coefficient of the column until meeting a convergence condition, and then stopping updating to obtain a trained K-SVD dictionary; step 106, determining whether the convergence condition issatisfied; step 107, carrying out downsampling processing on a multi-audio signal needing processing by using the dictionary; step 108, restoring and reconstructing the sampled data by using a CoSaMPalgorithm; and step 109, acquiring a reconstruction signal. According to the invention, the reconstruction speed is increased to a certain extent while the high accuracy is guaranteed; down-samplingprocessing and high-probability reconstruction of the multi-channel audio signal are realized; and the function of reducing the multi-channel audio storage space is realized. The KSVD-algorithm-basedmulti-channel audio processing method has characteristics of simpleness and high efficiency.

Description

technical field [0001] The present invention relates to various fields such as compressed sensing technology and multi-channel audio processing technology, and in particular relates to a multi-channel audio processing method based on KSVD algorithm. Background technique [0002] With the continuous advancement of the information age, the theory of Compressive Sensing (CS) was formally proposed in 2006, which provides people with a new way of thinking about signal processing. As a new sampling theory, compressive sensing enables discrete sampling at a rate much smaller than the Nyquist sampling rate through the development of signal sparseness, and finally achieves perfect signal reconstruction through a series of nonlinear reconstruction algorithms. Once proposed, it has attracted widespread attention from academia and industry, and has been widely used in many fields such as image processing, earth science, microwave imaging, and wireless communication. [0003] Seeking th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G10L19/00G10L19/008
CPCG10L19/00G10L19/008
Inventor 刘昱翟丽
Owner TIANJIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap