A Linear Minimum Mean Square Error Estimation Method Based on Noise Enhancement

A minimum mean square error and mean square error technology, applied in the field of noise enhancement and linear minimum mean square error estimation, can solve the problems of small channel capacity, detection performance and estimation accuracy degradation, etc.

Active Publication Date: 2020-11-03
CHONGQING UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

More noise in the system will lead to smaller channel capacity, which will lead to a decrease in detection performance and estimation accuracy

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
  • A Linear Minimum Mean Square Error Estimation Method Based on Noise Enhancement
  • A Linear Minimum Mean Square Error Estimation Method Based on Noise Enhancement
  • A Linear Minimum Mean Square Error Estimation Method Based on Noise Enhancement

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The present invention will be further described below in conjunction with the examples, but it should not be understood that the scope of the subject of the present invention is limited to the following examples. Without departing from the above-mentioned technical ideas of the present invention, various replacements and changes made according to common technical knowledge and conventional means in this field shall be included in the protection scope of the present invention.

[0032] This embodiment discloses a noise-enhanced linear minimum mean square error estimation method, including the following steps:

[0033] (1) Establish a noise enhancement parameter estimation model:

[0034] Nonlinear system input signal x=θ+v, where θ is a useful input parameter to be estimated, and the value of θ is determined by its probability density function p θ (θ) determined, v represents the background noise, and its probability density function is p v (v).

[0035] First, add ...

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 linear minimum mean square error estimation method based on noise enhancement. It belongs to the field of signal processing. It is a linear estimation method that combines noise enhancement and a linear minimum mean square error estimation method. First add additive noise independent of the nonlinear system input signal, and obtain the nonlinear system output signal after the noise is added after the nonlinear system, and then use the nonlinear system output signal to perform linear minimum mean square error estimation on the input parameters , establish a noise-enhanced parameter estimation model, and finally solve the optimal additive noise under the model, and obtain the parameter estimation under the optimal additive noise. The invention combines the noise enhancement with the linear minimum mean square error estimation method, and achieves the purpose of further reducing the minimum mean square error generated when the system output signal linearly estimates the input parameters by adding noise to the nonlinear system input.

Description

technical field [0001] The invention belongs to the field of signal processing, in particular to noise enhancement and linear minimum mean square error estimation. Background technique [0002] Noise is everywhere, and understanding and mastering the distribution and performance of noise is a very important issue. In classical signal processing, noise is viewed as an unwanted signal or disturbance to a system. More noise in the system will lead to smaller channel capacity, thus degrading the detection performance and estimation accuracy. However, the impact of noise on the system is not all negative. Under certain conditions, noise can positively enhance the signal and system through the nonlinear system, which is called noise enhancement phenomenon. With the in-depth exploration and application research on noise enhancement in recent years, the important role played by noise enhancement in signal detection and estimation has gained more and more attention and affirmation....

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 Patents(China)
IPC IPC(8): G06F17/18G06K9/00
CPCG06F17/18G06F2218/00
Inventor 刘书君杨婷唐明春周喜川李勇明
Owner CHONGQING 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