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Noise enhancement-based linear minimum mean square error estimation method

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 detection performance and estimation accuracy degradation, small channel capacity, etc.

Active Publication Date: 2018-03-23
CHONGQING UNIV
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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

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  • Noise enhancement-based linear minimum mean square error estimation method
  • Noise enhancement-based linear minimum mean square error estimation method
  • Noise enhancement-based linear minimum mean square error estimation method

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[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 ...

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Abstract

The invention discloses a noise enhancement-based linear minimum mean square error estimation method, and belongs to the field of signal processing. The method is a linear estimation method which combines noise enhancement with a linear minimum mean square error estimation method. The method comprises the following steps of: firstly adding independent additive noise for a nonlinear system input signal, and obtaining a noise added nonlinear system output signal through a nonlinear system; carrying out linear minimum mean square error estimation on an input parameter by utilizing the nonlinear system output signal, and establishing a noise enhanced parameter estimation model; and finally solving optimum additive noise under the model and obtaining parameter estimation under the optimum additive noise. According to the method, noise enhancement and a linear minimum mean square estimation method are combined, and through adding noise for the nonlinear system input, the aim of further decreasing the minimum mean square error generated when linear estimation is carried out on the input parameter by the system output signal is achieved.

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....

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Application Information

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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
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