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Random sampling method based on information distribution mode

A distribution mode, random sampling technology, applied in genetic models, random number generators, genetic rules, etc., can solve problems such as Nyquist sampling aliasing

Active Publication Date: 2018-07-24
中科观世(北京)科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the practice of "compressed sampling" theory, it is found that Nyquist sampling in "compressed sampling" will still follow the law of sampling theorem and appear "aliasing" phenomenon

Method used

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  • Random sampling method based on information distribution mode
  • Random sampling method based on information distribution mode
  • Random sampling method based on information distribution mode

Examples

Experimental program
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Effect test

Embodiment 1

[0073] Embodiment 1: Spectrum analysis of audio signal

[0074] For a piece of audio signal, when the signal distribution mode is unknown, first use the sampling points of various distribution modes of the Y distribution to conduct sampling experiments, and at the same time apply the Nyquist sampling points for sampling, and then pass the Y distribution mode The sampling is compared with the reconstructed original signal information features of the Nyquist pattern sampling. Through experiments: when the Nyquist sampling rate is 44.1KHz, a high-fidelity sound effect can be obtained; and when the same sound effect is sampled in the Y distribution mode, the normal distribution 15 sampling rate only needs 400Hz to obtain the same sound effect as the Nyquist When the Qwest sampling rate is 44.1KHz, the data set whose distortion error is less than 0.3%. The normal distribution15 in the Y distribution mode produced the solution with the highest fitness, which we exported, obtained a...

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Abstract

The invention discloses a random sampling method based on an information distribution mode, relating to a method for adaptively establishing a random sampling point that has similar distribution characteristics with an original signal distribution mode to perform original signal acquisition. The device adopted by the method mainly consists of a signal acquisition module (1), a signal sensor (5), an FIFO module (8), a random data generation module (9), a computer (10), a Y distribution module (12) and a signal analysis module (13). When the sound bandwidth is 22.05KHz, the Nyquist sampling rateneeds to take 44.1KHz, and the original sound can be completely reconstructed; however, when reconstructing the original sound by using normal distribution mode sampling, the sampling frequency onlyneeds to take 400Hz, and the sound effect with an error of less than 0.3% can be obtained; and in the case of obtaining the same signal resolution by using Y distribution mode sampling and Nyquist mode sampling, the data volume of Y distribution mode sampling can be greatly compressed.

Description

technical field [0001] The invention belongs to the technical field of signal detection and information acquisition, in particular to a pseudo-random sampling technology established based on information distribution. Background technique [0002] Sampling is the mathematical method of converting a signal of interest into a sequence of values. The collection point where the target signal data is collected at the corresponding time is called the sampling point, the sampling process of the sample is called sample sampling, and the signal value of each sample is called a sampling sample; the time gap between two sampling points is called the sampling interval ;The time interval of signal sampling is very small, which can be on the order of milliseconds, microseconds or even nanoseconds; the time function of the sampling point is x(t), and the signal value collected at the sampling point is the signal level, through analog / digital conversion , to convert an analog signal level v...

Claims

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Application Information

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IPC IPC(8): H03M1/12G06F7/58G06N3/12
CPCG06F7/588G06N3/126H03M1/128
Inventor 姚萌苏勇飞叶征宇
Owner 中科观世(北京)科技有限公司
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