Method for correcting time error between sub converters of double-channel analog-to-digital converter on basis of machine learning

An analog-to-digital converter, time error technology, applied in the direction of analog/digital conversion calibration/test, analog/digital conversion, code conversion, etc., can solve problems such as time mismatch error

Inactive Publication Date: 2018-05-04
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] In order to solve the problems caused by the time mismatch error between single sub-data collectors, the technical solution adopted by the present invention is:

Method used

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  • Method for correcting time error between sub converters of double-channel analog-to-digital converter on basis of machine learning
  • Method for correcting time error between sub converters of double-channel analog-to-digital converter on basis of machine learning
  • Method for correcting time error between sub converters of double-channel analog-to-digital converter on basis of machine learning

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Embodiment Construction

[0046] Below in conjunction with accompanying drawing and specific embodiment the present invention will be further described:

[0047] Such as figure 1 Shown is a schematic diagram of the structure of a dual-channel analog-to-digital converter time-alternating analog-to-digital conversion system, including two sub-converters. The whole system is composed of two sub-analog-to-digital converters working in parallel with an acquisition time interval of 2Ts, and the total operating frequency is fs=1 / Ts, where Ts is the total acquisition period of the converter. Each sub-converter works in parallel, and the input analog signal xc(t) is collected by two sub-converters in parallel and then restored to an uncorrected analog-to-digital converter with time error mismatch through the multiplexer MUX Non-ideal non-uniform digital signal y[n]. Then, the supervised machine learning method in the present invention is used for y[n] to restore the ideal signal.

[0048] Such as figure 2 ...

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Abstract

The invention discloses a method for correcting a time error between sub converters of a double-channel analog-to-digital converter on the basis of machine learning, which comprises the steps of: carrying out chopping on a total output of the analog-to-digital converter, then obtaining a signal with a phase different of 90 degrees from a chopping signal by a Hilbert filter, then multiplying the signal by an original analog-to-digital converter output signal to obtain a feedback signal component closely related to the error, and extracting a corresponding error component to obtain an error signal; injecting the error signal into a feedback loop, according to taylor expansion correlation calculation, obtaining a corresponding deviation of sampling time among samplers; and adding the deviation of the signals, which is caused by a time error among the plurality of samplers, into an original acquired signal, carrying out correction on the error and completing recovery of data.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a method for correcting time errors between sub-converters of a dual-channel analog-to-digital converter based on machine learning. Background technique [0002] Today, with the widespread application of artificial intelligence, the requirements for human-computer interaction and environmental-machine interaction are getting higher and higher. In many application scenarios, we need the computing speed of the machine to be very fast. For example, in a self-driving car, we need to pay attention to the road condition information in real time, so that we can take corresponding measures in any case, especially when the car is driving at high speed, the collection and processing speed of road condition information is higher. The football game robot's judgment of the football position and track information also requires the support of a high-speed collection information...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03M1/06H03M1/10
CPCH03M1/0629H03M1/1009
Inventor 刘素娟李泽
Owner BEIJING UNIV OF TECH
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