CN112311518A - Time domain data preprocessing method based on frequency domain prediction - Google Patents
Time domain data preprocessing method based on frequency domain prediction Download PDFInfo
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- CN112311518A CN112311518A CN202011213030.2A CN202011213030A CN112311518A CN 112311518 A CN112311518 A CN 112311518A CN 202011213030 A CN202011213030 A CN 202011213030A CN 112311518 A CN112311518 A CN 112311518A
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- H—ELECTRICITY
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- H04L5/00—Arrangements affording multiple use of the transmission path
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- H04L5/0003—Two-dimensional division
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- H04L5/0007—Time-frequency the frequencies being orthogonal, e.g. OFDM(A), DMT
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- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
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Abstract
The invention discloses a time domain data preprocessing method based on frequency domain prediction, which comprises the steps of reading a time sequence, storing the time sequence data in a file by adopting binary coding, wherein the file consists of a plurality of segments of data, and each segment of data comprises the time sequence and header file information; reading file data, namely writing a function file by adopting a Matlab language to read the time sequence data, and finishing reading file information and time domain data; mapping the read file data to a plurality of subcarriers to obtain frequency domain data blocks; performing N/4-point discrete Fourier transform on the frequency domain data block; carrying out post-rotation processing on the data subjected to the discrete Fourier transform by using a twiddle factor to obtain frequency domain data; and (5) Hanning window processing. The time domain processing method provided by the invention can respectively preprocess the known sequence data by utilizing the mutual information among the data, so that the detection precision is high, the realization structure is simple, the obtained preprocessing structure has strong accuracy and can directly reflect the information among the data.
Description
Technical Field
The invention relates to the technical field of time domain data preprocessing, in particular to a time domain data preprocessing method based on frequency domain prediction.
Background
In recent years, data mining has attracted great attention in the information industry, mainly because there are a large amount of data that can be widely used, and there is an urgent need to find and refine useful information and knowledge from these data to be widely applied to various fields.
The time domain processing is a recognization process for explaining original data, which is a necessary step in the data processing process, and subsequent qualitative and quantitative explanation works are all performed on the basis.
The traditional time domain data processing mode does not well utilize mutual information among data, and an obtained preprocessing structure is difficult to avoid distortion and cannot accurately reflect more information among data.
Therefore, a time domain data preprocessing method based on frequency domain prediction is provided for solving the problems.
Disclosure of Invention
The present invention aims to provide a time domain data preprocessing method based on frequency domain prediction to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a time domain data preprocessing method based on frequency domain prediction comprises the following steps:
s1: reading a time sequence, wherein the time sequence data stored in a file adopts binary coding, the file consists of a plurality of data segments, and each data segment comprises the time sequence and header file information;
s2: reading file data, namely writing a function file by adopting a Matlab language to read the time sequence data, and finishing reading file information and time domain data;
s3: mapping the read file data to a plurality of subcarriers to obtain frequency domain data blocks;
s4: performing N/4-point discrete Fourier transform on the frequency domain data block;
s5: carrying out post-rotation processing on the data subjected to the discrete Fourier transform by using a twiddle factor to obtain frequency domain data;
s6: hanning window processing, when the length of the frequency domain data is limited, performing FFT time-frequency transformation to generate a truncation effect, and at the moment, windowing the frequency domain data before the FFT time-frequency transformation;
s7: power spectrum analysis, namely estimating a power spectrum according to an FFT frequency spectrum obtained by FFT time-frequency transformation;
s8: performing power spectrum processing, namely performing smooth estimation on the initial power spectrum by adopting two modes of overall smoothing and frequency smoothing;
s9: and (4) impedance estimation, namely performing impedance estimation by adopting a least square method to finally obtain time domain data with specific parameters.
Preferably, the discrete fourier transform process further includes:
the pre-rotation unit is used for performing pre-rotation processing on the data obtained by the pre-processing unit by using a rotation factor;
the Fourier transform unit is used for carrying out N/4-point discrete Fourier transform on the data processed by the first pre-rotation unit;
and the post-rotation unit is used for performing post-rotation processing on the data subjected to the discrete Fourier transform by the Fourier transform unit by using the rotation factor to obtain frequency domain data.
Compared with the prior art, the invention has the beneficial effects that: the time domain processing method provided by the invention can respectively preprocess the known sequence data by utilizing the mutual information among the data, so that the detection precision is high, the realization structure is simple, the obtained preprocessing structure has strong accuracy and can directly reflect the information among the data.
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FIG. 1 is a schematic flow diagram of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a time domain data preprocessing method based on frequency domain prediction comprises the following steps:
s1: reading a time sequence, wherein the time sequence data stored in a file adopts binary coding, the file consists of a plurality of data segments, and each data segment comprises the time sequence and header file information;
s2: reading file data, namely writing a function file by adopting a Matlab language to read the time sequence data, and finishing reading file information and time domain data;
s3: mapping the read file data to a plurality of subcarriers to obtain frequency domain data blocks;
s4: performing N/4-point discrete Fourier transform on the frequency domain data block;
s5: carrying out post-rotation processing on the data subjected to the discrete Fourier transform by using a twiddle factor to obtain frequency domain data;
s6: hanning window processing, when the length of the frequency domain data is limited, performing FFT time-frequency transformation to generate a truncation effect, and at the moment, windowing the frequency domain data before the FFT time-frequency transformation;
s7: power spectrum analysis, namely estimating a power spectrum according to an FFT frequency spectrum obtained by FFT time-frequency transformation;
s8: performing power spectrum processing, namely performing smooth estimation on the initial power spectrum by adopting two modes of overall smoothing and frequency smoothing;
s9: and (4) impedance estimation, namely performing impedance estimation by adopting a least square method to finally obtain time domain data with specific parameters.
Wherein, the discrete Fourier transform process further comprises:
the pre-rotation unit is used for performing pre-rotation processing on the data obtained by the pre-processing unit by using a rotation factor;
the Fourier transform unit is used for carrying out N/4-point discrete Fourier transform on the data processed by the first pre-rotation unit;
and the post-rotation unit is used for performing post-rotation processing on the data subjected to the discrete Fourier transform by the Fourier transform unit by using the rotation factor to obtain frequency domain data.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (2)
1. A time domain data preprocessing method based on frequency domain prediction is characterized by comprising the following steps:
s1: reading a time sequence, wherein the time sequence data stored in a file adopts binary coding, the file consists of a plurality of data segments, and each data segment comprises the time sequence and header file information;
s2: reading file data, namely writing a function file by adopting a Matlab language to read the time sequence data, and finishing reading file information and time domain data;
s3: mapping the read file data to a plurality of subcarriers to obtain frequency domain data blocks;
s4: performing N/4-point discrete Fourier transform on the frequency domain data block;
s5: carrying out post-rotation processing on the data subjected to the discrete Fourier transform by using a twiddle factor to obtain frequency domain data;
s6: hanning window processing, when the length of the frequency domain data is limited, performing FFT time-frequency transformation to generate a truncation effect, and at the moment, windowing the frequency domain data before the FFT time-frequency transformation;
s7: power spectrum analysis, namely estimating a power spectrum according to an FFT frequency spectrum obtained by FFT time-frequency transformation;
s8: performing power spectrum processing, namely performing smooth estimation on the initial power spectrum by adopting two modes of overall smoothing and frequency smoothing;
s9: and (4) impedance estimation, namely performing impedance estimation by adopting a least square method to finally obtain time domain data with specific parameters.
2. The time-domain data preprocessing method based on frequency-domain prediction as claimed in claim 1, wherein: the discrete Fourier transform process further comprises:
the pre-rotation unit is used for performing pre-rotation processing on the data obtained by the pre-processing unit by using a rotation factor;
the Fourier transform unit is used for carrying out N/4-point discrete Fourier transform on the data processed by the first pre-rotation unit;
and the post-rotation unit is used for performing post-rotation processing on the data subjected to the discrete Fourier transform by the Fourier transform unit by using the rotation factor to obtain frequency domain data.
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Citations (5)
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|---|---|---|---|---|
| US20050207565A1 (en) * | 2004-03-04 | 2005-09-22 | Mitel Networks Corporation | Method of selecting impedance setting for loop start trunk line |
| CN101930425A (en) * | 2009-06-24 | 2010-12-29 | 华为技术有限公司 | Signal processing method, data processing method and device |
| JP2011243002A (en) * | 2010-05-18 | 2011-12-01 | Mitsubishi Chemicals Corp | Data processing method, data processing device, data display method, data display device, data processing system, client device, recording medium and program |
| CN103078825A (en) * | 2013-01-30 | 2013-05-01 | 清华大学 | Method and device for generating frame synchronizing sequence in digital communication system |
| CN111739555A (en) * | 2020-07-23 | 2020-10-02 | 深圳市友杰智新科技有限公司 | Audio signal processing method and device based on end-to-end deep neural network |
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- 2020-11-04 CN CN202011213030.2A patent/CN112311518A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050207565A1 (en) * | 2004-03-04 | 2005-09-22 | Mitel Networks Corporation | Method of selecting impedance setting for loop start trunk line |
| CN101930425A (en) * | 2009-06-24 | 2010-12-29 | 华为技术有限公司 | Signal processing method, data processing method and device |
| JP2011243002A (en) * | 2010-05-18 | 2011-12-01 | Mitsubishi Chemicals Corp | Data processing method, data processing device, data display method, data display device, data processing system, client device, recording medium and program |
| CN103078825A (en) * | 2013-01-30 | 2013-05-01 | 清华大学 | Method and device for generating frame synchronizing sequence in digital communication system |
| CN111739555A (en) * | 2020-07-23 | 2020-10-02 | 深圳市友杰智新科技有限公司 | Audio signal processing method and device based on end-to-end deep neural network |
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Application publication date: 20210202 |