CN116707491A - FIR low-pass digital filtering method for reducing resource consumption - Google Patents

FIR low-pass digital filtering method for reducing resource consumption Download PDF

Info

Publication number
CN116707491A
CN116707491A CN202310529677.3A CN202310529677A CN116707491A CN 116707491 A CN116707491 A CN 116707491A CN 202310529677 A CN202310529677 A CN 202310529677A CN 116707491 A CN116707491 A CN 116707491A
Authority
CN
China
Prior art keywords
filtering
fir
resource consumption
average
filtering method
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310529677.3A
Other languages
Chinese (zh)
Inventor
陈玥
焦妍瑞
马佩军
史江义
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xidian University
Original Assignee
Xidian University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xidian University filed Critical Xidian University
Priority to CN202310529677.3A priority Critical patent/CN116707491A/en
Publication of CN116707491A publication Critical patent/CN116707491A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0223—Computation saving measures; Accelerating measures
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0248—Filters characterised by a particular frequency response or filtering method
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0248—Filters characterised by a particular frequency response or filtering method
    • H03H17/026—Averaging filters
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0294—Variable filters; Programmable filters
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H2017/0072—Theoretical filter design
    • H03H2017/0081—Theoretical filter design of FIR filters
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0223—Computation saving measures; Accelerating measures
    • H03H2017/0245—Measures to reduce power consumption
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H17/00—Networks using digital techniques
    • H03H17/02—Frequency selective networks
    • H03H17/0294—Variable filters; Programmable filters
    • H03H2017/0295—Changing between two filter characteristics
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Mathematical Physics (AREA)
  • Computing Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Complex Calculations (AREA)

Abstract

The application provides an FIR low-pass digital filtering method for reducing resource consumption, which is characterized in that a filtering condition required when the filtering effects of an average filtering method and an FIR filtering method are consistent is determined by comparing the filtering form of the average filtering method with the filtering form of the FIR filtering method; determining the filtering times according to the design parameters of the filtering effect; obtaining a filtering operation point proportion according to the required filtering condition and the filtering times; and filtering the signal to be filtered according to the filtering times by utilizing the filtering operation point proportion. The application can effectively inhibit the influence of various interference signals in the data acquisition process by continuously using the average filtering with the optimal calculation point number ratio for two times, improves the filtering effect, greatly reduces the resource consumption, can perform high-performance calculation under the condition of extremely low calculation resource consumption, and is convenient for the designer to filter.

Description

FIR low-pass digital filtering method for reducing resource consumption
Technical Field
The application belongs to the technical field of digital signal processing, and particularly relates to an FIR low-pass digital filtering method for reducing resource consumption.
Background
The average filtering is a filtering algorithm which is relatively commonly used in various application scenes, and the filtering effect is realized by carrying out average value calculation on N continuous sampling points. When the value of N is larger, the output is smoother, the filtering effect is strong, but the response to parameter change is slow, the adjustment is not timely, the hysteresis is serious, and the sensitivity is low; on the contrary, when the value of N is smaller, the reaction and adjustment are timely, the sensitivity is high, the output smoothness is low, and the filtering effect is not obvious.
In engineering applications, if the average filtering method is selected, the number of filtering operation points N should be generally selected according to the parameter characteristics and the filtering requirements of the signal, which requires a more thorough analysis of the Finite Impulse Response (FIR) mathematical principle and the filtering operation characteristics of average filtering.
At present, three solutions for the number of the average filtering operation points N are available, namely an empirical value method, a numerical experiment method and an improved filtering algorithm. There are certain limitations to using empirical values. The numerical experiment method selects reasonable N values through different value trial methods, and has certain flexibility compared with an empirical value method, but has the characteristics of large trial times/calculated amount, insufficient definition of optimal design points of filter characteristics and the like.
The technical staff aims at the actual problem to improve the filtering algorithm, so that engineering data are required to be acquired and the algorithm is combined for targeted improvement, and the difficulty is high.
Disclosure of Invention
In order to solve the above problems in the prior art, the present application provides an FIR low-pass digital filtering method for reducing resource consumption. The technical problems to be solved by the application are realized by the following technical scheme:
the application provides an FIR low-pass digital filtering method for reducing resource consumption, which comprises the following steps:
s100, obtaining a filtering form of an average filtering method and a filtering form of an FIR filtering method;
s200, comparing the filtering form of the average filtering method with the filtering form of the FIR filtering method, and determining the required filtering condition when the filtering effects of the filtering form and the filtering form are consistent;
s300, determining the filtering times according to design parameters of the filtering effect;
s400, obtaining a filtering operation point proportion according to the required filtering condition and the filtering times in S200;
s500, filtering the signal to be filtered according to the filtering times by utilizing the filtering operation point proportion.
The beneficial effects are that:
the application provides an FIR low-pass digital filtering method for reducing resource consumption, which is characterized in that a filtering mode of an average filtering method is compared with a filtering mode of an FIR filtering method, and a required filtering condition is determined when the filtering effects of the filtering mode and the filtering mode are consistent; determining the filtering times according to the design parameters of the filtering effect; obtaining a filtering operation point proportion according to the required filtering condition and the filtering times; and filtering the signal to be filtered according to the filtering times by utilizing the filtering operation point proportion. The application continuously uses the average filtering with the optimal proportion twice, can effectively inhibit the influence of various interference signals in the data acquisition process, improves the filtering effect, greatly reduces the resource consumption, can perform high-performance calculation under the condition of extremely low calculation resource consumption, and is convenient for the designer to filter.
The present application will be described in further detail with reference to the accompanying drawings and examples.
Drawings
FIG. 1 is a flow chart of a method of FIR low-pass digital filtering for reducing resource consumption provided by an embodiment of the present application;
FIG. 2a is a flowchart of an averaging filtering algorithm provided by an embodiment of the present application;
FIG. 2b is an algorithm diagram of a coefficient congruent (1/N) FIR low-pass filter provided by an embodiment of the present application;
FIG. 3a is a schematic diagram of the resource classification consumed by a coefficient congruent (1/N) FIR low-pass filter according to an embodiment of the present application;
FIG. 3b is a statistical graph of the resources consumed by the FIR low-pass filter with congruent coefficients (1/N) provided by an embodiment of the present application;
FIG. 4a is a schematic diagram of the resource classification consumed by the twice-average filtering algorithm according to an embodiment of the present application;
FIG. 4b is a statistical graph of the resources consumed by the twice-average filtering algorithm provided by an embodiment of the present application;
fig. 5a is a zero distribution diagram with the number of filtering operation points of 8 and 12 respectively for two times according to the embodiment of the present application;
fig. 5b is a waveform diagram of the number of the two filtering operations provided by the embodiment of the present application being 8 and 12 respectively;
fig. 6 is a waveform diagram of the number of the two filtering operations provided by the embodiment of the application being 16 and 24 respectively.
Detailed Description
The present application will be described in further detail with reference to specific examples, but embodiments of the present application are not limited thereto.
As shown in fig. 1, the present application provides an FIR low-pass digital filtering method for reducing resource consumption, which includes:
s100, obtaining a filtering form of an average filtering method and a filtering form of an FIR filtering method;
the filtering form of the average filtering method and the filtering form of the FIR filtering method are respectively expressed as follows:
wherein x (N) represents the current measurement value, x (N-1) represents the previous measurement value of 1 time, x (N-n+1) is the previous measurement value of N-1 time, and N represents the number of filtering operation points.
The unit impulse response h (mu) length of the FIR is M, and the system function and the difference equation of the FIR filtering method are expressed as follows:
s200, comparing the filtering form of the average filtering method with the filtering form of the FIR filtering method, and determining the required filtering condition when the filtering effects of the filtering form and the filtering form are consistent;
the application analyzes the characteristic of N-point average filtering by analyzing the mathematical relationship to obtain the FIR low-pass filter with the mathematical nature of the N-point average filtering being the coefficient congruent (1/N).
Order the
The filtering form of the FIR filtering method is as follows:
where H (z) is the system function and y (μ) is the differential equation.
Comparing the formulas (1) and (4) is clearly identical. This means that the N term arithmetic average filtering corresponds to a filtering algorithm performed on the sequence x (N) with an N term coefficient 1/N FIR filter. The nature of arithmetic average filtering is in fact a FIR filter;
therefore, the required filtering condition when the two filtering effects are consistent in S200 is expressed as:
s300, determining the filtering times according to design parameters of the filtering effect;
the design parameter of the filtering effect in S300 is that the stop band peak value is below-30 dB; the number of times of filtering was 2.
The filtering effect is optimized by a convolution method. The dips of the zero control amplitude-frequency response are uniformly distributed in a unit circle and appear on the radian of 2npi/N (n=1, 2, … N-1), and the peak value is about the midpoint of the two dips. In order to make the low-pass filtering effect better, the peak value needs to be pulled down to a greater extent, and the peak value can be pulled down by carrying out the average filtering with different filtering operation points for two times so that the trough of the second time corresponds to the peak value of the first time.
S400, obtaining a filtering operation point proportion according to the required filtering condition and the filtering times in S200;
in S400, the number of the first filtering operation points is P, the number of the second filtering operation points is Q, and the ratio of the number of the filtering operation points is P: q=2:3.
As can be seen from the zero point profile and the waveform diagram in fig. 5a and 5b when the filter operation point n=8, the peak value of the filter operation point n=8 is approximately at 3 pi/8, 5 pi/8, 7 pi/8, 9 pi/8, 11 pi/8, 13 pi/8. Because the valleys are uniformly distributed on the unit circle, the unit circle is complemented by the peak intervals, i.e. the most ideal second filtering corresponds to the valleys in pi/8, 3 pi/8, 5 pi/8, 7 pi/8, 9 pi/8, 11 pi/8, 13 pi/8, 15 pi/8. N=16 can be taken, but in order to save resources and simplify operation, the valley points pi/2, pi and 3 pi/2 are reserved, namely 11 valley points are needed, and n=12 is taken as the filtering operation point of the second average filtering. As shown in the curves of the filter operation points n=8 and n=12 in fig. 5, the stopband amplitude of the filtering result of the primary average filtering is higher, the first stopband peak value is about-13 dB, and the filtering effect is not ideal. In order to optimize the filtering effect, after the average filtering with the number of the filtering operation points N=8 is carried out once, the average filtering with the number of the filtering operation points N=12 is carried out once again, so that the stop band peak value can be effectively lowered, and the stop band peak value can be below-30 dB.
According to the above deduction, the first filtering operation point can be selected by using an empirical value or a trial and error method in the practical application, and the second filtering operation point can be optimized by using a 2:3 ratio. Fig. 6 shows the filtering effect of the first filtering operation point n=16 and the second filtering operation point n=24.
As shown in fig. 2a, the method performs average filtering with two preferred ratios, and specifically comprises the following steps: the first time of the selected filter operation point number is P, the data is subjected to addition processing and division processing, the first time of the filter result is subjected to second time of filtering, the second time of the selected operation point number is Q (P: Q=2: 3), and the data is subjected to addition processing and division processing, so that a final filter result is obtained
S500, filtering the signal to be filtered according to the filtering times by utilizing the filtering operation point proportion.
The application can set the ratio of the number of filtering operation points to 2:3, and uses an average filtering method to continuously filter the signal to be filtered twice.
After S500, the FIR low-pass digital filtering method for reducing resource consumption of the present application further includes:
s610, setting a filtering operation point ratio of 2:3, and carrying out continuous twice filtering on the signal to be filtered by using an FIR filtering method;
s620, acquiring first computing resources required by the average filtering method when filtering the signal to be filtered and second computing resources required by the FIR filtering method when filtering the signal to be filtered;
wherein the first computing resources are N (p+q) additions and 2N multiplications; the second computing resources are N (P+Q) multiplications and N (P-1) +N (Q-1) additions.
S630, comparing the first computing resource with the second computing resource to obtain a resource consumption result.
The application compares the twice average filtering method with the resources consumed by the FIR filtering method. The resource consumption maps are respectively fig. 3a, 3b, 4a and 4b. On the premise of finding the same filtering effect, the twice average filtering method has lower resources. This is because, when the average filtering is performed twice, if the number of the double convolution points is P, Q, respectively, the (p+q) addition and the 2 multiplications are required for outputting 1 point, and the N (p+q) addition and the 2N multiplications are required for outputting N points. When the generalized floating-point convolution performs FIR filtering, P multiplications and (P-1) additions are required to output one point, NP multiplications and N (P-1) additions are required to output N points, and under the same data processing, N (p+q) multiplications and N (P-1) +n (Q-1) additions are required to perform FIR filtering, whereas additions and divisions are not at all of one order of magnitude in terms of resource consumption.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Although the application is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed application, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality.
The foregoing is a further detailed description of the application in connection with the preferred embodiments, and it is not intended that the application be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the application, and these should be considered to be within the scope of the application.

Claims (8)

1. A method of FIR low-pass digital filtering for reducing resource consumption, comprising:
s100, obtaining a filtering form of an average filtering method and a filtering form of an FIR filtering method;
s200, comparing the filtering form of the average filtering method with the filtering form of the FIR filtering method, and determining the required filtering condition when the filtering effects of the filtering form and the filtering form are consistent;
s300, determining the filtering times according to design parameters of the filtering effect;
s400, obtaining a filtering operation point proportion according to the required filtering condition and the filtering times in S200;
s500, filtering the signal to be filtered according to the filtering times by utilizing the filtering operation point proportion.
2. The FIR low-pass digital filtering method for reducing resource consumption according to claim 1, wherein the filtering form of the average filtering method and the filtering form of the FIR filtering method in S100 are respectively expressed as:
wherein x (N) represents the current measurement value, x (N-1) represents the previous measurement value of 1 time, x (N-n+1) is the previous measurement value of N-1 time, and N represents the number of filtering operation points.
The unit impulse response h (mu) length of the FIR is M, and the system function and the difference equation of the FIR filtering method are expressed as follows:
the filtering form of the FIR filtering method is as follows:
where H (z) is the system function and y (μ0) is the differential equation.
3. The FIR low-pass digital filtering method for reducing resource consumption according to claim 2, wherein the required filtering condition when the two filtering effects are identical in S200 is expressed as:
4. the method for FIR low-pass digital filtering for reducing resource consumption according to claim 3, wherein the design parameter of the filtering effect in S300 is that the stop band peak reaches below-30 dB; the number of times of filtering was 2.
5. The method of claim 4, wherein the number of the 1 st filtering operations in S400 is P, the number of the second filtering operations is Q, and the ratio of the number of the filtering operations is P: q=2:3.
6. The method of FIR low-pass digital filtering for reducing resource consumption according to claim 5, wherein S500 includes:
setting a filtering operation point ratio of 2:3, and filtering the signal to be filtered twice continuously by using an average filtering method.
7. The FIR low-pass digital filtering method for reducing resource consumption according to claim 6, further comprising, after S500:
s610, setting a filtering operation point ratio of 2:3, and carrying out continuous twice filtering on the signal to be filtered by using an FIR filtering method;
s620, acquiring first computing resources required by the average filtering method when filtering the signal to be filtered and second computing resources required by the FIR filtering method when filtering the signal to be filtered;
s630, comparing the first computing resource with the second computing resource to obtain a resource consumption result.
8. The FIR low-pass digital filtering method for reducing resource consumption according to claim 7, wherein the first computing resources in S620 are N (p+q) additions and 2N multiplications; the second computing resources are N (P+Q) multiplications and N (P-1) +N (Q-1) additions.
CN202310529677.3A 2023-05-11 2023-05-11 FIR low-pass digital filtering method for reducing resource consumption Pending CN116707491A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310529677.3A CN116707491A (en) 2023-05-11 2023-05-11 FIR low-pass digital filtering method for reducing resource consumption

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310529677.3A CN116707491A (en) 2023-05-11 2023-05-11 FIR low-pass digital filtering method for reducing resource consumption

Publications (1)

Publication Number Publication Date
CN116707491A true CN116707491A (en) 2023-09-05

Family

ID=87840094

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310529677.3A Pending CN116707491A (en) 2023-05-11 2023-05-11 FIR low-pass digital filtering method for reducing resource consumption

Country Status (1)

Country Link
CN (1) CN116707491A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117102701A (en) * 2023-10-24 2023-11-24 上海方菱计算机软件有限公司 Compensation control method and device for groove cutting height, electronic equipment and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117102701A (en) * 2023-10-24 2023-11-24 上海方菱计算机软件有限公司 Compensation control method and device for groove cutting height, electronic equipment and storage medium
CN117102701B (en) * 2023-10-24 2024-03-26 上海方菱计算机软件有限公司 Compensation control method and device for groove cutting height, electronic equipment and storage medium

Similar Documents

Publication Publication Date Title
CN116707491A (en) FIR low-pass digital filtering method for reducing resource consumption
CN111985361A (en) Wavelet denoising and EMD-ARIMA power system load prediction method and system
CN116703183B (en) Novel power distribution network system power load assessment method
CN117786325B (en) Ambient temperature wisdom early warning system of heavy-calibre thing networking water gauge
CN117493921B (en) Artificial intelligence energy-saving management method and system based on big data
CN117727313B (en) Intelligent noise reduction method for wild bird sound data
CN117290679A (en) Running state detection method and device of current transformer and electronic equipment
CN110796303A (en) Short-term power load prediction method based on EWT and ODBSCAN
CN114755010A (en) Rotary machine vibration fault diagnosis method and system
CN114547782A (en) Method for calculating speed and road gradient of electric automobile
CN109995690B (en) Neural network self-optimization method for MFSK digital signal subclass modulation recognition
CN108805011B (en) Digital filtering method and system
CN110298767A (en) A kind of thermal power plant time series variable method for monitoring abnormality and system
CN115099291B (en) Building energy-saving monitoring method
CN109856964A (en) Moving target control method and system based on miss distance processing
CN116433085A (en) Performance evaluation method of rolling process control system
CN115184250A (en) Optical fiber aging state evaluation system and evaluation method thereof
CN109687924B (en) Short wave available frequency resource automatic detection method based on measured data
CN114386865A (en) Runoff influence factor determination method and system based on natural attributes of multi-element process
CN110061720B (en) Adaptive filtering system
CN113657659A (en) Parameter global optimization method of modular flood forecasting model
CN111525932A (en) Frequency identification method and filtering method of power frequency signal and microwave sensor
Kosanovich et al. Poisson wavelets applied to model identification
CN116067433B (en) Vibration wire data acquisition method and acquisition instrument thereof
CN117434906B (en) Automatic speed control adding method and system for filter aid powder

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination