CN109301428A - A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment - Google Patents
A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment Download PDFInfo
- Publication number
- CN109301428A CN109301428A CN201811033547.6A CN201811033547A CN109301428A CN 109301428 A CN109301428 A CN 109301428A CN 201811033547 A CN201811033547 A CN 201811033547A CN 109301428 A CN109301428 A CN 109301428A
- Authority
- CN
- China
- Prior art keywords
- coupling matrix
- filter
- firefly
- coupling
- target
- 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
Links
Classifications
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01P—WAVEGUIDES; RESONATORS, LINES, OR OTHER DEVICES OF THE WAVEGUIDE TYPE
- H01P11/00—Apparatus or processes specially adapted for manufacturing waveguides or resonators, lines, or other devices of the waveguide type
- H01P11/007—Manufacturing frequency-selective devices
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Complex Calculations (AREA)
Abstract
The present invention provides a kind of optimization method of the coupling matrix element of filter, equipment and storage equipment, glowworm swarm algorithm is used in the present invention, it is handled by the data to coupling matrix M1, directly optimize the element of coupling matrix M1, when the minimum value of objective function, which meets, to impose a condition, complete the optimization of coupling matrix element, the setting condition are as follows: objective function minimum value is less than given threshold or reaches the maximum number of iterations of setting.A kind of the optimization equipment and storage equipment of the coupling matrix element of filter, for realizing a kind of optimization method of the coupling matrix element of microwave filter.The beneficial effects of the present invention are: optimizing to obtained coupling matrix element, optimal speed is fast, reduces error, accelerates the process to filter debugging, improves the debugging efficiency and adjustment accuracy of filter.
Description
Technical field
The present invention relates to the optimization method of wave filter technology field more particularly to a kind of coupling matrix element of filter,
Equipment and storage equipment.
Background technique
In order to accurately obtain the electrical characteristic of ideal microwave coupling resonant cavity filter, effective tuning is filter
Vital steps necessary in production process, filter tuner are the objects for obtaining the filter with acceptable frequency response
Manage the indispensable process realized.Conventional tune technology is mainly to rely on the tuning experience of many years, so tuning process becomes
It is extremely complex and expensive.Especially to multiple cross-linked higher order filters, more complicated fuzzy logic is needed.It calculates
Machine auxiliary tuning (CAT) technology can accelerate filter tuner process, greatly shorten the overall offering time.Committed step in CAT
It is to extract coupling matrix (CM), which corresponds to the filter freguency response from serious detuning state to good tuning state.
By comparing the difference between the CM and target CM of extraction, this will be helpful to filter designer and determines under each tuning state
Tune direction and physics regulated quantity.
Currently, at home and abroad the disclosed coupling matrix and the method for optimization of extracting mainly has: document
G.Macchiarellaand D.Traina,Aformulation ofthe Cauchy method suitable for the
synthesis oflossless circuit models ofmicrowave filters from lossy
Measurements, IEEE Microwave WirelessComponLett 16 (2006), 243-245.490-492. are proposed
A kind of analysis extracting method, this method being capable of the accurately CM of each resonator of extraction filter and non-homogeneous no-load Q.In text
In offering, the proper polynomial corresponding to Y parameter is fitted (VF) method by vector and solves.VF method needs an iterative process,
It depends on the initial pole of the auxiliary function of definition.In our pervious document H.Hu andK.L.Wu,
Ageneralizedcoupling matrix extraction technique for bandpass filters with
In uneven-Qs, IEEE Trans Microwave Theory Tech62 (2014), 244C251. in available method, Y ginseng
Number (for extracting CM) can be calculated by the proper polynomial corresponding to measured or simulation S.It is proposed at this
In method, the proper polynomial corresponding to Y parameter is solved in one step by Cauchy method.It was used before all
In the document of Cauchy method, such as R.J.Cameron, C.M.Kudsia, and R.R.Mansour, Microwave Filters
for Communication Systems.NewYork:Wiley；2007, ch.6C8, proper polynomial corresponds directly to S ginseng
Number.Therefore, the filter must be removed in advance using the lossy filter diagnosis of traditional Cauchy method (corresponding to S parameter)
Fissipation factor, and traditional Cauchy method can only handle the uniform no-load Q. of all resonators of filter
In the literature, various technologies are proposed and come extraction filter circuit model (also referred to as filter diagnosis), such as
G.MacchiarellaandD.Traina,Aformulation ofthe Cauchy method suitable for the
synthesis oflossless circuitmodels ofmicrowave filters from lossy
In measurements, IEEE Microwave Wireless Compon Lett 16 (2006), 243-245.490-492.
Cauchy method, M.Meng andK.L.Wu, An analytical approach to computeraided
diagnosis and tuning of lossy microwave coupled resonator filters,IEEE Trans
Analysis method and M.Kahrizi in Microwave Theory Tech 57 (2009), 3188C3195., Safavi-
Naeini,S.K.Chaudhuri,and R.Sabry,Computer diagnosis andtuning ofRF and
microwave filters usingmodel-basedparameterestimation,IEEETrans Circuit
Optimization method in SystI49 (2002), 1263C1270..Most of methods based on optimization, such as M.Kahrizi,
S.Safavi-Naeini,S.K.Chaudhuri,and R.Sabry,Computer diagnosis and tuning ofRF
and microwave filters using model-basedparameter estimation,IEEE Trans
Circuit SystI49 (2002), 1263C1270 generally depend on good initial CM value.Coupling in coupling matrix (CM)
Matrix coupling matrix (CM) coupling matrix (CM) is a basic ginseng when describing the relationship between physics realization and required relationship
It examines, because the CM of each coupling element is the element for being uniquely corresponding to physics tuning.All CAT skills including above-mentioned work
Art requires to carry out some filter diagnosis according to the filter response measured or coupling matrix extracts.In addition to directly in document
J.B.Ness,Aunifiedapproachtothe design,measurement,and tuning ofcoupled-
resonator filters,IEEE Trans:Microw:Theory Tech:；vol.46,no.4,pp.343C351,
Apr.1998. outside the method for using group delay information in, existing most parameters extractive technique is all based on nonlinear optimization.
Optimizer or time-consuming (being used for global optimization) or to initial value and variable number (for the local optimum based on gradient) very
Sensitivity, and be easy to jump to local optimum.
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of optimization methods of the coupling matrix element of filter, equipment
And storage equipment, a kind of optimization method of the coupling matrix element of filter mainly comprise the steps that
S101: the Dissipation Parameters of filter are obtained as sample data set；Sample data set includes under different spiro rod lengths
Dissipation Parameters corresponding to filter；
S102: each sample concentrated to sample data is handled, and converts Y parameter for Dissipation Parameters；
S103: according to Chebyshev's comprehensive designing method, transmission zero, return loss in conjunction with the filter are obtained
The target coupling matrix M of the filter；And S parameter is converted by target coupling matrix M: target S11 and target S21, target
S11 is reflective function, and target S21 is transfer function；
S104: the pole and residual of Y parameter are extracted using vector fitting method, according to the pole and residual, by opening up
Structural Transformation is flutterred, coupling matrix M1 is obtained；
S105: being handled using data of the glowworm swarm algorithm to coupling matrix M1, and by treated, coupling matrix M1 turns
Turn to S parameter: S111 and S121, S111 be reflective function, S121 be transfer function；
S106: according to target S11 and target S21, S111 and S121, obtain objective function: y=(| S11 |-| S111|)2+
(|S21|-|S121|)2；
S107: do you judge that the minimum value of objective function meets setting condition? if so, arriving step S109；If it is not, then arriving
Step S108；The setting condition are as follows: objective function minimum value is less than given threshold or reaches the maximum number of iterations of setting；
S108: all elements in coupling matrix M1 are reintegrated, and are formed a new coupling matrix, are returned to step
Rapid S105；
S109: the optimization of coupling matrix element is completed.
Further, in step s101, the screw rod of filter is comprising the screw rod with coupling bar and with resonant rod
Screw rod changes each spiro rod length using the method for uniform sampling sheet, obtains Dissipation Parameters.
Further, in step s 102, Y parameter is converted for Dissipation Parameters by following formula:
Wherein, S11And S22For reflection parameters, S12And S21For configured transmission, S11、S22、S12And S21It is Dissipation Parameters.
Further, in step s105, the process handled using data of the glowworm swarm algorithm to coupling matrix M1
Include:
(1) initialize the parameter in glowworm swarm algorithm, parameter includes maximum number of iterations and firefly quantity n, n be greater than
Integer equal to 1；
(2) position of each firefly i.e. each element of coupling matrix is searched for respectively；Each firefly is calculated in t moment
Fluorescein value li(t), li(t) indicate i-th firefly in the fluorescein value of t moment；In t moment, every firefly is in its dynamic
Decision domain radius ri dInterior, the individual for selecting fluorescein value higher than its forms the domain set N of the fireflyi(t), wherein 0 < ri d≤
rs, rsFor the perception radius of firefly individual；T > 0, i=1,2 ..., n；
(3) Probability p that each firefly shifts to individual j in neighborhood collection is calculatedij(t)；Firefly i shifts to Probability pij(t) greatly
Individual updates the position of firefly i and the radius of dynamic decision domain of firefly i；J=1,2 ..., n；
(4) judge whether firefly reaches maximum number of iterations or precision prescribed, if so, terminate glowworm swarm algorithm,
If it is not, then returning to step (2) continues iteration；
(5) final output current iteration optimal value, obtained optimal value are exactly the setting range of each element of coupling matrix
These element values are put into coupling matrix, the coupling matrix after being optimized by interior optimal value according to specified sorting position,
The matrix is exactly that treated coupling matrix M1.
Further, in step S108, method that all elements in coupling matrix are reintegrated are as follows: with first
Element after secondary iteration updates the element of the initial coupling matrix of opposite position, with the member of the coupling matrix after the m times iteration
Element updates the element of the coupling matrix after the m-1 times iteration of opposite position, and m is the integer more than or equal to 2, first time iteration
Element afterwards refers to handled for the first time using data of the glowworm swarm algorithm to coupling matrix M1 after obtained result.
A kind of storage equipment, equipment store instruction and the data of storing are for realizing a kind of Coupling matrix element of filter
The optimization method of element.
A kind of optimization equipment of the coupling matrix element of filter, comprising: processor and storage equipment；The processor adds
Carry and execute a kind of optimization method of the coupling matrix element of instruction and data for realizing filter in the storage equipment.
Technical solution provided by the invention, which has the benefit that, optimizes obtained coupling matrix element,
Optimal speed is fast, reduces error, accelerates the process to filter debugging, improves the debugging efficiency and debugging essence of filter
Degree.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is a kind of flow chart of the optimization method of the coupling matrix element of filter in the embodiment of the present invention；
Fig. 2 is the schematic diagram that hardware device works in the embodiment of the present invention.
Specific embodiment
For a clearer understanding of the technical characteristics, objects and effects of the present invention, now control attached drawing is described in detail
A specific embodiment of the invention.
The embodiment provides a kind of optimization method of the coupling matrix element of filter, equipment and storages to set
It is standby.
Referring to FIG. 1, Fig. 1 is a kind of process of the optimization method of the coupling matrix element of filter in the embodiment of the present invention
Figure, specifically comprises the following steps:
S101: the Dissipation Parameters of filter are obtained as sample data set；Sample data set includes under different spiro rod lengths
Dissipation Parameters corresponding to filter；The screw rod of filter includes the screw rod with coupling bar and the screw rod with resonant rod, is adopted
Change each spiro rod length with the method for uniform sampling sheet, obtains Dissipation Parameters；By taking microwave filter as an example；Dissipation Parameters include
S11、S22、S12And S21, wherein S11And S22For reflection parameters, S12And S21For configured transmission；
S102: each sample concentrated to sample data is handled, and converts Y parameter for Dissipation Parameters；By with
Dissipation Parameters are converted Y parameter by lower formula:
Wherein, S11And S22For reflection parameters, S12And S21For configured transmission, S11、S22、S12And S21It is Dissipation Parameters；
S103: according to Chebyshev's comprehensive designing method, transmission zero, return loss in conjunction with the filter are obtained
The target coupling matrix M of the filter；And S parameter is converted by target coupling matrix M: target S11 and target S21, target
S11 is the reflective function that is converted in target coupling matrix, be by the cycling of elements in target coupling matrix at S parameter, mesh
Mark S21 is the transfer function that is converted to of target coupling matrix, be by the cycling of elements in target coupling matrix at S parameter；
S104: the pole and residual of Y parameter are extracted using vector fitting method, according to the pole and residual, by opening up
Structural Transformation is flutterred, coupling matrix M1 is obtained；
S105: being handled using data of the glowworm swarm algorithm to coupling matrix M1, and by treated, coupling matrix M1 turns
It is melted into S parameter: S111 and S121, S111 reflective function to be converted in coupling matrix is by the cycling of elements in coupling matrix
At S parameter, S121 transfer function to be converted in coupling matrix, be by the cycling of elements in coupling matrix at S parameter；
Include: using the process that data of the glowworm swarm algorithm to coupling matrix M1 are handled
(1) initialize the parameter in glowworm swarm algorithm, parameter includes maximum number of iterations and firefly quantity n, n be greater than
Integer equal to 1；
(2) position of each firefly i.e. each element of coupling matrix is searched for respectively；Each firefly is calculated in t moment
Fluorescein value li(t), li(t) indicate i-th firefly in the fluorescein value of t moment；In t moment, every firefly is in its dynamic
Decision domain radius ri dInterior, the individual for selecting fluorescein value higher than its forms the domain set N of the fireflyi(t), wherein 0 < ri d≤
rs, rsFor the perception radius of firefly individual；T > 0, i=1,2 ..., n；
(3) Probability p that each firefly shifts to individual j in neighborhood collection is calculatedij(t)；Firefly i shifts to Probability pij(t) greatly
Individual updates the position of firefly i and the radius of dynamic decision domain of firefly i；J=1,2 ..., n；
(4) judge whether firefly reaches maximum number of iterations or precision prescribed, if so, terminate glowworm swarm algorithm,
If it is not, then returning to step (2) continues iteration；
(5) final output current iteration optimal value, obtained optimal value are exactly the setting range of each element of coupling matrix
These element values are put into coupling matrix, the coupling matrix after being optimized by interior optimal value according to specified sorting position,
The matrix is exactly that treated coupling matrix M1；
S106: according to target S11 and target S21, S111 and S121, obtain objective function: y=(| S11 |-| S111|)2+
(|S21|-|S121|)2；
S107: do you judge that the minimum value of objective function meets setting condition? if so, arriving step S109；If it is not, then arriving
Step S108；The setting condition are as follows: objective function minimum value is less than given threshold or reaches the maximum number of iterations of setting；
S108: all elements in coupling matrix are reintegrated, and are formed a new coupling matrix, are returned to step
S105；The method that all elements in coupling matrix are reintegrated are as follows: updated with the element after first time iteration corresponding
The element of the initial coupling matrix of position, the m-1 times that opposite position is updated with the element of the coupling matrix after the m times iteration
The element of coupling matrix after iteration, m are the integer more than or equal to 2, and the element after first time iteration refers to utilizes firefly for the first time
The result that fireworm algorithm obtains after handling the data of coupling matrix M1；
S109: the optimization of coupling matrix element is completed.
Fig. 2 is referred to, Fig. 2 is the hardware device operation schematic diagram of the embodiment of the present invention, and the hardware device specifically includes:
A kind of optimization equipment 401 of the coupling matrix element of filter, processor 402 and storage equipment 403.
A kind of optimization equipment 401 of the coupling matrix element of filter: a kind of coupling matrix element of filter
Optimization equipment 401 realizes a kind of optimization method of the coupling matrix element of filter.
Processor 402: the processor 402 loads and executes the instruction in the storage equipment 403 and data for real
A kind of existing optimization method of the coupling matrix element of filter.
Store equipment 403: 403 store instruction of storage equipment and data；The storage equipment 403 is for realizing described
A kind of optimization method of the coupling matrix element of filter.
The beneficial effects of the present invention are: optimizing to obtained coupling matrix element, optimal speed is fast, reduces mistake
Difference accelerates the process to filter debugging, improves the debugging efficiency and adjustment accuracy of filter.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (7)
1. a kind of optimization method of the coupling matrix element of filter, it is characterised in that: the following steps are included:
S101: the Dissipation Parameters of filter are obtained as sample data set；Sample data set includes to filter under different spiro rod lengths
Dissipation Parameters corresponding to device；
S102: each sample concentrated to sample data is handled, and converts Y parameter for Dissipation Parameters；
S103: according to Chebyshev's comprehensive designing method, transmission zero, return loss in conjunction with the filter are obtained described
The target coupling matrix M of filter；And convert S parameter for target coupling matrix M: target S11 and target S21, target S11 are
Reflective function, target S21 are transfer function；
S104: extracting the pole and residual of Y parameter using vector fitting method, according to the pole and residual, is tied by topology
Structure transformation, obtains coupling matrix M1；
S105: being handled using data of the glowworm swarm algorithm to coupling matrix M1, and by treated, coupling matrix M1 is converted into S
Parameter: S111 and S121, S111 be reflective function, S121 be transfer function；
S106: according to target S11 and target S21, S111 and S121, obtain objective function: y=(| S11 |-| S111|)2+(|S21
|-|S121|)2；
S107: do you judge that the minimum value of objective function meets setting condition? if so, arriving step S109；If it is not, then arriving step
S108；The setting condition are as follows: objective function minimum value is less than given threshold or reaches the maximum number of iterations of setting；
S108: all elements in coupling matrix M1 are reintegrated, and are formed a new coupling matrix, are returned to step
S105；
S109: the optimization of coupling matrix element is completed.
2. a kind of optimization method of the coupling matrix element of filter as described in claim 1, it is characterised in that: in step
In S101, the screw rod of filter includes the screw rod with coupling bar and the screw rod with resonant rod, using the side of uniform sampling sheet
Method changes each spiro rod length, obtains Dissipation Parameters.
3. a kind of optimization method of the coupling matrix element of filter as described in claim 1, it is characterised in that: in step
In S102, Y parameter is converted for Dissipation Parameters by following formula:
Wherein, S11And S22For reflection parameters, S12And S21For configured transmission, S11、S22、S12And S21It is Dissipation Parameters.
4. a kind of optimization method of the coupling matrix element of filter as described in claim 1, it is characterised in that: in step
In S105, include: using the process that data of the glowworm swarm algorithm to coupling matrix M1 are handled
(1) initialize the parameter in glowworm swarm algorithm, parameter includes maximum number of iterations and firefly quantity n, n be more than or equal to
1 integer；
(2) position of each firefly i.e. each element of coupling matrix is searched for respectively；Each firefly is calculated in the fluorescence of t moment
Plain value li(t), li(t) indicate i-th firefly in the fluorescein value of t moment；In t moment, every firefly is in its dynamic decision
Domain radius ri dInterior, the individual for selecting fluorescein value higher than its forms the domain set N of the fireflyi(t), wherein 0 < ri d≤rs,
rsFor the perception radius of firefly individual；T > 0, i=1,2 ..., n；
(3) Probability p that each firefly shifts to individual j in neighborhood collection is calculatedij(t)；Firefly i shifts to Probability pij(t) big individual,
Update the position of firefly i and the radius of dynamic decision domain of firefly i；J=1,2 ..., n；
(4) judge whether firefly reaches maximum number of iterations or precision prescribed, if so, terminate glowworm swarm algorithm, if it is not,
It then returns to step (2) and continues iteration；
(5) final output current iteration optimal value, obtained optimal value are exactly in the setting range of each element of coupling matrix
These element values are put into coupling matrix, the coupling matrix after being optimized, the square by optimal value according to specified sorting position
Battle array is exactly that treated coupling matrix M1.
5. a kind of optimization method of the coupling matrix element of filter as claimed in claim 4, it is characterised in that: in step
In S108, method that all elements in coupling matrix are reintegrated are as follows: updated with the element after first time iteration opposite
The element of the initial coupling matrix of position is answered, the m-1 of opposite position is updated with the element of the coupling matrix after the m times iteration
The element of coupling matrix after secondary iteration, m are the integer more than or equal to 2, and the element after first time iteration refers to be utilized for the first time
The result that glowworm swarm algorithm obtains after handling the data of coupling matrix M1.
6. a kind of storage equipment, it is characterised in that: the storage equipment store instruction and data are for realizing Claims 1 to 5
The optimization method of the coupling matrix element of any one filter.
7. a kind of optimization equipment of the coupling matrix element of filter, it is characterised in that: include: processor and storage equipment；Institute
Processor is stated to load and execute the instruction in the storage equipment and data for realizing any one described in Claims 1 to 5
The optimization method of the coupling matrix element of kind filter.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811033547.6A CN109301428A (en) | 2018-09-05 | 2018-09-05 | A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811033547.6A CN109301428A (en) | 2018-09-05 | 2018-09-05 | A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109301428A true CN109301428A (en) | 2019-02-01 |
Family
ID=65166134
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811033547.6A Pending CN109301428A (en) | 2018-09-05 | 2018-09-05 | A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109301428A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852009A (en) * | 2019-11-06 | 2020-02-28 | 中国电子科技集团公司第二十九研究所 | Filter coupling matrix decoupling transformation method based on genetic algorithm |
| CN111832213A (en) * | 2019-11-12 | 2020-10-27 | 中国电子科技集团公司第二十九研究所 | Filter coupling matrix decoupling transformation method based on hybrid optimization algorithm |
| CN111832195A (en) * | 2019-11-12 | 2020-10-27 | 中国电子科技集团公司第二十九研究所 | Modeling and intelligent design method of microstrip direct coupling filter |
| WO2021077291A1 (en) * | 2019-10-22 | 2021-04-29 | 华为技术有限公司 | Dielectric filter debugging method and device |
| CN112952315A (en) * | 2021-01-29 | 2021-06-11 | 中国地质大学（武汉） | Medium filter migration modeling debugging method based on mechanism guidance data acquisition |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108170922A (en) * | 2017-12-21 | 2018-06-15 | 中国地质大学（武汉） | A kind of aided debugging method of microwave filter, equipment and storage device |
-
2018
- 2018-09-05 CN CN201811033547.6A patent/CN109301428A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108170922A (en) * | 2017-12-21 | 2018-06-15 | 中国地质大学（武汉） | A kind of aided debugging method of microwave filter, equipment and storage device |
Non-Patent Citations (1)
| Title |
|---|
| XIAO-LONG ZHUANG等: ""An optimization method for coupling matrix elements of microwave filter"", 《PROCEEDINGS OF THE 37TH CHINESE CONTROL CONFERENCE》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021077291A1 (en) * | 2019-10-22 | 2021-04-29 | 华为技术有限公司 | Dielectric filter debugging method and device |
| CN110852009A (en) * | 2019-11-06 | 2020-02-28 | 中国电子科技集团公司第二十九研究所 | Filter coupling matrix decoupling transformation method based on genetic algorithm |
| CN111832213A (en) * | 2019-11-12 | 2020-10-27 | 中国电子科技集团公司第二十九研究所 | Filter coupling matrix decoupling transformation method based on hybrid optimization algorithm |
| CN111832195A (en) * | 2019-11-12 | 2020-10-27 | 中国电子科技集团公司第二十九研究所 | Modeling and intelligent design method of microstrip direct coupling filter |
| CN111832195B (en) * | 2019-11-12 | 2022-08-02 | 中国电子科技集团公司第二十九研究所 | Modeling and intelligent design method of microstrip direct coupling filter |
| CN112952315A (en) * | 2021-01-29 | 2021-06-11 | 中国地质大学（武汉） | Medium filter migration modeling debugging method based on mechanism guidance data acquisition |
| CN112952315B (en) * | 2021-01-29 | 2022-03-11 | 中国地质大学（武汉） | Medium filter migration modeling debugging method based on mechanism guidance data acquisition |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109301428A (en) | A kind of optimization method of the coupling matrix element of filter, equipment and storage equipment | |
| CN108170922B (en) | Auxiliary debugging method and device for microwave filter and storage device | |
| Amari et al. | Space-mapping optimization of planar coupled-resonator microwave filters | |
| Song et al. | Contracting exceptional divisors by the Kähler–Ricci flow | |
| Zhang et al. | Parallel computational approach to gradient based EM optimization of passive microwave circuits | |
| US9665572B2 (en) | Optimal data representation and auxiliary structures for in-memory database query processing | |
| CN110765651A (en) | Modeling and intelligent design method of microstrip direct coupling filter | |
| Zhang et al. | Application of the AWE method with the 3-D TVFEM to model spectral responses of passive microwave components | |
| CN110598170A (en) | Data prediction method based on FEEMD decomposition time sequence | |
| CN109063374A (en) | A kind of coupling matrix extracting method based on parameter optimization, equipment and storage equipment | |
| Cheng et al. | The state of the art of microwave CAD: EM‐based optimization and modeling | |
| Zhou et al. | Intelligent tuning for microwave filters based on multi-kernel machine learning model | |
| CN106602202A (en) | Debugging method for radio frequency device | |
| CN105551919A (en) | Method for determining characteristic parameters of resonant cavity of klystron | |
| Harscher et al. | EM-simulator based parameter extraction and optimization technique for microwave and millimeter wave filters | |
| Bila et al. | Finite-element modeling for the design optimization of microwave filters | |
| Sarmah et al. | Surrogate Model Assisted Design of CSRR Structure using Genetic Algorithm for Microstrip Antenna Application. | |
| Cheng et al. | Tuning space mapping optimization exploiting embedded surrogate elements | |
| CN114079131B (en) | Cavity filter debugging method | |
| An et al. | A Kriging surrogate model assisted Tabu search method for electromagnetic inverse problems | |
| CN116542135A (en) | Microwave filter shape coupling relation hybrid modeling method, device and storage device | |
| De La Rubia | Advanced CEM codes for microwave synthesis: Full-wave coupling matrix in electromagnetics | |
| CN118072887A (en) | Feature auxiliary optimization method for rapid design of wave-absorbing metamaterial | |
| Liao et al. | Reinforcement Learning for Microwave Windows Tuning | |
| Guo et al. | Recent Advances in Gradient-based EM Optimization using Neuro-TF Surrogate |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190201 |