Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is responsive to the applicant’s arguments filed on 12/23/2025.
Claims 1, 2, 4-6, 8-10, 12, 14, 16, and 18 are pending. Claims 1, 4, 5, 8, 9, 12, 14, 16, and 18 are amended.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/23/2025 has been entered.
Response to Arguments
Regarding claim objections:
The objection has been updated in view of the amendments.
Regarding rejections under 35 USC § 112:
The rejection has been withdrawn in view of the amendments.
Regarding rejections under 35 USC § 101:
Applicant's arguments filed on 12/23/2025 have been fully considered but they are not persuasive.
With respect to the remarks, page 13, regarding consideration as a whole, the Examiner respectfully disagrees.
To clarify, Examiner notes that the technical improvement must be provided by additional elements, not by the abstract ideas. It is important to note that the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See MPEP § 2106.05(a). Additionally, as discussed in MPEP 2106.05(a)(II), for improvements to technology or technical fields, “an improvement in the abstract idea itself ... is not an improvement in technology.” The improvement must be provided by additional elements.
In this case, as explained in the 101 rejection, the additional elements amount to data gathering activities; insignificant extra-solution activities; mere instructions to apply the judicial exception; and/or generally linking the use of a judicial exception to a particular technological environment or field of use that do not add meaningful limitation to the recited judicial exceptions. Therefore, even when considered as a whole, the additional elements do not integrate the judicial exception into a practical application or amount to significantly more than the judicial exceptions.
With respect to the remarks, page 13-14, regarding “training the neural network model” under Step 2A Prong 1, the Examiner respectfully disagrees.
To clarify, according to the description of specification para [0030] and [0044], the training is performed by using an error back propagation method. Such a method encompasses mathematical calculations, mathematical formulas or equations, or mathematical relationships. See July 2024 Subject Matter Eligibility Examples, Example 47 claim 2 step (c): the step of training an ANN using a selected algorithm was determined to amount to mathematical concepts because the training algorithm according to the specification was a backpropagation algorithm and a gradient descent algorithm, which involve a series of mathematical calculations (“Step (c) recites training an ANN using a selected algorithm. The training algorithm is a backpropagation algorithm and a gradient descent algorithm. When given their broadest reasonable interpretation in light of the background, the backpropagation algorithm and gradient descent algorithm are mathematical calculations. The plain meaning of these terms are optimization algorithms, which compute neural network parameters using a series of mathematical calculations.”). Even if the data used in the training step is “specific” as the remarks alleges, in the training step, these data are input into the functions or equations in the error back propagation method and mathematical calculations are performed. Therefore, the step of training the neural network model amounts to a mathematical concept.
With respect to the remarks, page 14, regarding “selecting” under Step 2A Prong 1, the Examiner respectfully disagrees.
To clarify, selecting a resonance frequency or a simulation result based on the simulation results, under broadest reasonable interpretation, amounts to a person looking at the simulation results, and making a judgment regarding which resonance frequency or simulation result to use as input to the neural network model. These processes involve mental observation and judgment. Therefore, these limitations amount to mental processes.
With respect to the remarks, page 15-16, regarding technical improvement, the Examiner respectfully disagrees.
To clarify, it is important to note that the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See MPEP § 2106.05(a). Additionally, as discussed in MPEP 2106.05(a)(II), for improvements to technology or technical fields, “an improvement in the abstract idea itself ... is not an improvement in technology.” The improvement must be provided by additional elements.
Therefore, as explained in the MPEP 2106.04(d) and also in Ex Parte Desjardins, if the specification sets forth an improvement apparent to one of ordinary skill in the art, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement, i.e., the claim includes the components or steps of the invention that provide the improvement described in the specification. In the discussion of technical improvement on pages 15-16, the remarks alleges that the alleged improvement is “evident through several key aspects of the claimed invention,” but does not explicitly identify additional elements that provides the alleged improvement. The remarks alleges that the improvement is provided by “by varying LCR element values that can impede accurate estimation in existing systems,” but it is not clear which limitation recited in claims it is referring to. The remarks on page 16 also mentions identification of "resonance frequency of the current" and "spatial distribution of the current at the resonance frequency" as distinct input channels, but Examiner notes that this limitation amounts to a mental process under broadest reasonable interpretation as explained previously for the “selecting” step.
Moreover, even if the steps that provide the alleged improvement are recited in the claims, the additional elements currently recited in the claims amount to data gathering activities; insignificant extra-solution activities; mere instructions to apply the judicial exception; and/or generally linking the use of a judicial exception to a particular technological environment or field of use that do not integrate the judicial exception into a practical application or amount to significantly more than the judicial exceptions.
With respect to the remarks, page 16, regarding “obtaining simulation results by using a circuit simulator”, the Examiner respectfully disagrees.
To clarify, the remarks alleges that this step is not passively collecting readily available information. However, data gathering includes pre-solution activities that are performed prior to primary process of the claim. This limitation is recited generically and recites generically using a circuit simulator to obtain the data required for the selecting and inputting steps. This amounts to a pre-solution activity that amounts to a data gathering activity. It also amounts to mere instruction to apply the judicial exception using a generic computer and generally linking the use of a judicial exception to a particular technological environment or field of use as explained in the 101 rejection below.
With respect to the remarks, page 17, regarding “inputting”, the Examiner respectfully disagrees.
To clarify, Examiner notes that this step amounts to inputting data, which amounts to an insignificant extra-solution activity; mere instructions to apply the judicial exception; and/or generally linking the use of a judicial exception to a particular technological environment or field of use, even if the data itself might be specific under consideration for 102/103. This step is merely performed after the generation/selection of such “specific” data as a step of using them, i.e., “inputting” them into a model. The step of generating/obtaining such data is a distinct step from the step of inputting or using them. It appears that the second input data is obtained from the step of obtaining simulation result and selecting data from the simulation results. These steps, as explained previously, amount to abstract ideas or additional elements that do not amount to significantly more than the judicial exception.
Claim Objections
Claims 4, 8, and 12 are objected to because of the following informalities: the limitation “the trained machine learning model” should read “the trained neural network model” for consistency. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 4-6, 8-10, 12, 14, 16, and 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more.
Step 1: Claims 1-2, 4, and 14 are directed to a non-transitory computer-readable recording medium, which is a manufacture, falling under a statutory category of invention. Claims 5-6, 8, and 16 are directed to a method, which is a process, falling under a statutory category of invention. Claim 9-10, 12, and 18 are directed to a device, which is a machine, falling under a statutory category of invention. Therefore, claims 1-2, 4-6, 8-10, 12, 14, 16, and 18 are directed to patent eligible categories of invention.
Regarding claim 1:
Step 2A Prong 1: The following limitations recite abstract ideas:
The limitation “training the neural network model, to generate a trained neural network model, using a training data set in which arrangements of circuit elements in respective electronic circuits differ from each other, the training data set being a set of training data each of which consists of a specific value of a resonance frequency for a specific electronic circuit as a first channel of first input data to the neural network model, information of a spatial distribution of a current that flows through the specific electronic circuit at the resonance frequency of the specific value as a second channel of the first input data, and an electromagnetic wave radiation situation of the specific electronic circuit as a label” under broadest reasonable interpretation covers mathematical concepts. According to the description of specification para [0030] and [0044], the training is performed by using an error back propagation method. Such a method encompasses mathematical calculations, mathematical formulas or equations, or mathematical relationships. See July 2024 Subject Matter Eligibility Examples, Example 47 claim 2 step (c): the step of training an ANN using a selected algorithm was determined to amount to mathematical concepts because the training algorithm according to the specification was a backpropagation algorithm and a gradient descent algorithm, which involve a series of mathematical calculations (“Step (c) recites training an ANN using a selected algorithm. The training algorithm is a backpropagation algorithm and a gradient descent algorithm. When given their broadest reasonable interpretation in light of the background, the backpropagation algorithm and gradient descent algorithm are mathematical calculations. The plain meaning of these terms are optimization algorithms, which compute neural network parameters using a series of mathematical calculations.”).
The limitation “selecting, based on a plurality of simulation results obtained by performing the obtaining of simulation result on the plurality of frequencies, a resonance frequency from among the plurality of frequencies” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. For example, this covers a person mentally observing the plurality of frequencies and making a mental judgment.
The limitation “selecting, from among the plurality of simulation results, the simulation result indicating the intensity of the current distribution corresponding to the selected resonance frequency” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. For example, this covers a person mentally observing the plurality of simulation results and making a mental judgment.
Step 2A Prong 2: The following limitations recite additional elements. However, these additional elements do not integrate the judicial exception into a practical application.
The additional element “A non-transitory computer-readable recording medium having stored therein a program of estimating an electromagnetic wave radiation situation of an electronic circuit using a neural network model, the program including instructions which, when executed by a computer, cause the computer to execute a process” does not integrate the judicial exception into a practical application because it amounts to no more than mere instructions to apply the judicial exception using a generic computer. See MPEP 2106.05(f).
The additional element “obtaining, for each frequency of a plurality of frequencies, a simulation result indicating an intensity of a current distribution that approximates a near field of the electromagnetic wave radiation in a target electronic circuit to be analyzed, by using a circuit simulator” does not integrate the judicial exception into a practical application because it amounts to data gathering. See MPEP 2106.05(g). This also amounts to mere instructions to apply the judicial exception using a generic computer. For example, the use of a circuit simulator is generically recited that it amounts to using a computer to run a simulator to obtain simulation results. This also amounts to generally linking the use of a judicial exception to a particular technological environment or field of use. The use of a circuit simulator is generically recited and therefore amounts to merely applying the circuit simulator to obtain simulation results. Such activities do not integrate the judicial exception into a practical application See MPEP 2106.05(f) and 2106.05(h).
The additional element “inputting, to the trained neural network model, second input data consisting of a frequency value of the selected resonance frequency as the first channel of the second input data and the selected simulation result indicating the intensity of the current distribution at the selected resonance frequency as the second channel of the second input data, to obtain, from the trained neural network model, an estimation result indicating the electromagnetic wave radiation situation of the target electronic circuit” does not integrate the judicial exception into a practical application because it amounts to an insignificant extra-solution activity of merely inputting data after training the neural network model and selecting desired input data. See MPEP 2106.05(g).
This amounts to mere instructions to apply the judicial exception and generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP 2106.05(f) and 2106.05(h). Specifically, this amounts to merely applying the simulation result and the result of selection to the trained neural network and generically using the trained neural network to produce an output. See July 2024 Subject Matter Eligibility Examples, Example 47 claim 2 on pages 8-9: “The limitations in (d) and (e) reciting “using the trained ANN” provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. The judicial exception of “detecting one or more anomalies in a data set using the trained ANN” and “analyzing the one or more detected anomalies using the trained ANN to generate anomaly data” is performed “using the trained ANN.” The trained ANN is used to generally apply the abstract idea without placing any limits on how the trained ANN functions. Rather, these limitations only recite the outcome of “detecting one or more anomalies” and “analyzing the one or more detected anomalies” and do not include any details about how the “detecting” and “analyzing” are accomplished. See MPEP 2106.05(f). The recitation of “using a trained ANN” in limitations (d) and (e) also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “using a trained ANN” limits the identified judicial exceptions “detecting one or more anomalies in a data set using the trained ANN” and “analyzing the one or more detected anomalies using the trained ANN to generate anomaly data,” this type of limitation merely confines the use of the abstract idea to a particular technological environment (neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).”
Therefore, even when viewed in combination, these additional elements do not integrate the judicial exception into a practical application.
Step 2B: Furthermore, the additional elements do not amount to significantly more than the judicial exception.
As previously discussed, the additional element “A non-transitory computer-readable recording medium having stored therein a program of estimating an electromagnetic wave radiation situation of an electronic circuit using a neural network model, the program including instructions which, when executed by a computer, cause the computer to execute a process” amounts to no more than mere instructions to apply the exception using a generic computer, which do not amount to significantly more than the judicial exception. See MPEP 2106.05(f).
As previously discussed, the additional element “obtaining, for each frequency of a plurality of frequencies, a simulation result indicating an intensity of a current distribution that approximates a near field of the electromagnetic wave radiation in a target electronic circuit to be analyzed, by using a circuit simulator” amounts to a mere instruction to apply the judicial exception using a generic computer and generally linking the use of a judicial exception to a particular technological environment or field of use, which do not amount to significantly more than the judicial exception. See MPEP 2106.05(f) and 2106.05(h). This also amounts to a data gathering activity that is akin to receiving or transmitting data over a network. Such activities do not amount to significantly more than the judicial exception. See MPEP 2106.05(d)(II): “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))”.
As previously discussed, the additional element “inputting, to the trained neural network model, second input data consisting of a frequency value of the selected resonance frequency as the first channel of the second input data and the selected simulation result indicating the intensity of the current distribution at the selected resonance frequency as the second channel of the second input data, to obtain, from the trained neural network model, an estimation result indicating the electromagnetic wave radiation situation of the target electronic circuit” amounts to a mere instruction to apply the judicial exception using a generic computer and generally linking the use of a judicial exception to a particular technological environment or field of use, which do not amount to significantly more than the judicial exception. See MPEP 2106.05(f) and 2106.05(h). This also amounts to an insignificant extra-solution activity that is akin to receiving or transmitting data over a network. Such activities do not amount to significantly more than the judicial exception. See MPEP 2106.05(d)(II): “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))”.
Accordingly, the claim does not recite any additional elements that amount to significantly more than the judicial exception.
Therefore, claim 1 is not eligible.
Regarding claim 2:
The limitation “the selecting of the resonance frequency includes selecting, as the resonance frequency, a frequency at which a maximum value of the current distribution is highest among the plurality of simulation results” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. For example, this amounts to a person mentally observing the frequencies and the values of the current distribution and making a mental judgment.
The claim does not recite any additional elements that would have provided practical application of or have added significantly more to the cited abstract idea.
Therefore, claim 2 is not eligible.
Regarding claim 4:
The limitation “the selecting of the simulation result includes dividing the current distribution indicated in the selected simulation result into several spatial distributions in accordance with configurations of respective circuit elements included in the target electronic circuit” under broadest reasonable interpretation covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. For example, this covers someone mentally observing the current distribution and dividing the circuit mentally or with a pen and paper.
The limitation “obtaining the estimation result indicating the electromagnetic wave radiation situation of the target electronic circuit by adding the plurality of outputs obtained from the trained neural network model” under broadest reasonable interpretation covers a mathematical concept and a mental process. According to specification para [0067], the output amounts to the EMI intensity value. Therefore, under broadest reasonable interpretation, adding the output amounts to mathematically adding a plurality of EMI intensity values. This amounts to a mathematical concept. This also amounts to a mental process because a person can perform such an addition mentally or with a pen and paper.
The limitation “obtaining a plurality of outputs from the trained neural network model using the several spatial distributions by inputting, for each spatial distribution of the several spatial distributions, to the trained neural network model, the frequency value of the selected resonance frequency as the first channel of the second input data, and the each spatial distribution as the second channel of the second input data” amounts to an addition element which does not integrate the judicial exception into a practical application because it amounts to an insignificant extra-solution activity of merely inputting data after training the neural network model and selecting desired input data. See MPEP 2106.05(g). This is akin to akin to receiving or transmitting data over a network, which do not amount to significantly more than the judicial exception. See MPEP 2106.05(d)(II): “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))”.
This amounts to mere instructions to apply the judicial exception and generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP 2106.05(f) and 2106.05(h). Specifically, this amounts to merely applying the simulation result and the result of selection to the trained neural network and generically using the trained neural network to produce an output. See July 2024 Subject Matter Eligibility Examples, Example 47 claim 2 on pages 8-9: “The limitations in (d) and (e) reciting “using the trained ANN” provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. The judicial exception of “detecting one or more anomalies in a data set using the trained ANN” and “analyzing the one or more detected anomalies using the trained ANN to generate anomaly data” is performed “using the trained ANN.” The trained ANN is used to generally apply the abstract idea without placing any limits on how the trained ANN functions. Rather, these limitations only recite the outcome of “detecting one or more anomalies” and “analyzing the one or more detected anomalies” and do not include any details about how the “detecting” and “analyzing” are accomplished. See MPEP 2106.05(f). The recitation of “using a trained ANN” in limitations (d) and (e) also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “using a trained ANN” limits the identified judicial exceptions “detecting one or more anomalies in a data set using the trained ANN” and “analyzing the one or more detected anomalies using the trained ANN to generate anomaly data,” this type of limitation merely confines the use of the abstract idea to a particular technological environment (neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).”
Therefore, claim 4 is not eligible.
Regarding claim 14:
The limitation “creating a first two-dimensional matrix indicating the selected resonance frequency” amounts to a mathematical concept and a mental process. Specification para [0055] discloses that the resonance frequency is a scalar value and is converted into a matrix. Converting a value into a matrix amounts to mathematical concepts involving mathematical calculations, equations, and/or relationships. This also amounts to a mental process because a person can perform these operations mentally or with a pen and paper.
The limitation “creating a second two-dimensional matrix in which a wiring pattern of the target electronic circuit is colored based on the intensity of the current distribution indicated in the selected simulation result in order to represent the electromagnetic wave radiation situation of the target electronic circuit” amounts to a mathematical concept and a mental process. For example, creating a matrix involves mathematical calculations, equations, and/or relationships. Furthermore, a person can observe the current distribution and color a matrix, which can be done mentally or with a pen and paper.
The limitation “wherein the inputting includes inputting, to the trained neural network model, the first two-dimensional matrix as the first channel of the input data and the second two-dimensional matrix as the second channel of the input data” further limits the inputting recited in claim 1. Therefore, this amounts to an insignificant extra-solution activity; a mere instruction to apply the judicial exception; and generally linking the use of a judicial exception to a particular technological environment or field of use, for the similar reason as the inputting recited in claim 1.
Therefore, claim 14 is not eligible.
Claim 9 is substantially similar to claim 1. Therefore, the similar analysis is applicable.
In addition, the limitations “a memory” and “a processor coupled to the memory and the processor configured to perform processing” are additional elements which amount to no more than mere instructions to apply the judicial exception using a generic computer. A memory and a processor are generic computer components. See MPEP 2106.05(f).
Therefore, claim 9 is not eligible.
Claims 5-8, 10-12, 16, and 18 are substantially similar to claims 1-4 and 14 and therefore rejected for the similar reasons.
Accordingly, claims 1-12, 14, 16, and 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without anything significantly more.
Allowable Subject Matter
The 103 rejection of claim(s) 1-2, 4-6, 8-10, 12, 14, 16, and 18 is withdrawn based on the amendments filed on 07/01/2025. The limitation(s) include “inputting, to the trained neural network model, the input data consisting of a frequency value of the selected resonance frequency as the first channel of the input data and the selected simulation result indicating the intensity of the current distribution at the selected resonance frequency as the second channel of the input data, to obtain, from the trained neural network model, an estimation result indicating the electromagnetic wave radiation situation of the target electronic circuit”, in combination with the all of the remaining limitations.
The closest prior art references of record are:
Ma et al. (“Deep Learning Method for Prediction of Planar Radiating Sources from Near-Field Intensity Data”)
Kayano et al. (“Electromagnetic Radiation Resulting from Strip Line Structure Driven by a Feed Cable”)
Li et al. (“Prediction of Electromagnetic Compatibility Problems Based on Artificial Neural Networks”).
These references alone or in combination do not disclose the limitations including “inputting, to the trained neural network model, the input data consisting of a frequency value of the selected resonance frequency as the first channel of the input data and the selected simulation result indicating the intensity of the current distribution at the selected resonance frequency as the second channel of the input data, to obtain, from the trained neural network model, an estimation result indicating the electromagnetic wave radiation situation of the target electronic circuit” in combination with the remaining limitations. Therefore, claim(s) 1-2, 4-6, 8-10, 12, 14, 16, and 18 as drafted, are rendered neither obvious nor anticipated by the prior art of the record and the available field of prior art. The claims would be allowable if rewritten to overcome the 101 rejection of the claims.
Conclusion
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/HEIN JEONG/Examiner, Art Unit 2188
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186