DETAILED ACTION
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 action is responsive to communication filed on 12/11/2025.
Claims 1-2, 4, 6-12, and 15-20 are pending. Claims 3, 5 and 13-14 have been cancelled. Claims 1, 2, 8, 11, 12, 17, and 18 have been amended. Entry of this amendment is accepted and made of record.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/11/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 4, 6-12, 15-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Support for the newly added limitations of “using the short pattern waveforms as inputs to a trained neural network as part of a machine learning system, the trained neural network having access to one or more short pattern databases to obtain a value for the one or more measurements without having to perform tests on the waveform to obtain the one or more measurements of the waveform” recited by independent claims 1 and 11 cannot be found in the original disclosure of the invention nor in the portions of the original disclosure of the invention cited by the applicant. From paragraphs 0028, 0033, 0037, and 0039 it is evident that signal measurements are being performed with a machine learning module and that the tests are being performed to obtain the one or more measurements. Clarification and correction is required.
Dependent claims 2, 4, 6-10, 12 and 15-20, are rejected under 35 USC 112(a) for the reasons discussed above with respect to their respective independent claims 1 and 11 from which they depend.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-2, 4, 6-12, 15-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding independent claims 1 and 11, the recitation “using the short pattern waveforms as inputs to a trained neural network as part of a machine learning system, the trained neural network having access to one or more short pattern databases to obtain a value for the one or more measurements without having to perform tests on the waveform to obtain the one or more measurements of the waveform” renders the claim indefinite. It is unclear from the claimed limitation how the values is being obtained from the one or more measurements without having to perform tests on the waveform to obtain the one or more measurements of the waveform” since the claim recites that the signal is a signal from a device under test and therefore it is clear that a test is being performed. Furthermore as discussed above with respect to rejections made to the claims under 35 USC 112(a), it is evident from the original disclosure of the invention that signal measurements are being performed with a machine learning module and that the tests are being performed to obtain the one or more measurements (see para. 0028, 0033, 0037, and 0039) and that tests are being performed on the waveform. Clarification and correction is required
Dependent claims 2, 4, 6-10, 12 and 15-20, are rejected under 35 USC 112(b) for the reasons discussed above with respect to their respective independent claims 1 and 11 from which they depend.
For examination on the merits the claims will be interpreted as best understood in light of the 35 USC 112(b) rejections above.
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, 6-7, 9-12, 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. A subject matter eligibility analysis is set forth below. See MPEP 2106.
Under Step 1 of the analysis, claim 1 belongs to a statutory category, namely it is a “method” claim. Likewise, claim 11, namely is “system” claim.
Under Step 2A, prong 1: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
The claim(s) 1 and 11 recite(s) concepts related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion for “applying an equalizer to the waveform…”; identifying one or more measurements to be made on the waveform; selecting a number of unit intervals (UIs); scanning the equalized waveform to identify short pattern waveforms having a length equal to the number of UIs; using the short pattern waveforms as inputs to a trained neural network… to obtain a value for the one or more measurements, without having to perform tests on the waveform to obtain the one or more measurements on the waveform; removing short pattern databases from the machine learning system that have coefficient values below a threshold to reduce input data size”.
The concepts discussed above can be considered to describe mental processes, namely concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. Although, the claim does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
Claim 11 is a test and measurement system, with substantially similar claim language as the method of claim 1.
Step 2A, prong 2 of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
This judicial exception is not integrated into a practical application because the abstract idea is not performed by using any particular device and because the “processor”, “machine learning system”, “test measurement device”, “one or more processors” and “trained neural network” (claims 1 and 11) amounts to the recitation of a general purpose computer used to apply the abstract idea; and because “receiving a signal from a device under test”, “using an analog-to-digital converter (ADC) to sample the signal from the device under test to generate a waveform from the signal” and “receiving an input” (claims 1 and 11), is mere data gathering recited at high level of generality and the results of the algorithm are merely output as part of insignificant post-solution activity (i.e. providing the values of the one or more measurements …) and are not used in any particular matter as to integrate the abstract idea in a practical application.
Claim 1 recites the additional element(s) of using generic AI/ML technology, i.e. “using the short pattern waveforms as inputs to a trained neural network as part of a machine learning system, the trained neural network having access to one or more short pattern databases to the short pattern waveforms …”, to perform data evaluations or calculations (i.e. obtain a value for the one or more measurements), as identified under Prong 1 above. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the use of the “trained neural network” merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h). Therefore, the use of “trained neural network” to perform steps that are otherwise abstract does not integrate the abstract idea into a practical application. See the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence; and Example 47, ineligible claim 2.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are general purpose computer “processor” and “machine learning system” used to apply the abstract idea and mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 1, and 11 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Under Step 2A, prong 1:
Dependent claims 2, 4 and 6-7 and 9-10 merely expand on the abstract idea by appending additional steps to the mathematical algorithm on their respective independent claim 1.
Dependent claims 2, 4, and 6-7, and 9-10 merely expands on the abstract idea by reciting additional steps related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion to “converting the short pattern waveforms to tensors and wherein using the short pattern waveform as input to the trained neural network comprises using the tensors as inputs ” (claim 2), “selecting the number of UIs based upon a number of taps of the equalizer” (claim 6), “selecting the number of UIs based on the one or more measurements to be made on the waveform” (claim 7), “selecting the different set of the short training patterns comprises selecting a different set of short training patterns of a same length, or selecting a different set of short training patterns having a longer length” (claim 9); and “using only a subset of the one or more short pattern databases” (claim 4), and “wherein the number, L, of short pattern sequence databases depends upon a number of signal levels, S, used in a type of signaling, and a pattern length, N, according to the relationship L S “ (claim 10) which is mere data characterization and part of the abstract idea.
Under Step 2A, prong 2:
This judicial exception is not integrated into a practical application in claims 2, 4, 6-7, 9-10 because the abstract idea is not performed by using any particular device and because the “machine learning system” recited in claims 2 amounts to the recitation of a general purpose computer used to apply the abstract idea; and because the recitation of “short pattern databases” storing short patterns amounts to mere data gathering recited at a high level of generality and insignificant extrasolution activities that are well understood routine and conventional, and because the limitations merely add further details as to the type of data, the means of collecting data being received/input (i.e. pattern length, N, according to the relationship LS in claim 9) and used with the mental process and/or math steps recited in the independent claims, also further calculations and math, so they are properly viewed as part of the recited abstract idea; and the results are not used in any particular matter as to integrate the abstract idea in a practical application.
Under Step 2B:
The claim(s) 2, 4, 6-7 and 9-10 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are general purpose computer “processor” and “machine learning system” used to apply the abstract idea and mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities (i.e. providing the values of the one or more measurements…) as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Under Step 2A, prong 1:
Dependent claims 12, 15-20 merely expand on the abstract idea by appending additional steps to the mathematical algorithm on their respective independent claim 11.
Dependent claims 12, 15-20 merely expands on the abstract idea by reciting additional steps related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion to “convert the short pattern waveforms to tensors…” (claim 12); “identify the known data patterns as short pattern waveforms comprises code to select short pattern waveforms and include time sequence information” (claim 17), “set a length of a short training pattern to be used and a subset of the short training patterns with the set short pattern length; select a subset of available short training patterns from a waveform and associated measurements for the short training patterns to be provided a machine learning system as datasets; test the machine learning system to determine if results produced by the machine learning system meet a desired result; and select a different subset of the short training patterns, and repeat the testing when the results do not meet a desired result” (claim 18); and “use the short pattern waveforms as inputs to the trained neural network…use tensors as the inputs” (claim 12), “use only a subset of the one or more short pattern waveform databases” (claim 15) “select a number of UIs based upon a number of taps of the equalizer to be applied to the waveform” (claim 16), “select a different subset of the short training patterns comprises code that causes the one or more processors to select a different subset of the short training patterns with a same length, or to select a different subset of the short training patterns of a longer length” (clam 19) and “wherein the number, L, of short pattern sequence databases depends upon a number of signal levels, S, used in a type of signaling, and a pattern length, N, according to the relationship L SN” (claim 20) which is mere data characterization and part of the abstract idea.
Under Step 2A, prong 2:
This judicial exception is not integrated into a practical application in claims 12, 15-20 because the abstract idea is not performed by using any particular device and because the “test and measurement system” (claims 12, 15-20), and “one or more processors” (claim 12, 15-19) amounts to the recitation of a general purpose computer used to apply the abstract idea; and because the recitation of “short pattern databases” storing short patterns recited in claim 20, amounts to mere data gathering recited at a high level of generality and insignificant extrasolution activities well understood routine and conventional, and because the limitations merely add further details as to the type of data, the means of collecting data being received/input (i.e. short pattern length, patterns of same length or longer length in claim 18; pattern length, N, according to the relationship LS in claim 19) and used with the mental process and/or math steps recited in the independent claims, also further calculations and math, so they are properly viewed as part of the recited abstract idea; and the results are not used in any particular matter as to integrate the abstract idea in a practical application.
Under Step 2B:
The claim(s) 12, 15-20 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are general purpose computer “one or more processors” and “machine learning system” used to apply the abstract idea and mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities (i.e. provide the values of the one or more measurements…) as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore claims 1-2, 4, 6-7, 9-12, and 15-20 are rejected under 35 USC 101 as directed to an abstract idea without significantly more.
Reasons to overcome 35 USC 101 Rejection
Claim 8 recites the additional element(s) of “training the neural network, the training comprising: setting a selecting a set of short training patterns from a waveform and associated measurements for the set of short training patterns for use by the machine learning system as training datasets; testing the neural network to determine if results produced by the neural network meet a desired result; and selecting a different set of the short training patterns and repeating the testing using the different set of short training patterns when the results do not meet the desired result”. The claims positively recite additional details regarding how the AI/ML algorithm or model functions or is trained.
Therefore, the recitation of “training the neural network, the training comprising: setting a selecting a set of short training patterns from a waveform and associated measurements for the set of short training patterns for use by the machine learning system as training datasets; testing the neural network to determine if results produced by the neural network meet a desired result; and selecting a different set of the short training patterns and repeating the testing using the different set of short training patterns when the results do not meet the desired result” integrate the abstract idea into a practical application and is patent eligible.
Response to Arguments
Applicant's arguments filed 12/11/2025 have been fully considered but they are not persuasive.
With respect to claim 1, applicant argues that the claimed steps cannot be accomplished by the human mind (see last paragraph of page 7 of the remarks). Applicant further submits that as amended claim 1 recites using the short pattern waveforms as inputs to a trained neural network extracted from the waveform of the signal and submits that using neural network cannot be performed by the human mind and that at the first prong of step 2A of the MPEP eligibility analysis claim 1 is not directed to a mental process.
In response the examiner disagrees and submits that as discussed above under first prong of step 2A of the MPEP eligibility analysis, claim 1 recite(s) concepts related to mathematical algorithms/concepts, (i.e. “applying an equalizer to the waveform…”; using the short pattern waveforms as inputs to … to obtain a value for the one or more measurements, without having to perform tests on the waveform to obtain the one or more measurements on the waveform”) and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion (i.e. scanning the equalized waveform to identify short pattern waveforms having a length equal to the number of UIs; identifying one or more measurements to be made on the waveform; selecting a number of unit intervals (UIs);removing short pattern databases from the machine learning systems that have coefficient values below a threshold to reduce input data size).
The concepts discussed above can be considered to describe mental processes, namely concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. Although, the claim does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
Therefore, claims 1 and 11 stand rejected as not being patent eligible since the claims are directed to an abstract idea without significantly more.
Applicant argues that claim 1 is patent eligible because it integrates any alleged abstract idea into a practical application. Applicant submits that as amended claim 1 recites using one or more short pattern waveform databases to determine the measurement values needed without having to perform the measurement and that in addition, as the short pattern waveform databases are employed those short pattern waveform databases that have been coefficient values below a threshold, reducing the input data size. Applicant states that Reducing the input data size makes the machine learning more efficient and therefore constitutes and improvement to test and measurement technology (see in second and third paragraphs of page 8 of the remarks). Applicant further argues similarly to Enfish LLC v. Microsoft Corp 822 F.3d 1327, 1335-38, 118 USPQ2d 1684, 1689 (Fed. Circ. 2018) that claims are eligible because they improve upon conventional functioning of a computer, or upon conventional technology, or conventional processes. Applicant submits that Machine learning is not a conventional process, removing databases to be examined by machine learning is not conventional and submits that removal of databases to be considered by machine learning based upon their coefficients used to be below a threshold reduces the data input size, which in turn will make the machine learning function more efficiently and accurately and that it is an improvement to the technology (see last paragraph of page 8 through third paragraph of page 9 of the remarks).
In response, the examiner disagrees and submits that the claimed language do not reflect the alleged improvement to the operation of a computer and that the alleged improvements mentioned is generally linking the use of the judicial exception to a particular technological environment or field of use (i.e. machine learning) – see MPEP 2106.05(h) and as such is not indicative of a practical application of abstract idea.
As such the reduction on input size by the removal of databases is well-understood routine an conventional activity in the field. Deciding the amount of data used in a mathematical process depending on the desired sensitivity (i.e. removing short pattern databases…to reduce input data size) is matter of design choice and a well understood routine and conventional activity in the field and as such do not integrate the abstract idea into a practical application.
Furthermore, the additional claim limitations recited by the instant application claims do not reflect an improvement to the functioning of the computer, improvement to any other technology or technical field, applying the judicial exception with or by use of a particular machine or adding a specific limitation other than what is well-understood, routine and conventional activity in the field, or adding unconventional steps that confine the claim to a particular useful application as discussed above.
In response, to applicant arguments regarding claims of instant application being similar to those in Enfish (see last paragraph of page 8 of the remarks), the examiner disagrees and submits that the claims of instant application are distinct from those of Enfish and SRI International, Inc. v. CISCO Systems, Inc., 930 F.3d 1295 because the claims do not reflect the argued specific technique to solve a technological problem nor reflect an improvement to the technology.
In Enfish, the focus of the claims is on the specific asserted improvement in computer capabilities (i.e. a self-referential table for a computer database). In sum, the self-referential table recited in the claims is a specific type of data structure designed to improve the way a computer stores and retrieves data in memory. In Enfish The claimed invention achieves benefits over conventional databases such as increased flexibility, faster search times and smaller memory requirements. In the Enfish LLC v. Microsoft Corp. case the Federal circuit held that the claims were not directed to an abstract idea and further held that the claims covered "an improvement to computer functionality itself, not on economic or other tasks for which a computer is used in its ordinary capacity",
In the instant application the claimed invention as presented on the claims is not improving the computer technology but merely using a generic computer to perform calculations and data processing which is considered abstract, in addition the instant application claims does not correspond to a technology improvement, the logic or structure recited on the claims does not show specific steps as recited logic step to be considered an improvement to the computer functionality. The argued improvements appear to be a conclusory statement since the claim language does not reflect what the applicant is stating in the arguments. In addition, the claims do not reflect improvement to the computer processing but simply uses a general purpose computer for performing calculations (i.e. encoding) and determination of parameters. Therefore the claims stand rejected as being directed to non-statutory subject matter (see rejections above).
With respect to step 2B applicant submits that claim recites elements that go beyond what is routine or conventional in the test and measurement field and that claim 1 passes each step of the eligibility analysis and recites patent eligible subject matter (see antepenultimate and penultimate paragraphs on page 9 of the remarks).
In response, the examiner disagrees and submits that the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are general purpose computer “processor” and “machine learning system” used to apply the abstract idea and mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 1-2, 4, 6-7, 9-12 and 15-20 stand rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YARITZA H PEREZ BERMUDEZ whose telephone number is (571)270-1520. The examiner can normally be reached Monday-Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at (571) 272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YARITZA H. PEREZ BERMUDEZ/
Examiner
Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857