Prosecution Insights
Last updated: April 19, 2026
Application No. 17/893,071

Testing Circuitry And Methods For Analog Neural Memory In Artificial Neural Network

Non-Final OA §102§103
Filed
Aug 22, 2022
Examiner
BERMUDEZ LOZADA, ALFREDO
Art Unit
2825
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Silicon Storage Technology Inc.
OA Round
7 (Non-Final)
89%
Grant Probability
Favorable
7-8
OA Rounds
2y 3m
To Grant
91%
With Interview

Examiner Intelligence

Grants 89% — above average
89%
Career Allow Rate
461 granted / 518 resolved
+21.0% vs TC avg
Minimal +2% lift
Without
With
+1.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 3m
Avg Prosecution
39 currently pending
Career history
557
Total Applications
across all art units

Statute-Specific Performance

§101
1.2%
-38.8% vs TC avg
§103
40.7%
+0.7% vs TC avg
§102
44.3%
+4.3% vs TC avg
§112
8.4%
-31.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 518 resolved cases

Office Action

§102 §103
DETAILED ACTION Notice of 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 the following communications: the Amendment filed December 31, 2025. Claims 1-8 are pending. Claims 1 and 5 are amended. Claims 1 and 5 are independent. Continued Examination Under 37 CFR 1.114 After Final Rejection 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 December 31, 2025 has been entered. Information Disclosure Statement Acknowledgment is made of applicant’s Information Disclosure Statement (IDS) filed on November 7, 2025. These IDSs have been considered. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-3 and 5-7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jiang et al. (U.S. 2016/0099070; hereinafter “Jiang”). Regarding independent claim 1, Jiang discloses a method comprising: programming an analog neural non-volatile memory cell in an array to a target value representing one of N different values, where N is an integer and the N different values are all possible values the analog neural non-volatile memory cell will be programmed to during operation (“one or more targets data states of threshold voltage ranges,” see page 5, par. 0070); verifying that a respective one of the N different values stored in the analog neural non-volatile memory cell within an acceptable window of values set by an upper threshold and a lower threshold (see Figs. 10C-10E: the plurality of number of cells store different states and each state is set by an upper threshold and a lower threshold, for example, S1 has a starting threshold Vv1 and an ending threshold before Vv2, S2 has a starting threshold at Vv2 and an ending threshold before Vv2) around the respective target value (“several verify pulses between each program pulse to test for different program states,” see page 6, par. 0072); repeating the programming and verifying for all other values within the N values (a plurality of program pulse are applied, i.e. programming is repeated, and between each program pulse, verify pulses are applied to test for different program states, i.e. N values, see page 6, par. 0072), wherein the acceptable window of values is different in size for two or more of the N values (From Figure 10C to 10E the acceptable window of values is different in size), wherein the size is the difference between the upper threshold and the lower threshold for the acceptable window of values (Figs. 10C-10E: during the repetition of the programming and verifying, the size of the acceptable window varies from 10C to 10E. For example: the difference between Vv1’ and Vv2’ of Fig. 10C varies from the difference between Vv1 and Vv2 of Fig. 10E); and identifying the analog neural non-volatile memory cell as bad if any of the verifying indicates the respective one of the N different values stored in the cell is not within the acceptable window of values around the respective target value (see page 6, par. 0073). Regarding claim 2, Jiang discloses wherein the analog neural non-volatile memory cell is a stacked-gate flash memory cell (see page 2, par. 0044). Regarding claim 3, Jiang discloses wherein the analog neural non-volatile memory cell is a split-gate flash memory cell (see page 2, par. 0044). Regarding independent claim 5, Jiang discloses a system (Fig. 7) comprising: an array of analog neural non-volatile memory cells (Fig. 7: 700); and test control logic to: program a selected analog neural non-volatile memory cell in the array to a respective target value representing one of N different values, where N is an integer and the N different values are all possible values the analog neural non-volatile memory cell will be programmed to during operation (“one or more targets data states of threshold voltage ranges,” see page 5, par. 0070); verify that a respective one of the N different values stored in the selected analog neural non-volatile memory cell is within an acceptable window of values set by an upper threshold and a lower threshold (see Figs. 10C-10E: the plurality of number of cells store different states and each state is set by an upper threshold and a lower threshold, for example, S1 has a starting threshold Vv1 and an ending threshold before Vv2, S2 has a starting threshold at Vv2 and an ending threshold before Vv2) around the respective target value (“several verify pulses between each program pulse to test for different program states,” see page 6, par. 0072); repeat the programming and verifying for all other values within the N values (a plurality of program pulse are applied, i.e. programming is repeated, and between each program pulse, verify pulses are applied to test for different program states, i.e. N values, see page 6, par. 0072), wherein the acceptable window of values is different in size for two or more of the N values (From Figure 10C to 10E the acceptable window of values is different in size), wherein the size is the difference between the upper threshold and the lower threshold for the acceptable window of values (Figs. 10C-10E: during the repetition of the programming and verifying, the size of the acceptable window varies from 10C to 10E. For example: the difference between Vv1’ and Vv2’ of Fig. 10C varies from the difference between Vv1 and Vv2 of Fig. 10E); and identify the selected analog neural non-volatile memory cell as bad if any of the verifying indicates the respective one of the N different values stored in the cell is not within the acceptable window of values around the respective target value (see page 6, par. 0073). Regarding claim 6, Jiang discloses wherein the selected analog neural non-volatile memory cell is a stacked-gate flash memory cell (see page 2, par. 0044). Regarding claim 7, Jiang discloses wherein the selected analog neural non-volatile memory cell is a split-gate flash memory cell (see page 2, par. 0044). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 4 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Jiang et al. (U.S. 2016/0099070; hereinafter “Jiang”) in view of Lai et al. (U.S. 2020/0202941; hereinafter “Lai”). Regarding claim 4, Jiang discloses the limitations with respect to claim 1. However, Jiang is silent with respect to the array is part of a neural network. Similar to Jiang, Lai teaches programming operation in an array of non-volatile memory cell (see Abstract). Furthermore, Lai teaches wherein the array is part of a neural network (see page 1, par. 0019-0020). Since Lai and Jiang are from the same field of endeavor, the teachings described by Lai would have been recognized in the pertinent art of Jiang. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Lai with the teachings of Jiang for the purpose of provide save circuit area, see Lai’s page 4, par. 0050. Regarding claim 8, Jiang discloses the limitations with respect to claim 5. However, Jiang is silent with respect to the array is part of a neural network. Similar to Jiang, Lai teaches a system (Fig. 1) comprising test control logic (Fig. 1: PE1) to perform programming operation in an array of non-volatile memory cell (see Abstract). Furthermore, Lai teaches wherein the array is part of a neural network (see page 1, par. 0019-0020). Since Lai and Jiang are from the same field of endeavor, the teachings described by Lai would have been recognized in the pertinent art of Jiang. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teachings of Lai with the teachings of Jiang for the purpose of provide save circuit area, see Lai’s page 4, par. 0050. Response to Arguments Applicant's arguments filed with respect to claims 1 and 5 have been fully considered but they are not persuasive. With respect to claims 1 and 5, Applicant asserts that Jiang does not disclose performing programming and verifying for all N values by determining if the programmed cell is within an acceptable window of values around the target values, where the window is set by an upper threshold and a lower threshold for each target value, and where the acceptable window of values is different in size for at least two of the N values, where the size is the difference between the upper threshold and the lower threshold of the windows, see Applicant’s Remarks page 6. This particular remark is not considered persuasive. Jiang shows in Figures 10A-10E that multiple verify levels are tested, see also paragraph 0072 as described in the rejection above. Furthermore, the acceptable window of values between Figures 10C and 10E is different in size. For example: the size of the window of values shown in Figure 10C for a plurality of states is wider than the window of values shown in Figure 10E. For the above reason, the applied rejection is considered proper and maintained. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALFREDO BERMUDEZ LOZADA whose telephone number is (571)272-0877. The examiner can normally be reached 7:00AM-3:30PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexander G Sofocleous can be reached at 571-272-0635. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /Alfredo Bermudez Lozada/Primary Examiner, Art Unit 2825
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Prosecution Timeline

Aug 22, 2022
Application Filed
Jan 09, 2024
Non-Final Rejection — §102, §103
Apr 10, 2024
Response Filed
Jun 13, 2024
Final Rejection — §102, §103
Sep 18, 2024
Request for Continued Examination
Sep 20, 2024
Response after Non-Final Action
Oct 01, 2024
Non-Final Rejection — §102, §103
Dec 30, 2024
Response Filed
Feb 20, 2025
Final Rejection — §102, §103
May 16, 2025
Request for Continued Examination
May 20, 2025
Response after Non-Final Action
Jun 02, 2025
Non-Final Rejection — §102, §103
Aug 14, 2025
Response Filed
Oct 02, 2025
Final Rejection — §102, §103
Dec 31, 2025
Request for Continued Examination
Jan 20, 2026
Response after Non-Final Action
Jan 28, 2026
Non-Final Rejection — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

7-8
Expected OA Rounds
89%
Grant Probability
91%
With Interview (+1.6%)
2y 3m
Median Time to Grant
High
PTA Risk
Based on 518 resolved cases by this examiner. Grant probability derived from career allow rate.

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