DETAILED ACTION
This Action is in consideration of the Applicant’s response on May 2, 2026. No Claims are amended by the Applicant. Claims 1 – 7, 12 – 14, and 16 – 21, where Claims 1, 12, and 14 are in independent form, are presented for examination.
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 .
Specification
The amendment filed May 2, 2026 is objected to under 35 U.S.C. 132(a) because it introduces new matter into the disclosure. 35 U.S.C. 132(a) states that no amendment shall introduce new matter into the disclosure of the invention. The added material which is not supported by the original disclosure is as follows: the various hardware implementations of the claimed counting module and the decision-making module were not previous described in the specification. While these technologies may have been well-known to one of ordinary skill in the art, they were not disclosed or supported in the originally filed specification [See Remarks, Pgs. 9-10]. Additionally, the claimed structure has been admitted by the Applicant as prior art [See Remark, Pgs. 9].
Applicant is required to cancel the new matter in the reply to this Office Action.
Response to Arguments
Applicant’s arguments filed on May 2, 2026 have been fully considered but they are not persuasive. Applicant argued:
Regarding Claims 1 and 14, specification describes specific structure for the claimed “counting module” and “decision-making module” to overcome 112(b) indefiniteness rejection when invoking 35 USC 112(f).
Regarding Claims 1, 12, and 14, Linares-Barranco does not disclose or suggest a network-level counter.
The Office respectfully disagrees with Applicant’s assertions.
1. With regards to a), the amendments to the specification to include the particular structure for the “counting module” and “decision-making module” are not implicit or inherent from the originally filed specification as Applicant opines [See Remarks, Pg. 10, 2nd Para.]. Even if the structures are conventional and well-known to a PHOSITA, the structures would need to be in the originally filed specification. The 112(b) rejection is maintained.
Additionally, the Applicant argues that a digital synchronous sequential counter circuit for performing the “counting” and a digital comparator and trigger circuit for performing the “decision-making” are conventional and well-known to a PHOSITA [See Remarks, Pgs.8-9]. The Applicant’s admission that these components are prior art is acknowledged.
2. With regards to b), the Office reminds the Applicant that the pending claims must be "given the broadest reasonable interpretation consistent with the specification" [In re Prater, 162 USPQ 541 (CCPA 1969)] and "consistent with the interpretation that those skilled in the art would reach" [In re Cortright, 49 USPQ2d 1464 (Fed. Cir. 1999)].
The claim recites “to count a number of input spike events of the spiking neural network.” Nothing within the claims indicates that the counter counts the spiking events of the entire neural network as argued by the Applicant [See Remarks, Pg. 12]. Nothing indicates specifically how many inputs or outputs are being received. The neuron circuit has both an input and output layer and in part of the spiking neural network [See Linares-Barranco, Figs. 1A, 1B, 5, and 7]. Counting the input spike events in one neural circuit that is part of a spiking neural network reads on the limitation of “count(ing) a number of input spike events of the spinking neural network as claimed.
Claim Rejections - 35 USC § 112
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1 – 7, 14, and 16 – 21 are 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.
3. Claim limitation “counting module” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification provides a generalized box to perform the functions and the possibility of the module being within or outside the neuromorphic chip. However, no structure for performing the counting is described. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
4. Claim limitation “decision-making module” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification provides a generalized box to perform the functions, the possibility of the module being within or outside the neuromorphic chip, and a portion of the module comprising a low-pass filter, which also can be software [Fig. 5; Para. 0063-64, 0070]. However, no structure for performing the decision-making is described. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 12, and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Applicant’s admission of prior art.
5. Regarding Claims 1, 12, and 14, the claims are rejected based on the components that have been argued as conventional and well-known to a PHOSITA to contain the structure to perform the claimed functions in the attempt to amend the specification [See Remarks, Pgs. 8-9].
Claim(s) 1 – 7, 12 – 14, and 16 – 21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by PGPub. 2019/0138900 (hereinafter “Linares-Barranco”).
6. Regarding Claim 1, Linares-Barranco discloses a spike event decision-making device [Fig. 7; Para. 0137; neuron circuit], configured to make a decision based on output spike events of a spiking neural network in the neuromorphic chip [Figs. 5, 7, and 10; Para. 0137; neuron circuit within a SNN], the spike event decision-making device comprising:
a first counting module, configured to count a number of input spike events of the spiking neural network [Figs. 1a and 7; Para. 0118-119, 0139-142; learning counter]; and
a decision-making module is configured to generate a decision-making result according to numbers of spike events fired by a plurality of neurons in an output layer of the spiking neural network when the number counted by the first counting module reaches a first predetermined value [Figs. 7, 10; Para. 0119, 0144; first comparator module decides on an output signal].
7. Regarding Claim 2, Linares-Barranco discloses the limitations of Claim 1. Linares-Barranco further discloses of comprising:
a second counting module [Fig. 7; Para. 0165-168; firing counter], configured to perform one of following operations to count the numbers of spike events fired by the plurality of neurons in the output layer of the spiking neural network:
(i) counting spikes fired by each neuron in the output layer, and adding them up to obtain a total count of the spikes fired by a part or all neurons in the output layer;
(ii) counting spikes fired by a plurality of neurons in the output layer to obtain the total count [Para. 0165-168]; and
(iii) counting spikes fired by each neuron in the output layer without adding them up.
8. Regarding Claim 3, Linares-Barranco discloses the limitations of Claim 1. Linares-Barranco further discloses that the decision-making module is further configured to make a decision when the number counted by the first counting module reaches the first predetermined value or when the count of the first count module reaches the first predetermined value and when a number counted by the second counting module reaches a second predetermined value [Fig. 7; Para. 0139-142, 0165-168].
9. Regarding Claim 4, Linares-Barranco discloses the limitations of Claim 1. Linares-Barranco further discloses that when there are at least two successive decision-making results, there is a partial overlap between the input spike events corresponding to the two corresponding numbers counted by the first counting module; and/or, there is partial overlap between the spike events fired by the neurons in the output layer of the spiking neural network corresponding to the two corresponding numbers counted by the second counting module [Fig. 7; Para. 0139-142, 0165-168].
10. Regarding Claim 5, Linares-Barranco discloses the limitations of Claim 2. Linares-Barranco further discloses that the second counting module uses a plurality of sub-counter to count spike events fired by each of the plurality of neurons in the output layer, to remove an earliest count in the sub-counter, and to use a zeroed sub-counter to count new spike events; and a sum of counts in all sub-counters corresponding to each neuron in the output layer is used as a count on which the decision-making result is based [Para. 0165-168].
11. Regarding Claim 6, Linares-Barranco discloses the limitations of Claim 1. Linares-Barranco further discloses that when a plurality of successive decision-making results meet one or a plurality of conditions below, then outputting a decision-making result with the largest number of occurrences in the successive decision-making results: (i) when a transition rate or a number of transitions of the successive decision-making results is lower than a first threshold [Para. 0165-168; fixed firing threshold value can be lower than the learning threshold counter]; and (ii) when a ratio of the decision result with the most occurrences to the successive decision-making results is higher than a second threshold; otherwise, stopping outputting any decision result or outputting the decision result with an uncertain indication result.
12. Regarding Claim 7, Linares-Barranco discloses the limitations of Claim 1. Linares-Barranco further discloses that one or more of the first counting module, and the decision-making module is implemented inside or outside the neuromorphic chip [Fig. 7; inside].
13. Regarding Claim 12, Linares-Barranco discloses a spike event decision-making method, configured to make a decision based on output spike events of a spiking neural network in a neuromorphic chip [Figs. 5, 7, 10, and 11; Para. 0137; neuron circuit within a SNN], the method comprising:
counting a number of input spike events of the spiking neural network to obtain a first count value [Figs. 1a and 7; Para. 0118-119, 0139-142; learning counter]; and
generating a decision-making result according to counts of spike events of each of a plurality of neurons in an output layer of the spiking neural network when the first count value reaches a first predetermined value [Figs. 7, 10; Para. 0119, 0144; first comparator module decides on an output signal]; or counting a number of output spike events of some or all neurons in the output layer of the spiking neural network to obtain a second count value [Para. 0165-168]; and
generating a decision-making result according to counts of spike events of each of the neurons in an output layer of the spiking neural network when the second count value reaches a second predetermined value [Fig. 7; Para. 0165-168].
14. Regarding Claim 13, Linares-Barranco discloses the limitations of Claim 12. Linares-Barranco further discloses that there is at least a partial overlap between the input spike events corresponding to the first count value obtained twice when two adjacent decision-making results are made; or/and, use a plurality of sub-counter to count each spike event emitted by some or all neurons of the output layer; remove the earliest count in the sub-counter, and use the zeroed sub-counter to count the newly issued spike events; the sum of counts in all sub-counters corresponding to each neuron in the output layer is used as the count on which the decision result is based [Fig. 7; Para. 0139-142, 0165-168].
15. Regarding Claim 14, Linares-Barranco discloses a chip deploying a spike neural network, comprising a spike event decision-making device, wherein the spike event decision-making device is configured to make decisions on output spike events of the spike neural network by an event imaging device [Figs. 5, 7, 10, and 11; Para. 0137; neuron circuit within a SNN], the spike event decision-making device comprising:
a first counting module, configured to count a number of input spike events of the spiking neural network [Figs. 1a and 7; Para. 0118-119, 0139-142; learning counter]; and
a decision-making module is configured to generate a decision-making result according to numbers of spike events outputted by a plurality of neurons in an output layer of the spiking neural network when the number counted by the first counting module reaches a first predetermined value [Figs. 7, 10; Para. 0119, 0144; first comparator module decides on an output signal].
16. Regarding Claim 16, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that the spike event decision-making device further comprises:
a second counting module [Fig. 7; Para. 0165-168; firing counter], configured to perform one of following operations to count the numbers of spike events outputted by the plurality of neurons in the output layer of the spiking neural network: (i) counting spikes outputted by each neuron in the output layer, and adding them up to obtain a total count of the spikes outputted by a part or all neurons in the output layer; (ii) counting spikes outputted by a plurality of neurons in the output layer to obtain the total count [Fig. 7; Para. 0165-168; firing counter]; and (iii) counting spikes outputted by each neuron in the output layer without adding them up.
17. Regarding Claim 17, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that the decision-making module is further configured to make a decision when the number counted by the first counting module reaches the first predetermined value or when the count of the first count module reaches the first predetermined value and when a number counted by the second counting module second count module reaches a second predetermined value [Fig. 7; Para. 0139-142, 0165-168].
18. Regarding Claim 18, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that when there are at least two successive decision-making results, there is a partial overlap between the input spike events corresponding to the two corresponding numbers counted by the first counting module; and/or, there is partial overlap between the spike events outputted by the neurons in the output layer of the spiking neural network corresponding to the two corresponding numbers counted by in the second counting module [Fig. 7; Para. 0139-142, 0165-168].
19. Regarding Claim 19, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that the second counting module uses a plurality of sub-counter to count spike events outputted by each of the plurality of neurons in the output layer, to remove an earliest count in the sub-counter, and to use a zeroed sub-counter to count new spike events; and a sum of counts in all sub-counters corresponding to each neuron in the output layer is used as a count on which the decision-making result is based [Para. 0165-168].
20. Regarding Claim 20, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that when a plurality of successive decision-making results meet one or a plurality of conditions below, then outputting a decision-making result with the largest number of occurrences in the successive decision-making results: (i) when a transition rate or a number of transitions of the successive decision-making results is lower than a first threshold [Para. 0165-168; fixed firing threshold value can be lower than the learning threshold counter]; and (ii) when a ratio of the decision result with the most occurrences to the successive decision-making results is higher than a second threshold; otherwise, stopping outputting any decision result or outputting the decision result with an uncertain indication result.
21. Regarding Claim 21, Linares-Barranco discloses the limitations of Claim 14. Linares-Barranco further discloses that the one or more of the first counting module, the second counting module, and the decision-making module is implemented inside or outside the neurochip [Fig. 7; inside].
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contacts
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAE K KIM whose telephone number is (571)270-1979. The examiner can normally be reached M-F 9:30-5:30.
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, Jorge Ortiz-Criado can be reached at 5712727642. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TAE K KIM/Primary Examiner, Art Unit 2496
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