DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under pre-AIA .
Information Disclosure Statement
The information disclosure statement filed 12/01/22, cite number 5 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered. No copy could be found in the file.
Claim Rejections - 35 USC § 112
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.
Claims 3-14 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.
Claims 6, 7, 13 and 14 each recite “the further first matrix” and “the further second matrix”. These limitations lack antecedent basis rendering it unclear to which matrices each refers to.
Claim 8 line 3 recites “a processor configured to execute machine instructions”, and line 5 recites “receiving, by a processor of the electronic device, object data”. It is unclear if the processor receiving is the same processor as the processor configured to execute machine instructions or different. For purposes of examination, Examiner interprets as the same. Claims 9-14 inherit the same deficiency as claim 8 based on dependence.
Claim 10 lines 3-6 “initializing, a second matrix (V0) by generating a standard Gaussian matrix and setting a sparse matrix (S) as 0; and initializing k, indicates the number of the performed primary optimization iteration, as 1”. It is unclear whether the initializing is being performed by the analysis model or the processor based on prior antecedent basis. For purposes of examination, Examiner interprets as the analysis model performs the initializing. Claims 11-12 inherit the same deficiency as claim 10 based on dependence. Claim 3 recites substantially the same limitation and is rejected for the same reason. Claims 4-5 inherit the same deficiency as claim 3 based on dependence.
Claim 11 recites in the preamble “wherein k, indicates the number of the performed secondary optimization iteration, is initialized as 1”. However claim 10 upon which claim 11 depends recites “initializing k, indicates the number of the performed primary optimization iteration, as 1”. It is unclear how the variable k indicates both the number of the performed primary optimization iteration and the performed secondary optimization iteration as 1. It is unclear if the initializing of k in claim 11 is in addition to the initializing of k in claim 10 or in replacement of. For purposes of examination, Examiner interprets as in addition to. Furthermore, the clause “initializing k, indicates …” in both claim 10 and claim 11 is unclear. For purposes of examination, Examiner interprets as “initializing k, wherein k indicates the number …”. Claims 3, and 4 recite substantially the same limitations and are rejected for the same reasons. Each dependent claim 4, and 5 and 11, and 12 each inherit the same deficiency as claims upon which they depend.
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 1-14 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding treatment of claims, apparatus claims 8-14 will be treated first followed by method claims 1-7.
Regarding claim 1, under the Alice framework Step 1, the claims fall within the four statutory categories of patentable subject matter identified by 35 USC 101: a process, machine, manufacture or a composition of matter.
Under the Alice framework Step 2A prong 1, claim 8 recites mental steps and/or mathematical concepts of mathematical calculations and mathematical relationships for calculating an optimization of a low-rank matrix recovery using Hybrid Ordinary-Welsch Function (HOW). Specifically, claim 8 recites the following mental steps and/or mathematical calculations and mathematical relationships:
a robust low-rank matrix recovery using Hybrid Ordinary-Welsch Function (HOW), comprising:
the object data comprises an incomplete matrix, wherein the incomplete matrix is a low-rank matrix;
identifying a plurality of first values and a plurality of first indexes of a plurality of first entries of the incomplete matrix, and one or more second values and one or more second indexes of one or more second entries of the incomplete matrix according to the object data,
wherein the first values of the first entries are determined as original values of the first entries, and the one or more second values of the second entries are determined as non-original values of the second entries;
inputting the first values (XΩ), the first indexes (Ω), a rank r, the second indexes, a preset first parameter (ξ1), a preset second parameter (ξ2), a first maximum iteration number (I1), a second maximum iteration number (I2), a first tolerance parameter (ζ1) and a second tolerance parameter (ζ2) into an executed analysis model using HOW algorithm; and
obtaining a recovered complete matrix corresponding to the incomplete matrix from the analysis model, so as to obtain optimized one or more second values of the second entries, wherein the optimized one or more second values are determined as original values of the second entries, such that missing data corresponding to the second entries of the incomplete matrix is recovered by the recovered complete matrix.
See figures 8, and specification p. 11-12, equations (20), (32), (33), (34), which describe the claimed invention in terms of mathematical calculations and mathematical relationships. For these reasons claim 8 recites mental steps and/or mathematical concepts. Furthermore the steps of identifying a plurality of first values and a plurality of first indexes of a plurality of first entries of the incomplete matrix, and one or more second values and one or more second indexes of one or more second entries of the incomplete matrix according to the object data, wherein the first values of the first entries are determined as original values of the first entries, and the one or more second values of the second entries are determined as non-original values of the second entries comprises a mental step in addition to mathematical concepts.
Under the Alice framework Step 2A prong 2 analysis, claim 1 recites the following additional elements: an electronic device comprising a processor, configured to execute machine instructions to implement a computer implemented method, the method comprising: receiving, by a processor of the electronic device, object data, and steps performed by the processor. These additional elements are merely generically recited computer functions that merely “apply it” in a processor or merely recite includes instructions to implement the abstract idea or merely uses the computer as a tool to perform the abstract idea. Furthermore, the steps of receiving object data merely comprises an insignificant extra solution activity. For these reasons, claim 8 is not integrated into a practical application.
Under the Alice Framework Step 2B analysis, claim 8 considered individually and as an ordered combination do not include additional elements that are sufficient to amount to significantly more than the abstract idea. As stated in the Step 2A prong 2 analysis, the claims do no more than merely generally link the use of the mathematical concepts to a computer in a manner that merely recites “apply it”, or merely includes instructions to implement the abstract idea, or merely uses the computer as a tool to perform the abstract idea. Furthermore the receiving object data is well understood, routine, and conventional activity. See MPEP 2106.05.(d).II.i, iv receiving data over a network, and retrieving information from memory. For these reasons claim 8 does not amount to significantly more than the abstract idea.
Claims 9-14 are rejected for at least the reasons set forth with respect to claim 8. Claims 9-14 further mathematically limit the mathematical concepts of claim 8. Claims 9-14 recite no further additional elements that would require further analysis under steps 2A prong 2 and step 2B. As to claim 9, the steps of “starting”, “ending”, and “initializing” are each interpreted as part of the mathematical concepts because they are performed by the analysis model, a mathematical model and not a processor. As to claim 10, the claim does not make clear what is performing the initializing, the processor or the analysis model. As per the rejection under 35 USC 112(b), this step is being interpreted as being performed by the analysis model, the abstract idea.
Claims 1-7 are directed to a method that would be practiced by the apparatus of claims 8-14. All steps performed by the method of claims 1-7 are executed by the apparatus as in claims 8-14 as configured. The claim 8-14 analysis applies equally to claims 1-7.
Allowable Subject Matter
Claims 1-14 would be allowable if rewritten to overcome the rejections under 35 USC 101 and the respective rejections under 35 USC 112(b) for claims 3-14.
The following is a statement of reasons for indication of allowable subject matter. Applicant claims apparatus, a methods and apparatus for performing a robust low-rank matrix recovery using Hybrid Ordinary-Welsch Function (HOW), wherein the apparatus as in claim 8 recites:
a processor, configured to execute machine instructions to implement a computer-implemented method, the method comprising:
receiving, by a processor of the electronic device, the object data comprises an incomplete matrix, wherein the incomplete matrix is a low-rank matrix;
identifying, by the processor, a plurality of first values and a plurality of first indexes of a plurality of first entries of the incomplete matrix, and one or more second values and one or more second indexes of one or more second entries of the incomplete matrix according to the object data,
wherein the first values of the first entries are determined as original values of the first entries, and the one or more second values of the second entries are determined as non-original values of the second entries;
inputting, by the processor, the first values (XΩ), the first indexes (Ω), a rank r, the second indexes, a preset first parameter (ξ1), a preset second parameter (ξ2), a first maximum iteration number (I1), a second maximum iteration number (I2), a first tolerance parameter (ζ1) and a second tolerance parameter (ζ2) into an executed analysis model using HOW algorithm; and
obtaining, by the processor, a recovered complete matrix corresponding to the incomplete matrix from the analysis model, so as to obtain optimized one or more second values of the second entries, wherein the optimized one or more second values are determined as original values of the second entries, such that missing data corresponding to the second entries of the incomplete matrix is recovered by the recovered complete matrix.
The primary reason for indication of allowable subject matter are the specific algorithmic steps claimed in combination as above.
L. Gao, et al., Robust Sparse Recovery in Impulsive Noise via M-Estimator and Non-Convex Regularization, IEEE Access vol 7, 2019 (hereinafter “Gao”) discloses an efficient first-order algorithm with low computational complexity using the alternating direction method of multipliers framework and half-quadratic optimization (abstract). Gao further discloses using the Welsch M-estimator (Introduction, p. 3, section III, section IV). Gao does not, however, teach or suggest the specific algorithmic steps claimed in combination.
US 20160275416 A1 Min et al., (hereinafter “Min”) discloses systems and method for nonnegative matrix factorization and completion for big data (title, abstract, [0003]). Min further discloses a greedy algorithm and rank-one alternative direction method (technique 1, technique 2). Min does not, however, teach or suggest the specific algorithmic steps claimed in combination.
US 11010635 B2 So et al., (hereinafter “So”) discloses a method for obtaining low-rank representation of data near a low-dimensional subspace and data reconstruction (abstract, col 1 line 6-10). So further discloses a greedy pursuit algorithm and a rank-one fitting algorithm of multiple matrices (algorithm 1, algorithm 3).
Z.Y. Wang et al., Robust Low-Rank Matrix Recovery via Hybrid Ordinary-Welsch Function, IEEE Transactions on Signal Processing, Vol 71, 2023 (hereinafter “Wang”) disclosure by inventors of aspects of the claimed invention.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EMILY E LAROCQUE whose telephone number is (469)295-9289. The examiner can normally be reached on 10:00am - 1200pm, 2:00pm - 8pm ET M-F.
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/EMILY E LAROCQUE/ Primary Examiner, Art Unit 2182
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