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 .
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 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Claim 1.
STEP 1: Yes. The claim recites “A method” which is a process.
STEP 2A PRONG ONE:
The claim recites multiple mathematical concepts.
sampling the signal to abstract it as an ordered set of a sequence of literals that correspond to a sequence of time stamps in a first time period;This shows defining a mathematical relationship of the signal literals to time.iteratively determining whether a sub-sequence of literals repeats in a first window of time within the first time period, wherein after every iteration, the first window of time is lengthened;This shows a mathematical calculation of literals at different times.determining a frequency of the periodic coverage artifact based on a length of time between repeating sub-sequences of literals;
This shows a mathematical calculation of division.
uniformly resampling the signal in a second window of time to determine a temporary reference voltage that is a mean of all samples in the second window of time;This shows a mathematical calculation of resampling.determining a list of reference values for a set of time periods, wherein a reference value of the list of reference values is a mean of each sample in a respective time period, wherein each time period of the set of time periods is defined by consecutive positive level crossings of the temporary reference voltage; andThis shows a calculation of findings means and establishing a mathematical relationship.
determining a Direct Current (DC) reference based on a median of the list of reference values.
This shows a mathematical calculation of taking a median of a list.
STEP 2A PRONG TWO: The claim does not integrate the exception into a practical application.
STEP 2B: The claim does not recite an inventive concept or significantly more than the exception.
Conclusion: Claim 1 is directed to mathematical concepts, not integrated into a practical application and lacks an inventive concept. Therefore, it is ineligible under 35 USC 101.
Regarding Claim 2:
The method of claim 1, further comprising: performing a signal processing operation based on determining the frequency and the DC reference.
Claim 2 merely gives instructions to apply it. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons. MPEP 2106.05(f).
Regarding Claim 3:
The method of claim 1, further comprising: mitigating signal noise when determining whether the sub-sequence of literals repeats by employing a tolerance parameter that defines a maximum number of literals that are ignored when determining whether the sub-sequence of literals repeats.
Claim 3 merely defines more mathematical calculations of removal of a tolerance parameter if reached. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 4:
The method of claim 1, wherein a number of literals in the repeating sub- sequences of literals is an even number.
Claim 4 merely defines further the list of literals. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 5:
The method of claim 1, wherein for each literal in the repeating sub- sequences of literals, a preceding literal and a succeeding literal are immediate neighbors of the literal.
Claim 5 merely defines the pattern observed. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 6:
The method of claim 1, further comprising: in response to identifying the repeating sub-sequence of literals, shifting the first window of time to a second time period.
Claim 6 merely defines the mathematical window of measure. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 7:
The method of claim 6, wherein there are respective DC references and frequencies of periodic coverage artifacts for each of the first time period and the second time period.
This merely defines mathematical variables. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 8:
The method of claim 1, further comprising: generating a list of starting timestamps and a list of ending timestamps corresponding to respective starting points and ending points of each occurrence of the repeating sub-sequences of literals.
This merely defines taking mathematical time stamps and points based on the literals. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 9:
The method of claim 1, wherein the second window of time comprises at least two occurrences of the repeating sub-sequences of literals.
This merely defines the mathematical pattern more. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 10:
The method of claim 1, further comprising: determining a peak-to-peak value of a time period based on a difference between a maximum value and a minimum value in the time period.
This merely defines taking a mathematical measurement. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claim 11:
The method of claim 1, further comprising: determining a duty cycle based on a first-time interval between a positive level crossing and a negative level crossing divided by a time period associated with the first-time interval.
This merely defines a mathematical relationship and measurement. This does not resolve the issues from the claim it depends upon and is rejected for the same reasons.
Regarding Claims 12-22:
Claims 12-22 are ineligible under 35 U.S.C 101 for the same reasons as claims 1-11. They are substantially similar except they use a “memory” and a “processor” which are generic computer components. MPEP 2106.05 (b). The dependent claims just define in more detail the mathematical concepts and do not remedy the issues from the independent claim.
Regarding Claims 23-24:
Claims 23-24 are ineligible under 35 U.S.C 101 for the same reasons as claims 1-2. They are substantially similar except they use a “non-transitory computer readable storage medium”, “memory”, and a “processor” which are generic computer components. MPEP 2106.05 (b). The dependent claims just define in more detail the mathematical concepts and do not remedy the issues from the independent claim.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 4-10, 12-13, 15-21, and 23-24 are rejected under 35 U.S.C 103 as being unpatentable over LIN et al. “Experiencing SAX: a novel symbolic representation of time series” (2007) [herein “LIN”], ELFEKY et al. “STAGGER: Periodicity Mining of Data Streams Using Expanding Sliding Windows” (2006) [herein “ELFEKY”], SMITH et al. “The Scientist and Engineer's Guide to Digital Signal Processing” (1997) [herein “SMITH”], “Op-amp Comparator” (2015) [herein “WAYBACK MACHINE”], and MARECEK et al. “Prealgebra 2e” [herein “MARECEK”] (2020).
Regarding Claim 1, LIN teaches
A method to determine parameters of a periodic coverage artifact in a signal, comprising: sampling the signal to abstract it as an ordered set of a sequence of literals that correspond to a sequence of time stamps in a first time period;“Many high-level representations of time series have been proposed for data mining, including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models, etc. Many researchers have also considered symbolic representations of time series, noting that such representations would potentiality allow researchers to avail of the wealth of data structures and algorithms from the text processing and bioinformatics communities.”. (Abstract).
“SAX allows a time series of arbitrary length n to be reduced to a string of arbitrary length w, (w < n, typically w n). The alphabet size is also an arbitrary integer a, where a > 2. Table 2 summarizes the major notation used in this and subsequent sections.”. (Pg. 112)
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“Fig. 5 A time series is discretized by first obtaining a PAA approximation and then using predetermined breakpoints to map the PAA coefficients into SAX symbols. In the example above, with n =128, w =8anda=3, the timeseries is mapped to the word baabccbc”. (Pg. 116)
This shows abstracting a signal to a sequence of literals that correspond to time stamps.
LIN does not explicitly teach but ELFEKY teachesiteratively determining whether a sub-sequence of literals repeats in a first window of time within the first time period, wherein after every iteration, the first window of time is lengthened;“STAGGER maintains multiple expanding sliding windows staggered over the stream, where computations are shared among the multiple overlapping windows”. (Abstract).
“…an online incremental algorithm that uses expanding sliding-windows in order to discover potential periodicity rates in data streams. STAGGER uses and shares the execution among multiple expanding sliding-windows that are staggered over the data stream, in order to produce interactive output. This way, STAGGER discovers a wide range of potential periodicity rates…”. (Section 1).
“A data stream of events is an infinite sequence of timestamped events drawn from a finite set of nominal2. event types. An example is an event stream in a computer network that monitors the various events. Let ei be the event occurring at timestamp i, then the data stream S is represented as S=e0,e1,…,ei,…. Each event type can be denoted by a symbol (e.g., a, b, c). The set of event types can be denoted Σ={a,b,c,⋯}. Thus, the data stream S can be considered a sequence of infinite length over a finite alphabet Σ.”. (Section 1.1).“That description of periodic patterns implies that the technique devised for periodicity detection should consider symbol periodicities. Recall that a symbol may represent an event in an event data stream or a nominal discrete level in a discretized real-valued data stream.”. (Section 3).
This shows iteratively finding repeating segments in an expanding window.determining a frequency of the periodic coverage artifact based on a length of time between repeating sub-sequences of literals;“Analyze the results from the previous step (Section 3.2) to obtain potential period lengths pj, and their corresponding maximal periodic patterns.”. (Section 2 Outline).
“Periodicity detection, in our terms, stands for discovering potential rates at which the data stream is periodic.”. (Section 3.0).
“In a data stream S, a symbol s is said to be periodic with a period of length p if s exists “almost” every p timestamp. For example, in the data stream S=abcabbabdb, the symbol b is periodic with a period of length 4 since b exists every four timestamps (positions 1, 5 and 9).”. (Section 3.1).
This shows determining periodic coverage of repeating literals.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of ELFEKY’s method of finding patterns in literals with LIN’s SAX literal method for data streams. The motivation for doing so would have been to create a pattern matching literal system as stated by ELFEKY’s “STAGGER: a one-pass, online and incremental algorithm for mining periodic patterns in data streams.”. (Abstract).
LIN and ELFEKY do not explicitly teach but SMITH teachesuniformly resampling the signal in a second window of time to determine a temporary reference voltage that is a mean of all samples in the second window of time;
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(Pg. 13).“A signal is a description of how one parameter is related to another parameter. For example, the most common type of signal in analog electronics is a voltage that varies with time.”. (Pg. 11).“Authors commonly refer to these signals as being in the time domain. This is because sampling at equal intervals of time is the most common way of obtaining signals…”. (Pg. 12).
This shows calculating a mean voltage from a signal of an electronic that is equally separated (considered to be second window).determining a list of reference values for a set of time periods,“EQUATION 2-1 Calculation of a signal's mean. The signal is contained in x0 through xN-1 , i is an index that runs through these values, and µ is the mean.”. (Pg. 13).“Table 2-1 lists a computer routine for calculating the mean and standard deviation using Eqs. 2-1 and 2-2.”. (Pg. 15).
This shows taking per cycle a mean computation for set time points.
wherein a reference value of the list of reference values is a mean of each sample in a respective time period,
“The mean, indicated by µ (a lower case Greek mu), is the statistician's jargon for the average value of a signal. It is found just as you would expect: add all of the samples together, and divide by N. It looks like this in mathematical form:”. (Pg. 13).
“Calculation of a signal's mean. The signal is contained in x0 through xN-1 , i is an index that runs through these values, and µ is the mean.”. (Pg. 13).
“In electronics, the mean is commonly called the DC (direct current) value.”. (Pg. 14).
This shows taking a mean of sampled values over a time period.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of SMITH’s method of taking a mean of a signal in time windows with LIN-ELFEKY system of literals data mining. The motivation for doing so would have been to create a pattern matching literal system for signals as stated by SMITH’s “This chapter introduces the most important concepts in statistics and probability, with emphasis on how they apply to acquired signals.”. (Pg. 11).
LIN, ELFEKY, and SMITH do not explicitly teach but WAYBACK MACHINE teaches
wherein each time period of the set of time periods is defined by consecutive positive level crossings of the temporary reference voltage; and“The window comparator detects input voltage levels that are within a specific band or window of voltages, instead of indicating whether a voltage is greater or less than some pre-set or fixed voltage reference point.
This time, instead of having just one reference voltage value, a window comparator will have two reference voltages implemented by a pair of voltage comparators.
One reference which triggers an op-amp comparator on detection of some upper voltage threshold, VREF(UPPER) and one which triggers an op-amp comparator on detection of a lower voltage threshold level, VREF(LOWER).
Then the input voltage level which operates is between these two upper and lower reference voltages is called the “window”, hence its name: window comparator.”. (Section Window Comparator).
This shows defining a window based on reference voltage limits.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of WAYBACK MACHINES’s method of crossings at reference voltages with LIN-ELFEKY-SMITH system of literals data mining. The motivation for doing so would have been to create a pattern matching literal system for signals as stated by SMITH’s “The Op-amp comparator compares one analogue input voltage level with another analogue input voltage level, or some pre-set reference voltage, VREF and produces an output signal based on this voltage comparison.”. (Section What is an Op-amp Comparator?).
LIN, ELFEKY, and WAYBACK MACHINE do not explicitly teach but SMITH teaches direct current values (Pg. 14). However, SMITH does not teach but MARECEK teachesdetermining a reference based on a median of the list of reference values.
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(Pg. 425).
This shows taking a median of a list to find a reference value.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of MARECEK’s method of median calculation with LIN-ELFEKY-SMITH-WAYBACK MACHINES system of literals data mining. The motivation for doing so would have been to create a median weighted pattern matching literal system as stated by MARECEK’s “Find the median of a set of numbers... Apply the basic definition of probability…”. (Pg. 421).
Regarding Claim 2, LIN, ELFEKY, WAYBACK MACHINE, and MARACEK do not explicitly teach but SMITH teaches
The method of claim 1, further comprising: performing a signal processing operation based on determining the frequency and the DC reference.
“Statistics and probability allow these disruptive features to be measured and classified, the first step in developing strategies to remove the offending components. This chapter introduces the most important concepts in statistics and probability, with emphasis on how they apply to acquired signals.”. (Pg. 11).
“A signal is a description of how one parameter is related to another parameter. For example, the most common type of signal in analog electronics is a voltage that varies with time.”. (Pg. 11).
This shows doing signal processing operations on a signal.
Regarding Claim 4, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but JIN teaches
The method of claim 1, wherein a number of literals in the repeating sub- sequences of literals is an even number.
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“Fig. 5 A time series is discretized by first obtaining a PAA approximation and then using predetermined breakpoints to map the PAA coefficients into SAX symbols. In the example above, with n =128, w =8anda=3, the timeseries is mapped to the word baabccbc”. (Pg. 116).
This shows the signal being represented by an even number length string.
Regarding Claim 5, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but JIN teaches
The method of claim 1, wherein for each literal in the repeating sub- sequences of literals, a preceding literal and a succeeding literal are immediate neighbors of the literal.
“Fig. 9 An illustration of the notation introduced in this section: A time series T of length 128, the subsequence C67, of length n = 16, and the first eight subsequences extracted by a sliding window. Note that the sliding windows are overlapping”. (Pg. 123).
“However, imagine for a moment that we are using our proposed approach. If the first word extracted is aabbcc, and the window is shifted to discover that the second word is also aabbcc, we can reasonably decide not to include the second occurrence of the word in sliding windows matrix. If we ever need to retrieve all occurrences of aabbcc, we can go to the location pointed to by the first occurrences, and remember to slide to the right, testing to see if the next window is also mapped to the same word. We can stop testing as soon as the word changes.”. (Pg. 123).
This shows sliding windows where before and after there is neighbors of possible identical literals.
Regarding Claim 6, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but JIN teaches
The method of claim 1, further comprising: in response to identifying the repeating sub-sequence of literals, shifting the first window of time to a second time period.
“However, imagine for a moment that we are using our proposed approach. If the first word extracted is aabbcc, and the window is shifted to discover that the second word is also aabbcc, we can reasonably decide not to include the second occurrence of the word in sliding windows matrix. If we ever need to retrieve all occurrences of aabbcc, we can go to the location pointed to by the first occurrences, and remember to slide to the right, testing to see if the next window is also mapped to the same word. We can stop testing as soon as the word changes.”. (Pg. 123).
This shows finding a match of literals and then sliding the windows to check other sections.
Regarding Claim 7, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but JIN teaches
The method of claim 6, wherein there are respective DC references and frequencies of periodic coverage artifacts for each of the first time period and the second time period.
“Fig. 10 Sliding window extraction on Space Shuttle Telemetry data, with n = 32. At time point 61, the extracted word is aabbcc, and the next 401 subsequences also map to this word. Only a pointer to the first occurrence must be recorded, thus producing a large reduction in numerosity…”. (Pg. 123).
This teaches a sliding window applied to time series, showing signal data (DC or frequency) characteristics at respective time points.
Regarding Claim 8, JIN, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but ELFEKY teaches
The method of claim 1, further comprising: generating a list of starting timestamps and a list of ending timestamps corresponding to respective starting points and ending points of each occurrence of the repeating sub-sequences of literals.
“A data stream of events is an infinite sequence of timestamped events drawn from a finite set of nominal2. event types. An example is an event stream in a computer network that monitors the various events. Let ei be the event occurring at timestamp i, then the data stream S is represented as S=e0, e1, …, ei, …. Each event type can be denoted by a symbol (e.g., a, b, c). The set of event types can be denoted Σ={a,b,c,⋯}. Thus, the data stream S can be considered a sequence of infinite length over a finite alphabet Σ.”. (Section 1.1).
“A data stream may also be an infinite sequence of timestamped values collected by a sensor measuring a specific feature. For example, the feature in a data stream for stock prices might be the final daily stock price of a specific company. If we discretize 3. the data stream feature values into nominal discrete levels and denote each level (e.g., high, medium, low) by a symbol (e.g., a, b, c), then we can use the same notation above.”. (Section 1.1).
“If the event corresponds to considering a new window wi (e.g., events at Times t1, t2, and t6 of Figure 1(b)), then apply a convolution-based algorithm [4] over the window wi (Section 3.2), sharing the results from the previous window wi−1”. (Section 3.3.2).
This shows time stamps for data points across sliding windows.
Regarding Claim 9, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but JIN teaches
The method of claim 1, wherein the second window of time comprises at least two occurrences of the repeating sub-sequences of literals.
“Fig. 9 An illustration of the notation introduced in this section: A time series T of length 128, the subsequence C67, of length n = 16, and the first eight subsequences extracted by a sliding window. Note that the sliding windows are overlapping”. (Pg. 123).
“However, imagine for a moment that we are using our proposed approach. If the first word extracted is aabbcc, and the window is shifted to discover that the second word is also aabbcc, we can reasonably decide not to include the second occurrence of the word in sliding windows matrix. If we ever need to retrieve all occurrences of aabbcc, we can go to the location pointed to by the first occurrences, and remember to slide to the right, testing to see if the next window is also mapped to the same word.”. (Pg. 123).
This shows a window that comprises sub sequences of literals that can be repeating.
Regarding Claim 10, JIN, ELFEKY, WAYBACK MACHINE, and MARACEK do not explicitly teach but SMITH teaches
The method of claim 1, further comprising: determining a peak-to-peak value of a time period based on a difference between a maximum value and a minimum value in the time period.
“If the signal is a simple repetitive waveform, such as a sine or square wave, its excursions can be described by its peak-to-peak amplitude. Unfortunately, most acquired signals do not show a well-defined peak-to-peak value, but have a random nature, such as the signals in Fig. 2-1.”. (Pg. 14).
“Figure 2-2 shows the relationship between the standard deviation and the peak-to-peak value of several common waveforms.”. (Pg. 14).
“Ratio of the peak-to-peak amplitude to the standard deviation for several common waveforms. For the square wave, this ratio is 2; for the triangle wave it is; for the sine wave it is 12 ' 3.46 2 2'2.83. While random noise has no exact peak-to-peak value, it is approximately 6 to 8 times the standard deviation”. (Pg. 15).
This shows determining a peak-to-peak value of a time period of a waveform.
Claims 12-13, 15-21, and 23-24 recites substantially the same limitations as claims 1-2, 4-10 except these claims are directed to a “signal processing device” or “non-transitory computer-readable medium comprising computer executable instructions, that when executed by a processor, perform operations”. Therefore this, claim is rejected under the same rational as addressed above.
Claims 3 and 14 are rejected under 35 U.S.C 103 as being unpatentable over LIN et al. “Experiencing SAX: a novel symbolic representation of time series” (2007) [herein “LIN”], ELFEKY et al. “STAGGER: Periodicity Mining of Data Streams Using Expanding Sliding Windows” (2006) [herein “ELFEKY”], SMITH et al. “The Scientist and Engineer's Guide to Digital Signal Processing” (1997) [herein “SMITH”], “Op-amp Comparator” (2015) [herein “WAYBACK MACHINE”], and MARECEK et al. “Prealgebra 2e” [herein “MARECEK”] (2020), and NICOLAE et al. “On string matching with k mismatches” [herein “NICOLAE”] (2013).
Regarding Claim 3, LIN, ELFEKY, SMITH, WAYBACK MACHINE, and MARACEK do not explicitly teach but NICOLAE teaches
The method of claim 1, further comprising: mitigating signal noise when determining whether the sub-sequence of literals repeats by employing a tolerance parameter that defines a maximum number of literals that are ignored when determining whether the sub-sequence of literals repeats.
“In this paper we consider several variants of the pattern matching problem. In particular, we investigate the following problems: 1) Pattern matching with k mismatches; 2) Approximate counting of mismatches; and 3) Pattern matching with mismatches.”. (Abstract).
“Pattern matching with k mismatches (or the k-mismatches problem): Take an additional input parameter k. Output all i, 1 ≤ i ≤ (n−m+1) for which the Hamming distance between titi+1, ...ti+m−1 and p1p2 ...pm is less or equal to k.”. (Pg. 1).
This shows employing a tolerance parameter for pattern matching of literals in a string.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of NICOLAE’s method of string matching with LIN-ELFEKY-SMITH-WAYBACK MACHINE-MARACEK system of literals data mining. The motivation for doing so would have been to create a pattern matching literal system that can deal with mismatched patterns as stated by NICOLAE’s “We present some novel algorithms and techniques for solving these problems. Both deterministic and randomized algorithms are offered. Variants of these problems where there could be wild cards in either the text or the pattern or both are considered.”. (Abstract).
Claim 14 recites substantially the same limitations as claim 3 except this claim is directed to a “signal processing device”. Therefore this, claim is rejected under the same rational as addressed above.
Claims 11 and 22 are rejected under 35 U.S.C 103 as being unpatentable over LIN et al. “Experiencing SAX: a novel symbolic representation of time series” (2007) [herein “LIN”], ELFEKY et al. “STAGGER: Periodicity Mining of Data Streams Using Expanding Sliding Windows” (2006) [herein “ELFEKY”], SMITH et al. “The Scientist and Engineer's Guide to Digital Signal Processing” (1997) [herein “SMITH”], “Op-amp Comparator” (2015) [herein “WAYBACK MACHINE”], MARECEK et al. “Prealgebra 2e” [herein “MARECEK”] (2020), and “dutycycle R2012b “[herein “WAYBACK MACHINE 2”] (2012).
Regarding Claim 11, WAYBACK MACHINE 2 teaches
The method of claim 1, further comprising: determining a duty cycle based on a first-time interval between a positive level crossing and a negative level crossing divided by a time period associated with the first-time interval.
“Description
D = dutycycle(X) returns the ratio of pulse width to pulse period for each positive-polarity pulse. D has length equal to the number of pulse periods in X. The sample instants of X correspond to the indices of X. To determine the transitions that define each pulse, duty cycle estimates the state levels of the input waveform by a histogram method. duty cycle identifies all regions, which cross the upper-state boundary of the low state and the lower-state boundary of the high state. The low-state and high-state boundaries are expressed as the state level plus or minus a multiple of the difference between the state levels.
”. (Section Description).
“[D,INITCROSS,FINALCROSS,NEXTCROSS] = dutycycle(X,...,Name,Value) returns the ratio of pulse width to pulse period with additional options specified by one or more Name,Value pair arguments.”. (Section Description).
“‘Polarity' Pulse polarity. Specify the polarity as 'positive' or 'negative'. If you specify 'positive', dutycycle looks for pulses with positive-going (positive polarity) initial transitions. If you specify 'negative', dutycycle looks for pulses with negative-going (negative polarity) initial transitions. See Pulse Polarity for examples of positive and negative-polarity pulses.”. (Section Name-Value Pair Arguments).
This shows taking a duty cycle of a section which can be positive and negative crossings.
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of WAYBACK MACHINE 2’s method of duty cycle with LIN-ELFEKY-SMITH-WAYBACK MACHINES-MARACEK system of literals data mining. The motivation for doing so would have been to create a pattern matching literal system for signal crossings to measure duty cycles as stated by WAYBACK MACHINE 2’s “The function identifies all regions that cross the upper-state boundary of the low state and the lower-state boundary of the high state.”. (Section Description).
Claim 22 recites substantially the same limitations as claim 11 except this claim is directed to a “signal processing device”. Therefore this, claim is rejected under the same rational as addressed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. WO 2020052957 A1 by DE et al, CN 104714953 A by LIU et al, US 20210167879 A1 by VELA et al, US 20190340392 A1 by KHORRAMI et al, US 20190268112 A1 by PARA et al, and US 20130307524 A1 by SHAVITT et al.
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/N.E.M./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189