Efficient combinatorial optimization by quantum-inspired parallel annealing in analogue memristor crossbar
US-2024419761-A1 · Dec 19, 2024 · US
US11036470B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11036470-B2 |
| Application number | US-201715798345-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 30, 2017 |
| Priority date | Oct 30, 2017 |
| Publication date | Jun 15, 2021 |
| Grant date | Jun 15, 2021 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A method for operating a data processing system to analyze data sets for groupings and a computer readable medium having instructions to execute that method are disclosed. The method includes causing the data processing system to receive a plurality of data sets, each data set including a plurality of values characterized by a statistical distribution and a label. The method also includes causing the data processing system to compute a plurality of statistical parameters for each of the plurality of data sets, to generate a data set vector having components equal to the plurality of statistical parameters for each of the plurality of data sets, to assign each data set to a cluster based on the data set vectors using a clustering algorithm, and to generate a display of the statistical distributions as a function of the labels in which the statistical distributions belonging to the same cluster are grouped together.
Opening claim text (preview).
What is claimed is: 1. A method for operating a data processing system to analyze data sets for groupings, said method comprising causing said data processing system to: receive a plurality of data sets, each data set comprising a plurality of measurements of a first physical quantity made by a corresponding test instrument, and a label identifying said test instrument, and being characterized by a statistical distribution; compute a plurality of statistical parameters for each of said plurality of data sets; generate a data set vector having components equal to said plurality of statistical parameters for each of said plurality of data sets; assign each data set to a cluster based on said data set vectors using a clustering algorithm; and generate a graph of said statistical distributions as a function of said labels on a display of said data processing system that is viewed by user to determine if systematic variations in said data sets are the result of variations in said test instruments or variations in components measured by said test instruments in which said statistical distributions belonging to the same cluster are grouped together along a first axis of said graph with said labels being shown on said first axis and said statistical distributions are displayed on a second axis of said graph, wherein each statistical distribution comprises a one-dimensional scatter plot of said measurement values of said dataset corresponding to said label and adjacent clusters are separated by a dividing line parallel to said second axis. 2. The method of claim 1 wherein said display comprises a graph of a symbol associated with said statistical parameters, said symbol located at a median value or an average value of said data set values. 3. The method of claim 1 wherein said data sets are further ordered within each cluster in said graph by said median value or said average value. 4. The method of claim 1 wherein said display comprises a graph of a symbol associated with said statistical parameters as a function of said label, said symbol located at a median value or average value of said plurality of measurements made by that test instrument. 5. The method of claim 4 wherein said symbol comprises a boxplot. 6. The method of claim 1 wherein each of said test instruments comprises a second test probe different from said first test probe and provides a measurement of a second physical quantity by said second test probe, and wherein said data processing system generates a plurality of statistical parameters that characterize a statistical distribution for a set of measurements corresponding to each of said plurality of test instruments and said second test probe associated with that test instrument and said instrument vectors further comprising said second plurality of statistical parameters. 7. A computer readable medium comprising instructions that cause a data processing system to execute a method that causes said data processing system to: receive a plurality of data sets, each data set comprising a plurality of measurements of a first physical quantity made by a corresponding test instrument, and a label identifying said test instrument, and being characterized by a statistical distribution; compute a plurality of statistical parameters for each of said plurality of data sets; generate a data set vector having components equal to said plurality of statistical parameters for each of said plurality of data sets; assign each data set to a cluster based on said data set vectors using a clustering algorithm; and generate a graph of said statistical distributions as a function of said labels on a display of said data processing system that is viewed by user to determine if systematic variations in said data sets are the result of variations in said test instruments or variations in components measured by said test instruments in which said statistical distributions belonging to the same cluster are grouped together along a first axis of said graph with said labels being shown on said first axis and said statistical distributions are displayed on a second axis of said graph, wherein each statistical distribution comprises a one-dimensional scatter plot of said measurement values of said dataset corresponding to said label and adjacent clusters are separated by a dividing line parallel to said second axis. 8. The computer readable medium of claim 7 wherein said display comprises a graph of a symbol associated with said statistical parameters, said symbol located at a median value or an average value of said data set values. 9. The computer readable medium of claim 7 wherein said data sets are further ordered within each cluster in said graph by said median value or said average value. 10. The computer readable medium of claim 7 wherein said display comprises a graph of a symbol associated with said statistical parameters as a function of said label, said symbol located at a median value or average value of plurality of said measurements made by that test instrument. 11. The computer readable medium of claim 10 wherein said symbol comprises a boxplot. 12. The computer readable medium of claim 7 wherein each of said test instruments comprises a second test probe different from said first test probe and provides a measurement of a second physical quantity by said second test probe, and wherein said data processing system generates a plurality of statistical parameters that characterize a statistical distribution for a set of measurements corresponding to each of said plurality of test instruments and said second test probe associated with that test instrument and said instrument vectors further comprising said second plurality of statistical parameters.
for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title
Updates performed during online database operations; commit processing · CPC title
Sorting, i.e. grouping record carriers in numerical or other ordered sequence according to the classification of at least some of the information they carry (by merging two or more sets of carriers in ordered sequence G06F7/16) · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.