Using radial basis function networks and hyper-cubes for excursion classification in semi-conductor processing equipment
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-015/18
G06N-099/00
출원번호
US-0151295
(2014-01-09)
등록번호
US-9262726
(2016-02-16)
발명자
/ 주소
Cantwell, Dermot
출원인 / 주소
Applied Materials, Inc.
대리인 / 주소
Lowenstein Sandler LLP
인용정보
피인용 횟수 :
0인용 특허 :
1
초록▼
A method and system for analysis of data, including creating a first node, determining a first hyper-cube for the first node, determining whether a sample resides within the first hyper-cube. If the sample does not reside within the first hyper-cube, the method includes determining whether the sampl
A method and system for analysis of data, including creating a first node, determining a first hyper-cube for the first node, determining whether a sample resides within the first hyper-cube. If the sample does not reside within the first hyper-cube, the method includes determining whether the sample resides within a first hyper-sphere, wherein the first hyper-sphere has a radius equal to a diagonal of the first hyper-cube.
대표청구항▼
1. A method comprising creating, by a processor, a first node;determining, by the processor, a first hyper-cube for the first node;determining, by the processor, whether a sample resides within the first hyper-cube; andif the sample does not reside within the first hyper-cube, determining, by the pr
1. A method comprising creating, by a processor, a first node;determining, by the processor, a first hyper-cube for the first node;determining, by the processor, whether a sample resides within the first hyper-cube; andif the sample does not reside within the first hyper-cube, determining, by the processor, whether the sample resides within a first hyper-sphere, wherein the first hyper-sphere has a radius equal to a diagonal of the first hyper-cube. 2. The method of claim 1 further comprising determining a likely sample class based on whether the sample resides within the first hyper-cube or the first hyper-sphere. 3. The method of claim 2 further comprising: receiving a user-selection of an excursion;creating an excursion node for the excursion;determining an excursion hyper-cube for the excursion node;determining whether the sample resides within the excursion hyper-cube about an excursion node origin;if the sample does not reside within the excursion hyper-cube, determining whether the sample resides within an excursion hyper-sphere, wherein the excursion hyper-sphere has a radius equal to a diagonal of the excursion hyper-cube; anddetermining, by the processor, a likely sample class based on whether the sample resides within the excursion hyper-cube or the excursion hyper-sphere. 4. The method of claim 3 further comprising recording an excursion label for the excursion. 5. The method of claim 3 further comprising determining whether the sample belongs to the first node or the excursion node if the sample is within both the first hyper-sphere and the excursion hyper-sphere. 6. The method of claim 2 further comprising determining a confidence estimation for the sample class. 7. The method of claim 1, wherein creating a first node comprises: receiving input vector;receiving activation function; anddetermining an activation value of the at least one node. 8. A system comprising: a memory; anda processing device coupled to the memory to: create a first node;determine a first hyper-cube for the first node;determine whether a sample resides within the first hyper-cube; andif the sample does not reside within the first hyper-cube, determine whether the sample resides within a first hyper-sphere, wherein the first hyper-sphere has a radius equal to a diagonal of the first hyper-cube. 9. The system of claim 8, wherein the processing device is further to determine a likely sample class based on whether the sample resides within the first hyper-cube or the first hyper-sphere. 10. The system of claim 9, wherein the processing device is further to: receive a user-selection of an excursion;create an excursion node for the excursion;determine an excursion hyper-cube for the excursion node;determine whether the sample resides within the excursion hyper-cube about an excursion node origin;if the sample does not reside within the excursion hyper-cube, determine whether the sample resides within an excursion hyper-sphere, wherein the excursion hyper-sphere has a radius equal to a diagonal of the excursion hyper-cube; anddetermine a likely sample class based on whether the sample resides within the excursion hyper-cube or the excursion hyper-sphere. 11. The system of claim 10, wherein the processing device is further to record an excursion label for the excursion. 12. The system of claim 10, wherein the processing device is further to determine whether the sample belongs to the first node or the excursion node if the sample is within both the first hyper-sphere and the excursion hyper-sphere. 13. The system of claim 9, wherein the processing device is further to determine a confidence estimation for the sample class. 14. The system of claim 8, wherein to create a first node, the processing device is to: receive input vector;receive activation function; anddetermine an activation value of the at least one node. 15. A non-transitory computer-readable storage medium including instructions that, when executed by a computer system, cause the computer system to perform a set of operations comprising: creating a first node;determining a first hyper-cube for the first node;determining whether a sample resides within the first hyper-cube; andif the sample does not reside within the first hyper-cube, determining whether the sample resides within a first hyper-sphere, wherein the first hyper-sphere has a radius equal to a diagonal of the first hyper-cube. 16. The non-transitory computer-readable storage medium of claim 15, wherein the operations further comprise determining a likely sample class based on whether the sample resides within the first hyper-cube or the first hyper-sphere. 17. The non-transitory computer-readable storage medium of claim 16, wherein the operations further comprise: receiving a user-selection of an excursion;creating an excursion node for the excursion;determining an excursion hyper-cube for the excursion node;determining whether the sample resides within the excursion hyper-cube about an excursion node origin;if the sample does not reside within the excursion hyper-cube, determining whether the sample resides within an excursion hyper-sphere, wherein the excursion hyper-sphere has a radius equal to a diagonal of the excursion hyper-cube; anddetermining a likely sample class based on whether the sample resides within the excursion hyper-cube or the excursion hyper-sphere. 18. The non-transitory computer-readable storage medium of claim 17, wherein the operations further comprise recording an excursion label for the excursion. 19. The non-transitory computer-readable storage medium of claim 17, wherein the operations further comprise determining whether the sample belongs to the first node or the excursion node if the sample is within both the first hyper-sphere and the excursion hyper-sphere. 20. The non-transitory computer-readable storage medium of claim 15, wherein creating a first node comprises: receiving input vector;receiving activation function; anddetermining an activation value of the at least one node.
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