Space-time-node engine signal structure

• US 9,047,353 B2
• Filed: 06/03/2014
• Issued: 06/02/2015
• Est. Priority Date: 05/03/2011
• Status: Active Grant

• Current Assignee: Nokia of America Corporation (Nokia Corporation)
• Original Assignee: Space-Time Insight
• Inventors: Kumar, Krishna
• Primary Examiner(s): CHANG, LI WU
• Application Number:
  US14/294,925
• Publication Number:
  US 20140337390A1
• Time in Patent Office: 364 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 12/0276 Generational garbage collection
• CPC Class Codes: G06F 16/2246 Trees, e.g. B+trees
• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 2212/702 Conservative garbage collection
• CPC Class Codes: G06F 3/0604 Improving or facilitating administration, e.g. storage management
• CPC Class Codes: G06F 3/0638 Organizing or formatting or addressing of data
• CPC Class Codes: G06F 3/0671 In-line storage system
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

Example methods, apparatuses, or articles of manufacture are disclosed that may be implemented using one or more computing devices or platforms to facilitate or otherwise support one or more processes or operations associated with a space-time-node engine signal structure.

Claims

1. A method comprising:

acquiring one or more sampled signals comprising digital signal vectors having one or more attributes; and

converting said digital signal vectors based, at least in part, on features of said one or more attributes, wherein said converting said digital signal vectors comprises;

electronically identifying one or more dominant attributes among a number of attributes associated with said one or more digital signals; and

electronically applying a memory sweep operation to said one or more identified dominant attributes, wherein said applying said memory sweep operation to said one or more identified dominant attributes further comprises electronically generating a transitioning curve to locate said one or more identified dominant attributes, said transitioning curve is generated based, at least in part, on electronically specifying an incremental sweep angle and an incremental radius.

2. The method of claim 1, wherein said converting said digital signal vectors comprises formatting said digital signal vectors based, at least in part, on said features of said one or more attributes.

3. The method of claim 1, wherein said one or more attributes comprises at least one of the following:

an attribute relating to time;

an attribute relating to space;

an attribute relating to a node;

or any combination thereof.

4. The method of claim 1, wherein said features of said one or more attributes includes a cardinality score based, at least in part, on a count of changing sample signal value levels of said digital signal vectors.

5. The method of claim 1, wherein said features of said one or more attributes includes, at least in part, a relationship among nodes of a graph.

6. The method of claim 5, wherein said relationship comprises, at least in part, a canonical relationship among said nodes of said graph.

7. The method of claim 1, wherein said converting is based, at least in part, on an application of a dominance principle.

8. The method of claim 7, wherein said application of said dominance principle comprises arranging said digital signal vectors in accordance with a degree of cardinality.

9. The method of claim 1, wherein said converting comprises arranging said digital signal vectors to comply with a particular signal configuration.

10. The method of claim 9, wherein said particular signal configuration comprises a linear signal configuration.

11. The method of claim 9, wherein said particular signal configuration comprises a Hamming distance-based signal configuration.

12. An apparatus comprising:

a computing platform having a capability to;

acquire one or more sampled signals comprising digital signal vectors having one or more attributes; and

format said digital signal vectors based, at least in part, on features of said one or more attributes, wherein said computing platform having said capability to format said digital signal vectors further to;

electronically identify one or more dominant attributes among a number of attributes associated with said one or more digital signals; and

electronically apply a memory sweep operation to said one or more identified dominant attributes, said memory sweep operation being applied to said one or more identified dominant attributes to electronically generate a transitioning curve to locate said one or more identified dominant attributes, said transitioning curve is generated based, at least in part, on electronically specifying an incremental sweep angle and an incremental radius.

13. The apparatus of claim 12, wherein said one or more attributes comprises at least one of the following:

an attribute relating to time;

an attribute relating to space;

an attribute relating to a node;

or any combination thereof.

14. The apparatus of claim 12, wherein said features of said one or more attributes includes a cardinality score based, at least in part, on a count of changing sample signal value levels of said digital signal vectors.

15. The apparatus of claim 12, wherein said computing platform having a capability to format said digital signal vectors is having a capability to format based, at least in part, on an application of a dominance principle.

16. The apparatus of claim 15, wherein said application of said dominance principle enables said computing platform to arrange said digital signal vectors in accordance with a degree of cardinality.