Abstract: A system and method for stream mining using state machines and high-dimensionality databases. After a data stream is digitized, a stream analyzer searches a high-dimensionality data structure containing state machine parameters to determine which state machines to activate and execute. A signal classifier creates the state machine parameters stored in the high-dimensionality data structure using a second high-dimensionality data structure programmed with information about signals of interest. If a state machine identifies a signal of interest, the system can optionally alert the user.

Abstract: A high-performance object database wherein an application fetches an object from a database and the high-performance persistence framework constructs the object in memory. The database is programmed with a class that allows the application to selectively activate objects referenced by the class rather than automatically activate all referenced objects. The application selectively activates these referenced objects using read or write methods depending on whether the objects will be modified. Upon completion of the transaction, only those objects that were modified are written to disk. This high-performance persistence framework provides an object database capable of storing a large number of interconnected objects on disk and accessing them without having to activate all of the connected objects while simultaneously indexing the objects in a large number of independent dimensions all at once for fast data retrieval with complex queries.