Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2006-08-29
2006-08-29
Knight, Anthony (Department: 2121)
Data processing: artificial intelligence
Neural network
Learning task
C706S012000, C706S014000, C706S046000, C708S446000, C708S493000, C708S495000, C708S496000, C712S222000
Reexamination Certificate
active
07099851
ABSTRACT:
One embodiment of the present invention provides a system that solves a global optimization problem specified by a function ƒ and a set of equality constraints q1(x)=0 (i=1, . . . , r), wherein ƒ is a scalar function of a vector x=(x1, x2, x3, . . . xn). During operation, the system receives a representation of the function ƒ and the set of equality constraints and stores the representation in a memory within a computer system. Next, the system and performs an interval global optimization process to compute guaranteed bounds on a globally minimum value of the function ƒ(x) subject to the set of equality constraints. Performing this interval global optimization process involves, applying term consistency to the set of equality constraints over a subbox X, and excluding portions of the subbox X that violate the set of equality constraints.
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Hansen Eldon R.
Walster G. William
Datskovskiy Sergey
Knight Anthony
Park Vaughan & Fleming LLP
Sun Microsystems Inc.
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