In Re Vaidyanathan [corrected- image enlarged], (2010)

United States Court of Appeals for the Federal Circuit

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In Re Vaidyanathan [corrected- image enlarged], (2010)

NOTE: This disposition is nonprecedential.

United States Court of Appeals for the Federal Circuit (Serial No. 10/259,203)

IN RE RAVI VAIDYANATHAN

2009-1404

Appeal from the United States Patent and Trademark Office, Board of Patent Appeals and Interferences, No. 2008-2867.

Decided: May 19, 2010

BRIAN M. KOLKOWSKI, Orbital Research Inc., of Cleveland, Ohio, for appellant.

RAYMOND T. CHEN, Solicitor, Office of the Solicitor,

United States Patent and Trademark Office, of Arlington, Virginia, for the Director of the United States Patent and Trademark Office. With him on the brief were BENJAMIN

D.M. WOOD and NATHAN K. KELLEY, Associate Solicitors.

Before MICHEL, Chief Judge, NEWMAN AND DYK, Circuit Judges.

Opinion for the court filed by Circuit Judge NEWMAN.

IN RE VAIDYANATHAN 2

Circuit Judge DYK concurs in the judgment.

NEWMAN, Circuit Judge.

Ravi Vaidyanathan ("the applicant") appeals the ruling of the Board of Patent Appeals and Interferences of the United States Patent and Trademark Office, affirming the examiner's rejection of claims 1-9 of application Serial No. 10/259,203 ("the '203 application"), on the ground of obviousness, 35 U.S.C. §103(a). The Board reversed the rejection of claims 10-11. Ex parte Vaidyanathan, No. 2008-2867 (B.P.A.I. March 11, 2009) ("Board Opinion").

For claims 1-9, we vacate the rejection and remand for further examination.

DISCUSSION

The '203 application relates to a guidance and control method for controlling munitions such as missiles or unmanned aircraft, wherein an autonomous reflex response is based on a neural network model of a biological response. The method is designed for the "endgame" stage of flight when the munition is very close to the target, at which stage the system guides and controls the munition by calculating trajectory commands using a neural network that is trained using a genetic algorithm; the neural network pr...

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