Hybrid neural network generation system and method

Details Hybrid neural network generation system and method Hybrid neural network generation system and method

2008-03-04

2008-03-04

Hirl, Joseph P (Department: 2129)

Data processing: artificial intelligence

Neural network

Learning task

C706S012000, C706S014000, C706S015000

Reexamination Certificate

active

11636322

ABSTRACT:
A computer-implemented method and system for building a neural network is disclosed. The neural network predicts at least one target based upon predictor variables defined in a state space. First, an input data set is retrieved that includes the predictor variables and at least one target associated with the predictor variables for each observation. In the state space, a number of points is inserted in the state space based upon the values of the predictor variables. The number of points is less than the number of observations. A statistical measure is determined that describes a relationship between the observations and the inserted points. Weights and activation functions of the neural network are determined using the statistical measure.

REFERENCES:
patent: 5335291 (1994-08-01), Kramer et al.
patent: 5519319 (1996-05-01), Smith et al.
patent: 5650722 (1997-07-01), Smith et al.
patent: 5675253 (1997-10-01), Smith et al.
patent: 5761442 (1998-06-01), Barr et al.
patent: 6453206 (2002-09-01), Soraghan et al.
patent: 6549861 (2003-04-01), Mark et al.
patent: 6601049 (2003-07-01), Cooper
patent: 6631212 (2003-10-01), Luo et al.
patent: 6650779 (2003-11-01), Vachtesvanos et al.
patent: 6675145 (2004-01-01), Yehia et al.
patent: 6678640 (2004-01-01), Ishida et al.
Kishan Mehrotra et al., Elements of Artificial Neural Networks, 1997, MIT.
A.S.Y. Wong, et al., A Unified Sequential Method for PCA, IEEE, 0-7803-5682-Sep. 1999, 583-586.
Rudiger W. Brause, Cascaded Vector Quantization by Non-linear PCA Network Layers, IEEE, 1994, 1063-6730/94, 154-160.
Chan, Lipchen Alex et al., “Automatic target detection using dualband infrared imager”, Acoustics, Speech, and Signal PICASSP'00. Proceedings 2000 IEEE International Conference, Jun. 9, 2000, pp. 2286-2289.
Chatterjee, Chanchal et al., “Self-Organizing Algorithms for Generalized Eigen-Decomposition”, IEEE Transactions on Neural Networks, vol. 8, No.6, Nov. 1997, pp. 1518-1530.
Chen, Yupeng et al., “High Resolution Adaptive Bearing Estimation Using A Complex-Weighted Neural Network”, 1992, IEEE, 0-7803-0532-Sep. 1992, pp. 11-317-1111-320.
Mehrotra, Kishan et al., “Elements of Artificial Neural Networks”, 1997, MIT Press, 0-262-13328-8, pp. 11, 25, 71 76, 85-87, 157, 170-171.
Wong, A.S.Y. et al., “A Unified Sequential Method for PCA”, 1999, IEEE, 0-7803-5682-Sep. 1999, pp. 583-586.

Affiliated with

Also associated with

Rating

Hybrid neural network generation system and method does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Hybrid neural network generation system and method, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Hybrid neural network generation system and method will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3925200