Feedforward neural network system for the detection and characte

Details Feedforward neural network system for the detection and characte Feedforward neural network system for the detection and characte

1994-11-23

1996-03-26

Pihulic, Daniel T.

Communications, electrical: acoustic wave systems and devices

Underwater system

367135, 367901, H04B 1100, G01S 386

Patent

active

055026885

ABSTRACT:
The present invention provides a method and system for characterizing the sounds of ocean captured by passive sonar listening devices. The present invention accomplishes this by first generating a spectrogram from the received sonar signal. The spectrogram is characterized in terms of textural features and signal processing parameters. The textural features and signal processing parameters are fed into a neural network ensemble that has been trained to favor specific features and/or parameters. The trained neural network ensemble classifies the signal as either Type-I or clutter.

REFERENCES:
patent: 5181254 (1993-01-01), Schweizer et al.
patent: 5214744 (1993-05-01), Schweizer et al.
patent: 5233354 (1993-08-01), Roth et al.
patent: 5235339 (1993-08-01), Morrison et al.
Haralick et al., "Textural Features for Image Classification," IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-3, No. 6, Nov. 1973, pp. 610-621.
Weszka et al., "A Comparative Study of Texture Measures for Terrain Classification," IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-6, No. 4, Apr. 1976, pp. 269-285.
A. P. Russo, "Constrained Neural Networks for Recognition of Passive Sonar Signals Using Shape," Proc. of the IEEE Conf. on Neural Networks for Ocean Engineering, Washington, DC (1991), pp. 69-76.
Barton et al., "Calibrating the Performance of Neural Networks," Proc. of the IEEE Conf. on Neural Networks for Ocean Engineering, Washington, DC, Aug. 1991, pp. 343-351.

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