Vector neural network for low signal-to-noise ratio detection of

Details Vector neural network for low signal-to-noise ratio detection of Vector neural network for low signal-to-noise ratio detection of

1991-03-11

1993-05-11

Boudreau, Leo H.

Image analysis

Histogram processing

For setting a threshold

358125, 342 96, 395 22, G06K 962

Patent

active

052107981

ABSTRACT:
A vector neural network (VNN) of interconnected neurons is provided in transition mappings of potential targets wherein the threshold (energy) of a single frame does not provide adequate information (energy) to declare a target position. The VNN enhances the signal-to-noise ratio (SNR) by integrating target energy over multiple frames including the steps of postulating massive numbers of target tracks (the hypotheses), propagating these target tracks over multiple frames, and accommodating different velocity target by pixel quantization. The VNN then defers thresholding to subsequent target stages when higher SNR's are prevalent so that the loss of target information is minimized, and the VNN can declare both target location and velocity. The VNN can further include target maneuver detection by a process of energy balancing hypotheses.

REFERENCES:
patent: 4121192 (1978-10-01), Wilson
patent: 4906940 (1990-03-01), Greene et al.
patent: 4931868 (1990-06-01), Kadar
Cho et al., "Strategies for Applying Neural Networks to Real World Problems" International Neural Network Conference, Jul. 9-13, 1990.
Lupo, "Defense Applications of Neural Networks", IEEE Communications Magazine, Nov. 1989.

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