Target detecting neural network architecture for serial sensor data streams

Tim L. Overman; Ahmed Louri

Target detecting neural network architecture for serial sensor data streams

Tim L. Overman, Ahmed Louri

Research output: Contribution to conference › Paper › peer-review

Abstract

A Neural Network Target Detection Architecture is presented based on the Multilayer Perceptron Neural Receiver defined by Watterson. The neural network was trained to detect a Gaussian spot and allowed to detect the target through various levels of white Gaussian noise. Investigation into the architecture's performance through Monte Carlo simulations shows that the architecture gives 75% improvement in the probability of detection than the Rayleigh Channel Receiver. Finally, the real-time computing requirements for the neural network architecture are addressed and presented.

Original language	English (US)
Pages	393-403
Number of pages	11
State	Published - 1994
Externally published	Yes
Event	Proceedings of the Electro'94 International Conference - Boston, MA, USA Duration: May 10 1994 → May 12 1994

Other

Other	Proceedings of the Electro'94 International Conference
City	Boston, MA, USA
Period	5/10/94 → 5/12/94

ASJC Scopus subject areas

General Engineering

Cite this

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title = "Target detecting neural network architecture for serial sensor data streams",

abstract = "A Neural Network Target Detection Architecture is presented based on the Multilayer Perceptron Neural Receiver defined by Watterson. The neural network was trained to detect a Gaussian spot and allowed to detect the target through various levels of white Gaussian noise. Investigation into the architecture's performance through Monte Carlo simulations shows that the architecture gives 75% improvement in the probability of detection than the Rayleigh Channel Receiver. Finally, the real-time computing requirements for the neural network architecture are addressed and presented.",

author = "Overman, {Tim L.} and Ahmed Louri",

year = "1994",

language = "English (US)",

pages = "393--403",

note = "Proceedings of the Electro'94 International Conference ; Conference date: 10-05-1994 Through 12-05-1994",

}

TY - CONF

T1 - Target detecting neural network architecture for serial sensor data streams

AU - Overman, Tim L.

AU - Louri, Ahmed

PY - 1994

Y1 - 1994

N2 - A Neural Network Target Detection Architecture is presented based on the Multilayer Perceptron Neural Receiver defined by Watterson. The neural network was trained to detect a Gaussian spot and allowed to detect the target through various levels of white Gaussian noise. Investigation into the architecture's performance through Monte Carlo simulations shows that the architecture gives 75% improvement in the probability of detection than the Rayleigh Channel Receiver. Finally, the real-time computing requirements for the neural network architecture are addressed and presented.

AB - A Neural Network Target Detection Architecture is presented based on the Multilayer Perceptron Neural Receiver defined by Watterson. The neural network was trained to detect a Gaussian spot and allowed to detect the target through various levels of white Gaussian noise. Investigation into the architecture's performance through Monte Carlo simulations shows that the architecture gives 75% improvement in the probability of detection than the Rayleigh Channel Receiver. Finally, the real-time computing requirements for the neural network architecture are addressed and presented.

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UR - http://www.scopus.com/inward/citedby.url?scp=0028737520&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0028737520

SP - 393

EP - 403

T2 - Proceedings of the Electro'94 International Conference

Y2 - 10 May 1994 through 12 May 1994

ER -

Target detecting neural network architecture for serial sensor data streams

Abstract

Other

ASJC Scopus subject areas

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