Source Localization with Network Inversion Using an Answer-in-Weights Scheme

Takehiko OGAWA; Keisuke KAMEYAMA; Roman KUC; Yukio KOSUGI

Source Localization with Network Inversion Using an Answer-in-Weights Scheme

Takehiko OGAWA, Keisuke KAMEYAMA, Roman KUC, Yukio KOSUGI

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A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.

Publication: IEICE TRANSACTIONS on Information Vol.E79-D No.5 pp.608-619

Publication Date: 1996/05/25

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Type of Manuscript: PAPER

Category: Bio-Cybernetics and Neurocomputing

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Takehiko OGAWA, Keisuke KAMEYAMA, Roman KUC, Yukio KOSUGI, "Source Localization with Network Inversion Using an Answer-in-Weights Scheme" in IEICE TRANSACTIONS on Information, vol. E79-D, no. 5, pp. 608-619, May 1996, doi: .
Abstract: A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.
URL: https://globals.ieice.org/en_transactions/information/10.1587/e79-d_5_608/_p

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@ARTICLE{e79-d_5_608,
author={Takehiko OGAWA, Keisuke KAMEYAMA, Roman KUC, Yukio KOSUGI, },
journal={IEICE TRANSACTIONS on Information},
title={Source Localization with Network Inversion Using an Answer-in-Weights Scheme},
year={1996},
volume={E79-D},
number={5},
pages={608-619},
abstract={A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.},
keywords={},
doi={},
ISSN={},
month={May},}

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TY - JOUR
TI - Source Localization with Network Inversion Using an Answer-in-Weights Scheme
T2 - IEICE TRANSACTIONS on Information
SP - 608
EP - 619
AU - Takehiko OGAWA
AU - Keisuke KAMEYAMA
AU - Roman KUC
AU - Yukio KOSUGI
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 1996
AB - A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.
ER -