AFIT neural network research

Rogers S.K.; Ruck D.W.

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AFIT neural network research

机译：AFIT神经网络研究

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A brief summary of research done at the Air Force Institute of Technology (AFIT) in the area of neural networks is provided. It has been shown that backpropagation, used for feedforward artificial neural networks, is just a degenerate version of an extended Kalman filter, and that networks can do about as well as the optimum statistical classification technique. A method of finding the importance of features for use by a neural network classifier has been determined. Techniques for using neural networks for image segmentation have been developed. In optical pattern recognition, techniques that allow the processing of real FLIR (forward-looking infrared) images with existing binary spatial light modulators have been devised. An optical direction of arrival detector applicable to laser illumination direction determination has been designed and tested; the design is similar to a fly's eye. Coated mirrors for the optical confocal Fabry-Perot interferometer have been designed, specified, fabricated, and installed. Significant progress has been made in the use of neural networks for processing multiple-feature sets for speech recognition.

机译：提供了在空军技术学院（AFIT）进行的神经网络领域研究的简短摘要。已经表明，用于前馈人工神经网络的反向传播只是扩展卡尔曼滤波器的退化版本，并且网络可以和最佳的统计分类技术相媲美。已经确定了一种找到由神经网络分类器使用的特征的重要性的方法。已经开发出使用神经网络进行图像分割的技术。在光学图案识别中，已经设计出允许使用现有的二进制空间光调制器处理真实的FLIR（前视红外）图像的技术。设计并测试了适用于激光照射方向确定的光到达方向检测器；设计类似于苍蝇的眼睛。用于光学共焦法布里-珀罗干涉仪的镀膜镜已被设计，指定，制造和安装。在使用神经网络处理语音识别的多特征集方面已经取得了重大进展。

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《IEEE Aerospace and Electronic Systems Magazine》 |1990年第9期|P.17-19|共3页
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Rogers S.K.; Ruck D.W.;
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AFIT neural network research

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