12 October 1988 Vector Quantization Training By A Self-Organizing Neural Network
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Abstract
This paper presents work in progress on the application of a self-organizing neural network to vector quantization (VQ) training. A modified version of Kohonen's self-organizing feature map algorithm was applied to simulated data and to digitized Synthetic Aperture Radar image data. Preliminary results indicate that the network-based algorithm is potentially more robust than the traditional LBG training algorithm, especially when confronted with multimodal input data distributions.
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Thomas W Ryan, Thomas W Ryan, Charles A Cotter, Charles A Cotter, } "Vector Quantization Training By A Self-Organizing Neural Network", Proc. SPIE 0924, Recent Advances in Sensors, Radiometry, and Data Processing for Remote Sensing, (12 October 1988); doi: 10.1117/12.945700; https://doi.org/10.1117/12.945700
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