Abstract
A novel reconstruction algorithm of order parameters based on Immunity Clonal Strategy (ICS) is presented in this paper, which combines the self-learning ability of Synergetic Neural Network (SNN) with the global searching performance of ICS to construct linear transform and then realize reconstruction. Compared with the reconstruction method based on Genetic Algorithm (GA), the new method not only overcomes the aimless and random searching of GA at the later time of searching but also improves its searching efficiency greatly. The tests on IRIS data and Brodatz texture show that the proposed method can positively find a new set of reconstruction parameters and enhance the classification accuracy rate remarkably.
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Ma, X., Jiao, L. (2004). Reconstruction of Order Parameters Based on Immunity Clonal Strategy for Image Classification. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_57
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DOI: https://doi.org/10.1007/978-3-540-30125-7_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
Online ISBN: 978-3-540-30125-7
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