To improve sonar performance in shallow water, a novel method for target localization based on a statistical learning theory's recognizer was proposed. 摘要為了提高聲納在淺水域的性能，提出了一種基于統計學(xué)習理論的目標識別器的目標定位方法。
Through SVM can perfectly solve the problem of small sample learning, it fails to make use of the unlabelled samples of data. 針對這種情況，本文首先研究了支持向量機的基本原理和算法，指出支持向量機是一種基于統計學(xué)習理論的通用學(xué)習算法，能夠較好地解決小樣本學(xué)習問(wèn)題。
