By Marcos M Campos
This paper introduces S-TREE (Self-Organizing Tree), a kin of types that use unsupervised studying to build hierarchical representations of knowledge and on-line tree-structured vector quantizers. The S-TREE1 version, which incorporates a new tree-building set of rules. should be applied with a number of fee features. an alternate implementation. S-TREE2, which makes use of a brand new double-path seek approach, is usually constructed. The functionality of the S-TREE algorithms is illustrated with info clustering and vector quantization examples, together with a Gauss-Markov resource benchmark and a picture compression software. S-TREE functionality on those initiatives is in comparison with the normal tree-structured vector quantizer (TSVQ) and the generalized Lloyd set of rules (GLA). the picture reconstruction caliber with S-TREE2 ways that of GLA whereas taking under 10% of laptop time. S-TREE1 and S-TREE2 additionally examine favorably with the normal TSVQ in either the time had to create the codebook and the standard of picture reconstruction. c 2001 Elsevier technology Ltd. All rights reserved.
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