Analysis of Switching Dynamics With Competing Support Vector Machines  

Oleh:

Chang, Ming-Wei ; Lin, Chih-Jen ; Weng, R. C.-H.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 3 (May 2004), page 720-727.
Topik: support; switching dynamics; competing support; vector machines

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We present a framework for the unsupervised segmentation of switching dynamics using support vector machines. Following the architecture by Pawelzik et al., where annealed competing neural networks were used to segment a nonstationary time series, in this paper, we exploit the use of support vector machines, a well - known learning technique. First, a new formulation of support vector regression is proposed. Second, an expectation - maximization step is suggested to adaptively adjust the annealing parameter. Results indicate that the proposed approach is promising.

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