:: eBooks :: Kembali

eBooks :: Kembali

Hidden Markov models and dynamical systems

Andrew M. Fraser (Society for Industrial and Applied Mathematics, 2008)

 Abstrak

Hidden Markov models (HMMs) are discrete-state, discrete-time, stochastic dynamical systems. They are often used to approximate systems with continuous state spaces operating in continuous time. In addition to introducing the basic ideas of HMMs and algorithms for using them, this book explains the derivations of the algorithms with enough supporting theory to enable readers to develop their own variants. The book also presents Kalman filtering as an extension of ideas from basic HMMs to models with continuous state spaces.
Although applications of HMMs have become numerous (396,000 Google hits) since they emerged as the key technology for speech recognition in the 1980s, no introductory book on HMMs in general is available. This text aims to fill that gap.
Hidden Markov Models and Dynamical Systems features illustrations that use the Lorenz system, laser data, and natural language data. The concluding chapter presents the application of HMMs to detecting sleep apnea in experimentally measured electrocardiograms. Algorithms are given in pseudocode in the text, and a working implementation of each algorithm is available on the accompanying website.

 File Digital: 1

Shelf
 Hidden Markov models and dynamical systems.pdf :: Unduh

LOGIN required

 Metadata

No. Panggil : e20450784
Entri utama-Nama orang :
Subjek :
Penerbitan : Philadelphia: Society for Industrial and Applied Mathematics, 2008
Sumber Pengatalogan: LibUI eng rda
Tipe Konten: text
Tipe Media: computer
Tipe Pembawa: online resources
Deskripsi Fisik: xii, 132 pages : illustration
Tautan: http://portal.igpublish.com/iglibrary/search/SIAMB0000362.main.html?5
Lembaga Pemilik:
Lokasi:
  • Ketersediaan
  • Ulasan
No. Panggil No. Barkod Ketersediaan
e20450784 02-17-750870344 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 20450784