System identification using regular and quantized observations: applications of large deviations principles

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System identification using regular and quantized observations: applications of large deviations principles

Yin, G. George - Nama Orang; He, Qi - Nama Orang; Wang, Le Yi - Nama Orang;

This brief presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular. By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a new perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

Ketersediaan

Perpustakaan Pusat E542

E542

Tersedia

Informasi Detail

Judul Seri: SpringerBriefs in Mathematics
No. Panggil: E542
Penerbit: New York : Springer New York., 2013
Deskripsi Fisik: xii, 95hlm.
Bahasa: English
ISBN/ISSN: 9781461462927
Klasifikasi: NONE
Tipe Isi: -
Tipe Media: computer
Tipe Pembawa: online resource
Edisi: 1
Subjek: Statistik
Prinsip deviasi
Info Detail Spesifik: -
Pernyataan Tanggungjawab: Qi He, Le Yi Wang, G. George Yin

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System identification using regular and quantized observations: applications of large deviations principles
https://doi.org/10.1007/978-1-4614-6292-7

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