The Resource System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book)
System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book)
Resource Information
The item System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- 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
- Language
- eng
- Extent
- 1 online resource (99 p.)
- Contents
-
- Remarks and conclusion
- Introduction and Overview
- System Identification: Formulation
- Large Deviations: An Introduction
- LDP of System Identification under Independentand Identically Distributed Observation Noises
- LDP of System Identification under Mixing Observation Noises
- Applications to Battery Diagnosis
- Applications to Medical Signal Processing
- Applications to Electric Machines
- Isbn
- 9781461462927
- Label
- System identification using regular and quantized observations : applications of large deviations principles
- Title
- System identification using regular and quantized observations
- Title remainder
- applications of large deviations principles
- Statement of responsibility
- Qi He, Le Yi Wang, G. George Yin
- Language
- eng
- Summary
- 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
- Cataloging source
- EBLCP
- http://library.link/vocab/creatorName
- He, Qi
- Dewey number
-
- 003/.1
- 537.2446
- Index
- no index present
- LC call number
-
- QA402
- QC595.5
- LC item number
- .H4 2013
- Literary form
- non fiction
- Nature of contents
- dictionaries
- http://library.link/vocab/relatedWorkOrContributorDate
- 1954-
- http://library.link/vocab/relatedWorkOrContributorName
-
- Wang, Le Yi
- Yin, George
- Series statement
- SpringerBriefs in Mathematics
- http://library.link/vocab/subjectName
-
- System identification
- Signal processing
- Piezoelectric materials
- Piezoelectricity
- Pyroelectricity
- Label
- System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book)
- Contents
-
- Remarks and conclusion
- Introduction and Overview
- System Identification: Formulation
- Large Deviations: An Introduction
- LDP of System Identification under Independentand Identically Distributed Observation Noises
- LDP of System Identification under Mixing Observation Noises
- Applications to Battery Diagnosis
- Applications to Medical Signal Processing
- Applications to Electric Machines
- Control code
- SPR828302604
- Dimensions
- unknown
- Extent
- 1 online resource (99 p.)
- Form of item
- online
- Isbn
- 9781461462927
- Reproduction note
- Electronic resource.
- Specific material designation
- remote
- Label
- System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book)
- Contents
-
- Remarks and conclusion
- Introduction and Overview
- System Identification: Formulation
- Large Deviations: An Introduction
- LDP of System Identification under Independentand Identically Distributed Observation Noises
- LDP of System Identification under Mixing Observation Noises
- Applications to Battery Diagnosis
- Applications to Medical Signal Processing
- Applications to Electric Machines
- Control code
- SPR828302604
- Dimensions
- unknown
- Extent
- 1 online resource (99 p.)
- Form of item
- online
- Isbn
- 9781461462927
- Reproduction note
- Electronic resource.
- Specific material designation
- remote
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/System-identification-using-regular-and-quantized/h7Gf9w3DXG8/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/System-identification-using-regular-and-quantized/h7Gf9w3DXG8/">System identification using regular and quantized observations : applications of large deviations principles, Qi He, Le Yi Wang, G. George Yin, (electronic book)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
