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200524s2020 enk o 001 0 eng d |
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|a YDX
|b eng
|e pn
|c YDX
|d OPELS
|d OCLCF
|d UKMGB
|d EBLCP
|d NLE
|d OCLCO
|d OCLCA
|d OCLCO
|d OCLCQ
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|a GBC036838
|2 bnb
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|a 019738505
|2 Uk
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|a 9780128212486
|q (electronic bk.)
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|a 0128212489
|q (electronic bk.)
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|z 9780128212479
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|z 0128212470
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|a (OCoLC)1155163035
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|a TA1638
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|a 621.382/2
|2 23
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|a Compressive sensing in health care /
|c edited by Mahdi Khosravy, Nilanjan Dey, Carlos A. Duque.
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|a London :
|b Academic Press,
|c 2020.
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|a 1 online resource
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Advances in ubiquitous sensing applications for healthcare
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|a Includes index.
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|a Front Cover -- Compressive Sensing in Healthcare -- Copyright -- Contents -- List of contributors -- 1 Compressive sensing theoretical foundations in a nutshell -- 1.1 Introduction -- 1.2 Digital signal acquisition -- 1.3 Vectorial representation of signal -- l1 norm -- l2 norm -- l norm -- Spheres made by different lp norms as distance criterion -- Basis/dictionary -- Orthonormal basis/dictionary -- Frame/ over-complete dictionary -- Alternate/dual frame -- 1.4 Sparsity -- k-sparse signal -- Non-linearity of sparsity -- Sparsity and compressibility -- 1.5 Compressive sensing
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|a Compressive sensing model -- 1.6 Essential properties of compressive sensing matrix -- 1.6.1 Null space property (NSP) -- The essence of the concept of recovery -- Maximum compression in compressive sensing (lower bound of m) -- 1.6.2 Restricted isometry property -- 1.6.3 Coherence a simple way to check NSP -- Relation between coherence and spark of a matrix -- Coherence approach to RIP -- 1.7 Summary -- 1.A -- Null space property of order 2k -- References -- 2 Recovery in compressive sensing: a review -- 2.1 Introduction -- 2.1.1 Compressive sensing formulation
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|a 2.2 Criteria required for a compressive sensing matrix -- 2.2.1 Null space property -- Null space property of order k -- 2.2.1.1 Uniqueness theorem [46] -- Maximum compression in compressive sensing -- 2.2.2 Restricted isometry property -- 2.2.3 Coherence property -- 2.2.3.1 Coherence and spark of a matrix -- 2.2.3.2 The upper bound of sparsity level -- 2.3 Recovery -- 2.3.1 Recovery via minimization of l1 norm -- 2.3.2 Greedy algorithms -- 2.3.2.1 Pursuits -- 2.3.2.2 Matching pursuit -- 2.3.2.3 Orthogonal matching pursuit -- 2.3.2.4 Iterative hard thresholding -- 2.4 Summary -- References
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|a Measure SGini -- 3.5 Summary -- References -- 4 Compressive sensing in practice and potential advancements -- 4.1 Introduction -- 4.2 Compressive sensing theory -- 4.3 Example compressive sensing implementations -- 4.3.1 Compressive sensing in physiological signal monitoring -- In the eld application results -- 4.3.2 Compressive sensing in THEMIS imaging -- In-the- eld application results -- 4.4 Review of CS literature -- 4.4.1 Practical manifestations of theoretical bounds -- 4.5 Advancements in compressive sensing -- 4.5.1 Personalized basis -- Challenges
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|a The focus of the book is on healthcare applications for this technology. --
|c Edited summary from book.
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650 |
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|a Compressed sensing (Telecommunication)
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650 |
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|a Medical innovations.
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1 |
2 |
|a Biosensing Techniques
|0 (DNLM)D015374
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650 |
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|a Acquisition comprim�ee.
|0 (CaQQLa)000299156
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650 |
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|a M�edecine
|x Innovations.
|0 (CaQQLa)201-0046524
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650 |
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7 |
|a Compressed sensing (Telecommunication)
|2 fast
|0 (OCoLC)fst01921915
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650 |
|
7 |
|a Medical innovations
|2 fast
|0 (OCoLC)fst01014181
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700 |
1 |
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|a Khosravy, Mahdi.
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700 |
1 |
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|a Dey, Nilanjan,
|d 1984-
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700 |
1 |
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|a Duque, Carlos A.
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776 |
0 |
8 |
|i Ebook version :
|z 9780128212486
|
776 |
0 |
8 |
|i Print version:
|t Compressive sensing in health care.
|d London : Academic Press, 2020
|z 0128212470
|z 9780128212479
|w (OCoLC)1122451466
|
830 |
|
0 |
|a Advances in ubiquitous sensing applications for healthcare.
|
856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128212479
|z Texto completo
|