000 03816nam a22006015i 4500
001 978-981-97-7090-8
003 DE-He213
005 20251030114613.0
007 cr nn 008mamaa
008 241211s2024 si | s |||| 0|eng d
020 _a9789819770908
_9978-981-97-7090-8
024 7 _a10.1007/978-981-97-7090-8
_2doi
050 4 _aTJ212-225
050 4 _aTJ210.2-211.495
072 7 _aTJFM
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aTJFM
_2thema
100 1 _aJoseph, Geethu.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988795
245 1 0 _aSparsity-Constrained Linear Dynamical Systems
_h[electronic resource] :
_bFrom Compressed Sensing to Control Theory /
_cby Geethu Joseph, Chandra R. Murthy.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXVI, 98 p. 3 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Tracts in Electrical and Electronics Engineering,
_x2731-4219
505 0 _aSparsity in Linear Systems -- Sparse Initial State: Estimation Algorithms -- Sparse Initial State: Theoretical Guarantees -- Sparse Control Inputs: Algorithms -- Sparse Control Inputs: Theoretical Guarantees.
520 _aThis volume provides a comprehensive overview of recent research advances in the upcoming field of sparse control and state estimation of linear dynamical systems. The contents offer a detailed introduction to the subject by combining classical control theory and compressed sensing. It covers conceptual foundations, including the formulation, theory, and algorithms, and outlines numerous remaining research challenges. Specifically, the book provides a detailed discussion on observability, controllability, and stabilizability under sparsity constraints. It also presents efficient, systematic, and rigorous approaches to estimating the sparse initial states and designing sparse control inputs. It also gives background materials from real analysis and probability theory and includes applications in network control, wireless communication, and image processing. It serves as a compendious source for graduate students and researchers in signal processing and control systems to acquire a thorough understanding of the underlying unified themes. The academic and industrial professionals working on the design and optimization of sparsity-constrained systems also benefit from the exposure to the array of recent works on linear dynamical systems and related mathematical machinery. .
650 0 _aControl engineering.
650 0 _aRobotics.
_959148
650 0 _aAutomation.
_959149
650 0 _aComputational intelligence.
_964052
650 0 _aDynamical systems.
650 1 4 _aControl, Robotics, Automation.
650 2 4 _aComputational Intelligence.
_964052
650 2 4 _aDynamical Systems.
650 2 4 _aControl and Systems Theory.
_965868
700 1 _aMurthy, Chandra R.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988796
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819770892
776 0 8 _iPrinted edition:
_z9789819770915
776 0 8 _iPrinted edition:
_z9789819770922
830 0 _aSpringer Tracts in Electrical and Electronics Engineering,
_x2731-4219
_966106
856 4 0 _uhttps://doi.org/10.1007/978-981-97-7090-8
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c65633
_d65633