LEADER 00457nam##22001337##450# 001 9910551547803321 010 $a9782728309467 100 $a########d########u##y0engy50####ba 105 0 $a########00### 200 1 $aIl governo di ogni giorno : l'amministrazione quotidiana in uno stato di antico regime (Lucca, XVII-XVIII secolo) / Matteo Giuli. 700 $aGiuli, Matteo.$0617450 912 $a9910551547803321 996 $aIl governo di ogni giorno$92432978 997 $aUNINA LEADER 03325nam 2200589 450 001 9910142025203321 005 20220715222302.0 010 $a1-118-57977-1 010 $a1-118-57974-7 010 $a1-118-57973-9 035 $a(CKB)2670000000432331 035 $a(EBL)1443829 035 $a(OCoLC)861558924 035 $a(SSID)ssj0001173036 035 $a(PQKBManifestationID)11608947 035 $a(PQKBTitleCode)TC0001173036 035 $a(PQKBWorkID)11193392 035 $a(PQKB)10017191 035 $a(MiAaPQ)EBC1443829 035 $a(Au-PeEL)EBL1443829 035 $a(CaPaEBR)ebr10780752 035 $a(PPN)178460338 035 $a(EXLCZ)992670000000432331 100 $a20131029d2013 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBlind identification and separation of complex-valued signals /$fEric Moreau, Tu?lay Adal? 210 1$aLondon :$cISTE,$d2013. 215 $a1 online resource (108 p.) 225 1 $aFocus : digital signal and image processing series,$x2051-2481 300 $aDescription based upon print version of record. 311 $a1-84821-459-6 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Contents; Preface; Acknowledgments; Chapter 1. Mathematical Preliminaries; 1.1. Introduction; 1.2. Linear mixing model; 1.3. Problem definition; 1.4. Statistics; 1.4.1. Statistics of random variables and random vectors; 1.4.2. Differential entropy of complex random vectors; 1.4.3. Statistics of random processes; 1.4.4. Complex matrix decompositions; 1.5. Optimization: Wirtinger calculus; 1.5.1. Scalar case; 1.5.2. Vector case; 1.5.3. Matrix case; 1.5.4. Summary; Chapter 2. Estimation by Joint Diagonalization; 2.1. Introduction 327 $a3.2.1. Mutual information and mutual information rate minimization3.2.2. Maximum likelihood; 3.2.3. Identifiability of the complex ICA model; 3.3. Algorithms; 3.3.1. ML ICA: unconstrained W; 3.3.2. Complex maximization of non-Gaussianity: ML ICA with unitary W; 3.3.3. Density matching; 3.3.4. A flexible complex ICA algorithm: Entropy bound minimization; 3.4. Summary; Bibliography; Index 330 $aBlind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources - underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebra 410 0$aDigital signal and image processing series. 606 $aSignal processing$xStatistical methods 615 0$aSignal processing$xStatistical methods. 676 $a108 700 $aMoreau$b Eric$0958804 701 $aAdali$b Tu?lay$0845678 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910142025203321 996 $aBlind identification and separation of complex-valued signals$92897840 997 $aUNINA LEADER 04939oam 22006134a 450 001 996517768103316 005 20210915050341.0 010 $a1-5292-1265-0 035 $a(CKB)5590000000448399 035 $a(OCoLC)1247679421 035 $a(MdBmJHUP)muse98382 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/64096 035 $a(DE-B1597)645924 035 $a(DE-B1597)9781529212655 035 $a(MiAaPQ)EBC6551833 035 $a(Au-PeEL)EBL6551833 035 $a(EXLCZ)995590000000448399 100 $a20210424d2021 uy 0 101 0 $aeng 135 $aur|||||||nn|n 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEmotion and Proactivity at Work$eProspects and Dialogues 205 $a1st ed. 210 $aBristol$cBristol University Press$d2021 210 1$aBristol :$cBristol University Press,$d2021. 210 4$dİ2021. 215 $a1 online resource (1 online resource 350 p.) 300 $aEffects of work versus non-work events on affect, motivation, and proactive behaviour. 300 $aDescription based upon print version of record. 311 $a1-5292-0830-0 327 $aVigour and the energized-to pathway -- Dedication and the reason-to pathway -- Absorption and the can-do pathway -- Linking work engagement to proactivity -- Conclusion -- Implications and future directions -- Summary -- References -- Part II The Role of Emotion in Shaping Proactivity in Different Contexts -- 3 A Multilevel Model of Emotions and Proactive Behaviour -- The Five-Level Model of Emotions in the Workplace -- Level 1: Within person -- Level 2: Between-persons -- Level 3: Interpersonal relationships -- Level 4: Groups and teams -- Level 5: The organization as a whole 327 $aA conceptual focus on core affect -- The role of positive emotional states -- The role of negative emotional states -- The role of work engagement -- Limitations of current conceptualizations of energized-to proactive motivation -- Ways forward: Clarifying the energized-to pathway -- Focusing on discrete emotions -- How: Identifying different effects on the form or stage of proactivity -- When: Focusing on contingent factors linking negative emotions to proactivity -- Clarifying how work engagement shapes proactivity -- Engagement as more than an energized-to state 327 $aQualitative-based review on highly relevant and frequently cited papers -- Theoretical lenses in the affect-proactivity link -- Positive and negative affect and proactivity -- Proactive work behaviours -- Proactive personal-environment fit behaviours -- Discrete emotions and proactivity -- Proactive work behaviour -- The emotional consequences of proactivity -- Emotional regulation and proactivity -- A short outlook -- Conclusion -- Future research -- Notes -- References -- 2 Igniting Initiative -- Current conceptualizations of energized-to proactive motivation -- Defining affect 327 $aFront Cover -- Emotion and Proactivity at Work: Prospects and Dialogues -- Copyright information -- Table of contents -- List of Figures and Tables -- Notes on Contributors -- Acknowledgments -- Foreword -- Emotion and Proactivity at Work: Where Are We Now? -- Part I Emotion and Proactivity -- Why and How It Matters -- 1 Feeling Energized to Become Proactive -- A quantitative-based review of the affect-proactivity link -- Sample and procedure -- Affect-proactive work behaviour link -- Affect-proactive person-environment fit behaviour link 330 $aIn this pioneering work, expert scholars offer new thinking on proactivity by examining how emotion can drive employees' proactivity in the workplace and how, in turn, that proactivity can shape one's emotional experiences. 330 $aOf the five levels -- A multilevel model of emotions and proactivity -- The dynamic nature of the FLMEW -- The interactive nature of the FLMEW -- Future research -- Conclusion -- References -- 4 Affective Events and Proactivity -- Affective events theory -- Affective events and proactive behaviour: overview of previous research -- Effects of Positive Versus Negative Work Events on Affect, Motivation, and Proactive Behaviour -- Effects of task versus interpersonal work events on affect, motivation, and proactive behaviour. 606 $aEmotions 606 $aEmployee motivation 606 $aPsychology, Industrial 608 $aElectronic books. 610 $aAffective tone; Discrete emotion; Energy; Organizational behaviour; Proactive behaviour; Proactivity; Well-being 615 0$aEmotions. 615 0$aEmployee motivation. 615 0$aPsychology, Industrial. 700 $aPeng$b Kelly Z$0951476 701 $aWu$b Chia-Huei$0951477 801 0$bMdBmJHUP 801 1$bMdBmJHUP 906 $aBOOK 912 $a996517768103316 996 $aEmotion and Proactivity at Work$92151038 997 $aUNISA