Verfügbarkeit: Emotional Intelligence | Technische Universität München

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Bibliographische Detailangaben
Beteiligte Personen:	Chakraborty, Aruna (VerfasserIn), Konar, Amit (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	Englisch
Veröffentlicht:	Berlin Springer Berlin 2009
Ausgabe:	1. Aufl.
Schriftenreihe:	Studies in Computational Intelligence 234
Schlagwörter:	Mathematisches Modell Emotional intelligence Emotions > Mathematical models Emotions > Measurement Multimodales System Intelligenz Kybernetisches Modell Gefühl Mensch-Maschine-Kommunikation Affective Computing
Links:	https://doi.org/10.1007/978-3-540-68609-5 https://doi.org/10.1007/978-3-540-68609-5 https://doi.org/10.1007/978-3-540-68609-5 https://doi.org/10.1007/978-3-540-68609-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018673569&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	1 Online-Ressource (340 S.)
ISBN:	9783540686095
DOI:	10.1007/978-3-540-68609-5

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Datensatz im Suchindex

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adam_text	CONTENTS 1 INTRODUCTION TO EMOTIONAL INTELLIGENCE 1 1.1 WHAT IS EMOTIONAL INTELLIGENCE? 1 1.2 CAUSES OF EMOTIONS 4 1.3 TYPICAL CHARACTERISTICS OF EMOTION 4 1.4 BASIC COMPONENTS OF EMOTION 5 1.4.1 THE COGNITIVE COMPONENT 6 1.4.2 THE EVALUATIVE COMPONENT 6 1.4.3 THE MOTIVATIONAL COMPONENT 6 1.4.4 THE FEELING COMPONENT 6 1.5 RATIONALITY OF EMOTION 7 1.6 REGULATION AND CONTROL OF EMOTION 8 1.7 THE BIOLOGICAL BASIS OF EMOTION 10 1.7.1 AN AFFECTIVE NEURO SCIENTIFIC MODEL 11 1.8 SELF REGULATION MODELS OF EMOTION 13 1.9 EMOTIONAL LEARNING 17 1.10 MATHEMATICAL MODELING OF EMOTIONAL DYNAMICS 18 1.11 CONTROLLING EMOTION BY ARTIFICIAL MEANS 21 1.12 EFFECT OF EMOTION MODELING ON HUMAN MACHINE INTERACTIONS 22 1.13 SCOPE OF THE BOOK 23 1.14 SUMMARY 25 REFERENCES 31 2 MATHEMATICAL MODELING AND ANALYSIS OF DYNAMICAL SYSTEMS 35 2.1 INTRODUCTION 35 2.2 SYSTEM MODELING AND STABILITY 36 2.3 STABILITY ANALYSIS OF DYNAMICS BY LYAPUNOV ENERGY FUNCTIONS 40 2.3.1 STABILITY ANALYSIS FOR CONTINUOUS DYNAMICS 42 2.4 STABILITY ANALYSIS OF FUZZY SYSTEMS 45 2.4.1 MAMDANI TYPE FUZZY SYSTEMS 45 2.4.2 TAKAGI-SUGENO TYPE FUZZY SYSTEMS 46 2.4.3 STABILITY ANALYSIS OF *-S FUZZY SYSTEMS 48 2.5 CHAOTIC NEURO DYNAMICS AND LYAPUNOV EXPONENTS 52 2.6 EMOTIONAL DYNAMICS AND STABILITY ANALYSIS 54 2.7 THE LYAPUNOV EXPONENTS AND THE CHAOTIC EMOTIONAL DYNAMICS.... 55 REFERENCE BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/994783310 DIGITALISIERT DURCH XII CONTENTS 3 PRELIMINARIES ON IMAGE PROCESSING 63 3.1 INTRODUCTION 63 3.2 DISCRETE FOURIER AND COSINE TRANSFORMS 64 3.3 PREPROCESSING AND NOISE FILTERING 66 3.3.1 NEIGHBORHOOD AVERAGING 66 3.3.2 MEDIAN FILTERING 66 3.3.3 THRESHOLDING 67 3.4 IMAGE SEGMENTATION ALGORITHMS 69 3.4.1 BOUNDARY DETECTION ALGORITHMS 69 3.4.2 REGION ORIENTED SEGMENTATION ALGORITHM 75 3.4.2.1 REGION GROWING BY PIXEL AGGREGATION 76 3.4.2.2 REGIONS SPLITTING AND MERGING 76 3.4.2.3 IMAGE SEGMENTATION BY FUZZY CLUSTERING 77 3.5 BOUNDARY DESCRIPTION 84 3.5.1 CHAIN CODES 84 3.5.2 FOURIER DESCRIPTORS 86 3.5.3 REGIONAL DESCRIPTORS 86 3.6 OBJECT RECOGNITION FROEMAN IMAGE 87 3.6.1 UNSUPERVISED CLUSTERING 87 3.6.2 SUPERVISED CLASSIFICATION 88 3.6.3 IMAGE MATCHING 88 3.6.4 TEMPLATE MATCHING 89 3.7 SCENE INTERPRETATION 90 3.8 CONCLUSIONS 91 REFERENCES 91 4 BRAIN IMAGING AND PSYCHO-PATHOLOGICAL STUDIES ON SELF-REGULATION OF EMOTION 93 4.1 INTRODUCTION 93 4.2 EMOTION PROCESSING BY THE HUMAN BRAIN 94 4.2.1 THE AMYGDALE 94 4.2.2 ANIMAL STUDIES ON AMYGDALE 94 4.2.3 FEAR AND THREAT PERCEPTION OF THE AMYGDALE 95 4.2.4 THE ORBITOFRONTAL CORTEX (OFC) 96 4.2.5 ANIMAL LESIONS TO PREFRONTAL OFC 96 4.2.6 NEURO-PSYCHOLOGY AND FUNCTIONAL NEURO-IMAGING STUDIES ON OFC BEHAVIOR 96 4.2. CONTENTS XIII 4.5.3 NEURAL CIRCUITRY UNDERLYING EMOTIONAL SELF-REGULATION 103 4.6 EEG CONDITIONING AND AFFECTIVE DISORDERS 104 4.6.1 PAIN CONDITIONING IN RATS 105 4.6.2 CLINICAL STUDY OF DEPRESSION USING EEG 106 4.6.3 EEG ANALYSIS FOR PREMENSTRUAL DYSPHORIC DISORDER 106 4.7 EMOTION DYSREGULATION AND PSYCHO-PATHOLOGICAL ISSUES 107 4.7.1 EMOTINAL DYSREGULATION IN CHILDHOOD FROM NON-CLINICAL SAMPLES 107 4.7.2 CLINICAL SAMPLES FOR EMOTIONAL DYSREGULATION FOR CHILDREN 108 4.7.3 EMOTION REGULATION IN ADULTHOOD 109 4.7.3.1 NON-CLINICAL STUDIES 109 4.7.3.2 CLINICAL STUDIES 110 4.8 CONCLUSIONS 110 REFERENCES 124 FUZZY MODELS FOR FACIAL EXPRESSION-BASED EMOTION RECOGNITION AND CONTROL 133 5.1 INTRODUCTION 133 5.2 FILTERING, SEGMENTATION AND LOCALIZATION OF FACIAL COMPONENTS 135 5.2.1 SEGMENTATION OF THE MOUTH REGION 136 5.2.2 SEGMENTATION OF THE EYE-REGION 137 5.2.3 SEGMENTATION OF THE EYEBROW CONSTRICTION 139 5.3 DETERMINATION OF FACIAL ATTRIBUTES 139 5.3.1 DETERMINATION OF THE MOUTH-OPENING 139 5.3.2 DETERMINATION OF THE EYE-OPENING 139 5.3.3 DETERMINATION OF THE LENGTH OF EYEBROW-CONSTRICTION 139 5.4 FUZZY RELATIONAL MODEL FOR EMOTION DETECTION 141 5.4.1 FUZZIFICATION OF FACIAL ATTRIBUTES 141 5.4.2 THE FUZZY RELATIONAL MODEL FOR EMOTION DETECTION 141 5.5 EXPERIMENTS AND RESULTS 144 5.6 VALIDATION OF THE SYSTEM PERFORMANCE 152 5. XIV CONTENTS 6.2.1 FINDING COMMON INTERPRETATIONS OF PREPOSITIONAL STATEMENTS 177 6.2.2 DETERMINING STABLE POINTS OF LOGICAL STATEMENTS 179 6.3 STABLE POINTS IN PROPOSITIONAL TEMPORAL LOGIC 180 6.4 STABILITY OF PROPOSITIONAL TEMPORAL SYSTEM USING LYAPUNOV ENERGY FUNCTION 183 6.4.1 THE LYAPUNOV ENERGY FUNCTION 183 6.4.2 STABILITY ANALYSIS OF PROPOSITIONAL TEMPORAL SYSTEM 183 6.5 HUMAN EMOTION MODELING AND STABILITY ANALYSIS 185 6.5.1 STABILITY ANALYSIS OF THE EMOTIONAL DYNAMICS 186 6.5.2 WEIGHT ADAPTATION IN EMOTION DYNAMICS BY HEBBIAN LEARNING 189 6.5.3 IMPROVING RELATIVE STABILITY OF THE LEARNING DYNAMICS 190 6.6 THE FUZZY TEMPORAL REPRESENTATION OF PHENOMENA INVOLVING EMOTIONAL STATES 190 6.7 STABILIZATION OF EMOTIONAL DYNAMICS 194 6.8 PSYCHOLOGICAL STABILITY IN EMOTION-LOGIC COUNTER-ACTIONS 195 6.9 CONCLUSIONS 197 REFERENCES 207 7 MULTIPLE EMOTIONS AND THEIR CHAOTIC DYNAMICS 209 7.1 INTRODUCTION 209 7.2 PROPOSED MODEL FOR CHAOTIC EMOTIONAL DYNAMICS 210 7.3 EFFECT OF VARIATION IN PARAMETERS OF THE EMOTIONAL DYNAMICS 212 7.3.1 VARIATION IN A 212 7.3.2 VARIATION IN CIJ 214 7.3.3 VARIATIONOFBY 215 7.4 CHAOTIC FLUCTUATION IN EMOTIONAL STATE 217 7.5 STABILITY ANALYSIS OF THE PROPOSED EMOTIONAL DYNAMICS BY LYAPUNOV ENERGY FUNCTION 219 7.6 PARAMETER SELECTION OF THE EMOTIONAL DYNAMICS BY EXPERIMENTS WITH AUDIO-VISUAL STIMULUS 220 7. CONTENTS XV 8.4 BIO-POTENTIAL SIGNALS IN EMOTION PREDICTION 252 8.4.1 PRINCIPLES IN SVM 253 8.5 EMOTION CLUSTERING BY NEURAL NETWORKS 256 8.6 CONCLUSIONS 259 REFERENCES 259 9 APPLICATIONS AND FUTURE DIRECTIONS OF EMOTIONAL INTELLIGENCE 261 9.1 INTRODUCTIONS 261 9.2 APPLICATION IN HUMAN-MACHINE INTERACTIVE SYSTEMS 263 9.2.1 INPUT INTERFACES 263 9.2.2 OUTPUT INTERFACES 263 9.2.3 EMBODIMENT OF ARTIFICIAL CHARACTERS 264 9.3 APPLICATION IN MULTI-AGENT CO-OPERATION OF MOBILE ROBOTICS 265 9.4 EMOTIONAL INTELLIGENCE IN PSYCHO-THERAPY 266 9.5 DETECTION OF ANTI-SOCIAL MOTIVES FROM EMOTIONAL EXPRESSIONS 267 9.6 APPLICATIONS IN VIDEO PHOTOGRAPHY/MOVIE MAKING 269 9.7 APPLICATIONS IN PERSONALITY MATCHING OF PEOPLE FOR MATRIMONIAL COUNSELING 270 9.8 SYNTHESIZING EMOTIONS IN VOICE 271 9.9 APPLICATION IN USER ASSISTANCE SYSTEMS 272 9.10 EMOTION RECOGNITION FROM VOICE SAMPLES 273 9.10.1 SPEECH ARTICULATORY FEATURES 273 9.11 PERSONALITY BUILDING OF ARTIFICIAL CREATURES 275 9.12 MULTIMODAL EMOTION RECOGNITION 277 9.12.1 CURRENT STATUS 277 9.12.2 RESEARCH INITIATIVE AT JADAVPUR UNIVERSITY 278 9.13 PARAMETER IDENTIFICATION OF EMOTIONAL DYNAMICS USING EEG AND FMRI BRAIN IMAGING 283 9.13.1 SYSTEM IDENTIFICATION APPROACH TO EEG DYNAMICS MODELING BY EVOLUTIONARY ALGORITHMS 283 9.13.2 GENETIC ALGORITHM IN EMOTIONAL SYSTEM IDENTIFICATION 285 9.13.3 PARTICLE SWARM OPTIMIZATION IN EMOTIONAL SYSTEM IDENTIFICATIO XVI CONTENTS 10.4.2 ARTIFICIAL CONTROL OF EMOTION BY TAKAGI-SUGENO METHOD 299 10.4.3 DETERMINING MANIFESTATION OF EMOTION ON FACIAL EXPRESSION FROM EEG SIGNALS 299 10.5 FURTHER READINGS FOR RESEARCHERS 300 REFERENCES 301 APPENDIX 305 AUTHOR S BIOGRAPHY 319 SUBJECT INDEX 321
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id	DE-604.BV035814710
illustrated	Not Illustrated
indexdate	2024-12-20T14:00:48Z
institution	BVB
isbn	9783540686095
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-018673569
oclc_num	873617107
open_access_boolean
owner	DE-898 DE-BY-UBR DE-634 DE-92 DE-83
owner_facet	DE-898 DE-BY-UBR DE-634 DE-92 DE-83
physical	1 Online-Ressource (340 S.)
psigel	ZDB-2-ENG
publishDate	2009
publishDateSearch	2009
publishDateSort	2009
publisher	Springer Berlin
record_format	marc
series	Studies in Computational Intelligence
series2	Studies in Computational Intelligence
spellingShingle	Chakraborty, Aruna Konar, Amit Emotional Intelligence A Cybernetic Approach Studies in Computational Intelligence Mathematisches Modell Emotional intelligence Emotions Mathematical models Emotions Measurement Multimodales System (DE-588)4830853-5 gnd Intelligenz (DE-588)4027251-5 gnd Kybernetisches Modell (DE-588)4324238-8 gnd Gefühl (DE-588)4019702-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Affective Computing (DE-588)4784306-8 gnd
subject_GND	(DE-588)4830853-5 (DE-588)4027251-5 (DE-588)4324238-8 (DE-588)4019702-5 (DE-588)4125909-9 (DE-588)4784306-8
title	Emotional Intelligence A Cybernetic Approach
title_auth	Emotional Intelligence A Cybernetic Approach
title_exact_search	Emotional Intelligence A Cybernetic Approach
title_full	Emotional Intelligence A Cybernetic Approach Aruna Chakraborty ; Amit Konar
title_fullStr	Emotional Intelligence A Cybernetic Approach Aruna Chakraborty ; Amit Konar
title_full_unstemmed	Emotional Intelligence A Cybernetic Approach Aruna Chakraborty ; Amit Konar
title_short	Emotional Intelligence
title_sort	emotional intelligence a cybernetic approach
title_sub	A Cybernetic Approach
topic	Mathematisches Modell Emotional intelligence Emotions Mathematical models Emotions Measurement Multimodales System (DE-588)4830853-5 gnd Intelligenz (DE-588)4027251-5 gnd Kybernetisches Modell (DE-588)4324238-8 gnd Gefühl (DE-588)4019702-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Affective Computing (DE-588)4784306-8 gnd
topic_facet	Mathematisches Modell Emotional intelligence Emotions Mathematical models Emotions Measurement Multimodales System Intelligenz Kybernetisches Modell Gefühl Mensch-Maschine-Kommunikation Affective Computing
url	https://doi.org/10.1007/978-3-540-68609-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018673569&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV020822171
work_keys_str_mv	AT chakrabortyaruna emotionalintelligenceacyberneticapproach AT konaramit emotionalintelligenceacyberneticapproach

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