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Bibliographic Details
Main Authors:	Chakraborty, Aruna (Author), Konar, Amit (Author)
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2009
Series:	Studies in computational intelligence 234
Subjects:	Mathematisches Modell Emotional intelligence Emotions > Mathematical models Emotions > Measurement Multimodales System Gefühl Kybernetisches Modell Intelligenz Affective Computing Mensch-Maschine-Kommunikation
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018721458&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Physical Description:	XVI, 326 S. Ill., graph. Darst. 235 mm x 155 mm
ISBN:	9783540686064 9783540686095

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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 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 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 Т -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 References ......................................................................... 60 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 from an 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 Studieson 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 4.2.7 The Insula ...................................................................... 97 4.2.8 Experiment of Selective Lesion of Insula Cortex ............... 97 4.2.9 The Anterior Cingulated ..................................................... 97 4.2.10 Emotion Monitoring by the Cingulated Cortex ................· 98 4.3 The Role of Medial Frontal Cortex in Self-regulation of Emotion... 99 4.4 The Anterior Cingulate Cortex as a Self-regulatory Agent ............ 99 4.5 Voluntary Self-regulation of Emotion .......................................... 101 4.5.1 fMRI Studies on Voluntary Regulation of Sexual Arousals... 102 4.5.2 Voluntary Regulation of Sadness in Adults ..................... 103 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 ExperimentsandResults .................................................... 144 5.6 Validation of the System Performance ................................... 152 5.7 Proposed Model of Emotion Transition and Its Control ............... 153 5.7.1 The Model ............................................................ 153 5.7.2 Properties of the Model ............................................. 155 5.7.3 Emotion Control by Mamdani s Model .......................... 157 5.7.4 Architecture of the Proposed Emotion Control Scheme ....... 163 5.7.5 Experiments and Results ............................................ 163 5.8 Conclusions ................................................................... 166 References ........................................................................... 171 Control of Mental Stability in Emotion-Logic Interactive Dynamics ..................................................................................... 175 6.1 Introduction ................................................................... 175 6.2 Stable Points of Non-temporal Logic .................................... 176 XIV Contents 6.2.1 Finding Common Interpretations of Propositional 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 су ....................................................... 214 7.3.3 Variation of by ....................................................... 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 7.7 A Stabilization Scheme for the Mixed Emotional Dynamics ......... 226 7.8 Conclusions .................................................................. 228 References .......................................................................... 232 8 Electroencephalographic Signal Processing for Detection and Prediction of Emotion ........................................................... 235 8.1 Introduction .................................................................. 235 8.2 EEG Prediction by Adaptive Filtering .................................... 236 8.2.1 LMS Filter ............................................................ 237 8.2.2 EEG Prediction by NLMS Algorithm ........................... 238 8.2.3 The RLS Filter for EEG Prediction .............................. 240 8.2.4 The Kalman Filter for EEG Prediction ........................... 242 8.2.5 Implication of the Results .......................................... 245 8.3 EEG Signal Prediction by Wavelet Coefficients ........................ 247 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 Identification ...................................................... 286 9.13.4 Differential Evolution Algorithm in Emotional System Identification ...................................................... 289 9.14 Conclusions .................................................................. 290 References .......................................................................... 291 10 Open Research Problems ........................................................ 295 10.1 Introduction ................................................................................ 295 10.2 Reasoning with Emotions ................................................. 297 10.3 Uncertainty Management in Emotion-Based Reasoning .............. 298 10.4 Selected Open Problems ................................................................... 299 10.4.1 Multi-modal Emotion Recognition ............................... 299 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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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 Gefühl (DE-588)4019702-5 gnd Kybernetisches Modell (DE-588)4324238-8 gnd Intelligenz (DE-588)4027251-5 gnd Affective Computing (DE-588)4784306-8 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd
subject_GND	(DE-588)4830853-5 (DE-588)4019702-5 (DE-588)4324238-8 (DE-588)4027251-5 (DE-588)4784306-8 (DE-588)4125909-9
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 and Amit Konar
title_fullStr	Emotional intelligence a cybernetic approach Aruna Chakraborty and Amit Konar
title_full_unstemmed	Emotional intelligence a cybernetic approach Aruna Chakraborty and 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 Gefühl (DE-588)4019702-5 gnd Kybernetisches Modell (DE-588)4324238-8 gnd Intelligenz (DE-588)4027251-5 gnd Affective Computing (DE-588)4784306-8 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd
topic_facet	Mathematisches Modell Emotional intelligence Emotions Mathematical models Emotions Measurement Multimodales System Gefühl Kybernetisches Modell Intelligenz Affective Computing Mensch-Maschine-Kommunikation
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018721458&sequence=000002&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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Call Number:	0002 PSY 330f 2010 A 2601
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