Studies in Computational Intelligence

A Cybernetic Approach

By: Aruna Chakraborty, Amit Konar

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Hardcover | 11 November 2009

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344 Pages

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Emotional Intelligence is a new discipline of knowledge, dealing with modeling, recognition and control of human emotions. The book Emotional Intelligence: A Cybernetic Approach, to the best of the authors' knowledge is a first compreh- sive text of its kind that provides a clear introduction to the subject in a precise and insightful writing style. It begins with a philosophical introduction to E- tional Intelligence, and gradually explores the mathematical models for emotional dynamics to study the artificial control of emotion using music and videos, and also to determine the interactions between emotion and logic from the points of view of reasoning. The later part of the book covers the chaotic behavior of - existing emotions under certain conditions of emotional dynamics. Finally, the book attempts to cluster emotions using electroencephalogram signals, and d- onstrates the scope of application of emotional intelligence in several engineering systems, such as human-machine interfaces, psychotherapy, user assistance s- tems, and many others. The book includes ten chapters. Chapter 1 provides an introduction to the s- ject from a philosophical and psychological standpoint. It outlines the fundamental causes of emotion arousal, and typical characteristics of the phenomenon of an emotive experience. The relation between emotion and rationality of thoughts is also introduced here. Principles of natural regulation of emotions are discussed in brief, and the biological basis of emotion arousal using an affective neu- scientific model is introduced next.

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Non-Fiction Psychology Psychology: Emotions Mathematics Applied Mathematics Engineering & Technology Technology in General Maths for Engineers Cognition & Cognitive Psychology Computing & I.T.Graphical & Digital Media Applications Engineering in General

Computer Science Artificial Intelligence Computer Vision

Introduction to Emotional Intelligence	p. 1
What Is Emotional Intelligence?	p. 1
Causes of Emotions	p. 4
Typical Characteristics of Emotion	p. 4
Basic Components of Emotion	p. 5
The Cognitive Component	p. 6
The Evaluative Component	p. 6
The Motivational Component	p. 6
The Feeling Component	p. 6
Rationality of Emotion	p. 7
Regulation and Control of Emotion	p. 8
The Biological Basis of Emotion	p. 10
An Affective Neuro Scientific Model	p. 11
Self Regulation Models of Emotion	p. 13
Emotional Learning	p. 17
Mathematical Modeling of Emotional Dynamics	p. 18
Controlling Emotion by Artificial Means	p. 21
Effect of Emotion Modeling on Human Machine Interactions	p. 22
Scope of the Book	p. 23
Summary	p. 25
References	p. 31
Mathematical Modeling and Analysis of Dynamical Systems	p. 35
Introduction	p. 35
System Modeling and Stability	p. 36
Stability Analysis of Dynamics by Lyapunov Energy Functions	p. 40
Stability Analysis for Continuous Dynamics	p. 42
Stability Analysis of Fuzzy Systems	p. 45
Mamdani Type Fuzzy Systems	p. 45
Takagi-Sugeno Type Fuzzy Systems	p. 46
Stability Analysis of T-S Fuzzy Systems	p. 48
Chaotic Neuro Dynamics and Lyapunov Exponents	p. 52
Emotional Dynamics and Stability Analysis	p. 54
The Lyapunov Exponents and the Chaotic Emotional Dynamics	p. 55
References	p. 60
Preliminaries on Image Processing	p. 63
Introduction	p. 63
Discrete Fourier and Cosine Transforms	p. 64
Preprocessing and Noise Filtering	p. 66
Neighborhood Averaging	p. 66
Median Filtering	p. 66
Thresholding	p. 67
Image Segmentation Algorithms	p. 69
Boundary Detection Algorithms	p. 69
Region Oriented Segmentation Algorithm	p. 75
Region Growing by Pixel Aggregation	p. 76
Regions Splitting and Merging	p. 76
Image Segmentation by Fuzzy Clustering	p. 77
Boundary Description	p. 84
Chain Codes	p. 84
Fourier Descriptors	p. 86
Regional Descriptors	p. 86
Object Recognition from an Image	p. 87
Unsupervised Clustering	p. 87
Supervised Classification	p. 88
Image Matching	p. 88
Template Matching	p. 89
Scene Interpretation	p. 90
Conclusions	p. 91
References	p. 91
Brain Imaging and Psycho-pathological Studies on Self-regulation of Emotion	p. 93
Introduction	p. 93
Emotion Processing by the Human Brain	p. 94
The Amygdale	p. 94
Animal Studies on Amygdale	p. 94
Fear and Threat Perception of the Amygdale	p. 95
The Orbitofrontal Cortex (OFC)	p. 96
Animal Lesions to Prefrontal OFC	p. 96
Neuro-psychology and Functional Neuro-imaging Studies on OFC Behavior	p. 96
The Insula	p. 97
Experiment of Selective Lesion of Insula Cortex	p. 97
The Anterior Cingulated	p. 97
Emotion Monitoring by the Cingulated Cortex	p. 98
The Role of Medial Frontal Cortex in Self-regulation of Emotion	p. 99
The Anterior Cingulate Cortex as a Self-regulatory Agent	p. 99
Voluntary Self-regulation of Emotion	p. 101
fMRI Studies on Voluntary Regulation of Sexual Arousals	p. 102
Voluntary Regulation of Sadness in Adults	p. 103
Neural Circuitry Underlying Emotional Self-regulation	p. 103
EEG Conditioning and Affective Disorders	p. 104
Pain Conditioning in Rats	p. 105
Clinical Study of Depression Using EEG	p. 106
EEG Analysis for Premenstrual Dysphoric Disorder	p. 106
Emotion Dysregulation and Psycho-pathological Issues	p. 107
Emotinal Dysregulation in Childhood from Non-clinical Samples	p. 107
Clinical Samples for Emotional Dysregulation for Children	p. 108
Emotion Regulation in Adulthood	p. 109
Non-clinical Studies	p. 109
Clinical Studies	p. 110
Conclusions	p. 110
References	p. 124
Fuzzy Models for Facial Expression-Based Emotion Recognition and Control	p. 133
Introduction	p. 133
Filtering, Segmentation and Localization of Facial Components	p. 135
Segmentation of the Mouth Region	p. 136
Segmentation of the Eye-Region	p. 137
Segmentation of the Eyebrow Constriction	p. 139
Determination of Facial Attributes	p. 139
Determination of the Mouth-Opening	p. 139
Determination of the Eye-Opening	p. 139
Determination of the Length of Eyebrow-Constriction	p. 139
Fuzzy Relational Model for Emotion Detection	p. 141
Fuzzification of Facial Attributes	p. 141
The Fuzzy Relational Model for Emotion Detection	p. 141
Experiments and Results	p. 144
Validation of the System Performance	p. 152
Proposed Model of Emotion Transition and Its Control	p. 153
The Model	p. 153
Properties of the Model	p. 155
Emotion Control by Mamdani's Model	p. 157
Architecture of the Proposed Emotion Control Scheme	p. 163
Experiments and Results	p. 163
Conclusions	p. 166
References	p. 171
Control of Mental Stability in Emotion-Logic Interactive Dynamics	p. 175
Introduction	p. 175
Stable Points of Non-temporal Logic	p. 176
Finding Common Interpretations of Propositional Statements	p. 177
Determining Stable Points of Logical Statements	p. 179
Stable Points in Propositional Temporal Logic	p. 180
Stability of Propositional Temporal System Using Lyapunov Energy Function	p. 183
The Lyapunov Energy Function	p. 183
Stability Analysis of Propositional Temporal System	p. 183
Human Emotion Modeling and Stability Analysis	p. 185
Stability Analysis of the Emotional Dynamics	p. 186
Weight Adaptation in Emotion Dynamics by Hebbian Learning	p. 189
Improving Relative Stability of the Learning Dynamics	p. 190
The Fuzzy Temporal Representation of Phenomena Involving Emotional States	p. 190
Stabilization of Emotional Dynamics	p. 194
Psychological Stability in Emotion-Logic Counter-Actions	p. 195
Conclusions	p. 197
References	p. 207
Multiple Emotions and Their Chaotic Dynamics	p. 209
Introduction	p. 209
Proposed Model for Chaotic Emotional Dynamics	p. 210
Effect of Variation in Parameters of the Emotional Dynamics	p. 212
Variation in aij	p. 212
Variation in Cij	p. 214
Variation of bij	p. 215
Chaotic Fluctuation in Emotional State	p. 217
Stability Analysis of the Proposed Emotional Dynamics by Lyapunov Energy Function	p. 219
Parameter Selection of the Emotional Dynamics by Experiments with Audio-Visual Stimulus	p. 220
A Stabilization Scheme for the Mixed Emotional Dynamics	p. 226
Conclusions	p. 228
References	p. 232
Electroencephalographic Signal Processing for Detection and Prediction of Emotion	p. 235
Introduction	p. 235
EEG Prediction by Adaptive Filtering	p. 236
LMS Filter	p. 237
EEG Prediction by NLMS Algorithm	p. 238
The RLS Filter for EEG Prediction	p. 240
The Kalman Filter for EEG Prediction	p. 242
Implication of the Results	p. 245
EEG Signal Prediction by Wavelet Coefficients	p. 247
Bio-potential Signals in Emotion Prediction	p. 252
Principles in SVM	p. 253
Emotion Clustering by Neural Networks	p. 256
Conclusions	p. 259
References	p. 259
Applications and Future Directions of Emotional Intelligence	p. 261
Introductions	p. 261
Application in Human-Machine Interactive Systems	p. 263
Input Interfaces	p. 263
Output Interfaces	p. 263
Embodiment of Artificial Characters	p. 264
Application in Multi-agent Co-operation of Mobile Robotics	p. 265
Emotional Intelligence in Psycho-therapy	p. 266
Detection of Anti-social Motives from Emotional Expressions	p. 267
Applications in Video Photography/Movie Making	p. 269
Applications in Personality Matching of People for Matrimonial Counseling	p. 270
Synthesizing Emotions in Voice	p. 271
Application in User Assistance Systems	p. 272
Emotion Recognition from Voice Samples	p. 273
Speech Articulatory Features	p. 273
Personality Building of Artificial Creatures	p. 275
Multimodal Emotion Recognition	p. 277
Current Status	p. 277
Research Initiative at Jadavpur University	p. 278
Parameter Identification of Emotional Dynamics Using EEG and fMRI Brain Imaging	p. 283
System Identification Approach to EEG Dynamics Modeling by Evolutionary Algorithms	p. 283
Genetic Algorithm in Emotional System Identification	p. 285
Particle Swarm Optimization in Emotional System Identification	p. 286
Differential Evolution Algorithm in Emotional System Identification	p. 289
Conclusions	p. 290
References	p. 291
Open Research Problems	p. 295
Introduction	p. 295
Reasoning with Emotions	p. 297
Uncertainty Management in Emotion-Based Reasoning	p. 298
Selected Open Problems	p. 299
Multi-modal Emotion Recognition	p. 299
Artificial of Emotion by Takagi-Sugeno Method	p. 299
Determining Manifestation of Emotion on facial Expression from EEG Signals	p. 299
Further Readings for Researchers	p. 300
References	p. 301
Appendix	p. 305
Author's Biography	p. 319
Subject Index	p. 321
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Studies in Computational Intelligence

A Cybernetic Approach

At a Glance

Hardcover

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