Comprehensive Analysis of Swarm Based Classifiers and Bayesian Based Models for Epilepsy Risk Level Classification from EEG Signals.
- 1st ed.
- 1 online resource (48 pages)
Comprehensive Analysis of Swarm Based Classifiers and Bayesian Based Models for Epilepsy Risk Level Classificationfrom EEG Signals -- ABSTRACT -- TABLE OF CONTENTS -- LIST OF TABLES -- LIST OF FIGURES -- LIST OF ABBREVIATIONS -- CHAPTER 1: INTRODUCTION -- 1.1 GENESIS OF EEG SIGNALS -- 1.2 EPILEPSY DETECTION AND EEG SIGNALS -- 1.3 EPILEPSY CLASSIFICATION SYSTEM -- 1.4 DATA COLLECTION -- 1.5 FEATURE EXTRACTION -- 1.5.1 ALGORITHM -- 1.6 ORGANISATION OF THE STUDY -- CHAPTER 2: CODE CONVERTER AS A PRE CLASSIFIER FOR CLASSIFICATION OFEPILEPSY RISK LEVEL -- 2.1 INTRODUCTION -- 2.2 EEG SIGNAL PARAMETERS -- 2.3 WAVELET TRANSFORM -- 2.4 THRESHOLDING -- 2.5 METHODOLOGY -- 2.6 SUMMARY -- CHAPTER 3: PSO AND BAYESIAN CLASSIFIER AS POST CLASSIFIER FOR CLASSIFICATION OF EPILEPSY RISK LEVEL -- 3.1 INTRODUCTION -- 3.2 PARTICLE SWARM OPTIMIZATION -- 3.2.1 PSO PARAMETER CONTROL -- 3.2.2 PSO ALGORITHM -- 3.3 HYBRID PSO ALGORITHM -- 3.3.1 STEPS OF HYBRID PSO -- 3.4 BAYESIAN CLASSIFIER -- 3.5 CONCLUSION -- CHAPTER 4: PERFORMANCE ANALYSIS AND DISCUSSION -- 4.1 PERFORMANCE INDEX -- 4.2 QUALITY VALUE -- 4.3 COMPARISON OF OPTIMIZATION RESULTS -- CHAPTER 5: CONCLUSION -- REFERENCES.