Search Results - mathematical statistics data processing.

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    Lecture notes on the mathematics of acoustics

    Published 2005
    Table of Contents: “…Part IV Signal ProcessingChapter 12 Digital Filters; 12.1 Mathematical Overview; 12.2 Fourier Transform; 12.3 Impulse Response and Frequency Response; 12.4 Convolution Principle; 12.5 Dirac Delta Functions and Sifting Property; 12.6 Laplace Transform Analysis; 12.7 Digital Filters; 12.8 Summary; Further Reading; Chapter 13 Measurement of Linear Time-Invariant Systems; 13.1 Introduction; 13.2 Estimating Statistics Using Fourier Methods; 13.3 Maximum Length Sequences; 13.4 Practical; Further Reading; Chapter 14 Numerical Optimisation; 14.1 Introduction; 14.2 Genetic Algorithms.…”
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  5. 225

    Adaptive processing of brain signals by Sanei, Saeid

    Published 2013
    Table of Contents: “…262 -- 11.8 Emotion-Related Brain Signal Processing 263 -- 11.9 Other Neuroimaging Modalities Used for Emotion Study 264 -- 11.10 Applications 267 -- 11.11 Conclusions 268 -- References 268 -- 12 Sleep and Sleep Apnoea 274 -- 12.1 Introduction 274 -- 12.2 Stages of Sleep 275 -- 12.2.1 NREM Sleep 275 -- 12.2.2 REM Sleep 277 -- 12.3 The Influence of Circadian Rhythms 278 -- 12.4 Sleep Deprivation 279 -- 12.5 Psychological Effects 280 -- 12.6 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis 281 -- 12.6.1 Analysis of Sleep Apnoea 281 -- 12.6.2 Detection of the Rhythmic Waveforms and Spindles Employing Blind Source Separation 282 -- 12.6.3 Application of Matching Pursuit 282 -- 12.6.4 Detection of Normal Rhythms and Spindles Using Higher Order Statistics 285 -- 12.6.5 Application of Neural Networks 287 -- 12.6.6 Model-Based Analysis 288 -- 12.6.7 Hybrid Methods 290 -- 12.7 EEG and Fibromyalgia Syndrome 290 -- 12.8 Sleep Disorders of Neonates 291 -- 12.9 Dreams and Nightmares 291 -- 12.10 Conclusions 292 -- References 292 -- 13 Brain-Computer Interfacing 295 -- 13.1 Introduction 295 -- 13.2 State of the Art in BCI 296 -- 13.3 BCI-Related EEG Features 300 -- 13.3.1 Readiness Potential and Its Detection 300 -- 13.3.2 ERD and ERS 300 -- 13.3.3 Transient Beta Activity after the Movement 302 -- 13.3.4 Gamma Band Oscillations 302 -- 13.3.5 Long Delta Activity 303 -- 13.4 Major Problems in BCI 303 -- 13.4.1 Pre-Processing of the EEGs 304 -- 13.5 Multidimensional EEG Decomposition 306 -- 13.5.1 Space-Time-Frequency Method 308 -- 13.5.2 Parallel Factor Analysis 309 -- 13.6 Detection and Separation of ERP Signals 310 -- 13.7 Estimation of Cortical Connectivity 311 -- 13.8 Application of Common Spatial Patterns 314 -- 13.9 Multiclass Brain-Computer Interfacing 316 -- 13.10 Cell-Cultured BCI 318 -- 13.11 Conclusions 319 -- References 320 -- 14 EEG and MEG Source Localization 325 -- 14.1 Introduction 325 -- 14.2 General Approaches to Source Localization 326 -- 14.2.1 Dipole Assumption 327 -- 14.3 Most Popular Brain Source Localization Approaches 329 -- 14.3.1 ICA Method 329 -- 14.3.2 MUSIC Algorithm 329 -- 14.3.3 LORETA Algorithm 333 -- 14.3.4 FOCUSS Algorithm 335 -- 14.3.5 Standardised LORETA 335 -- 14.3.6 Other Weighted Minimum Norm Solutions 336 -- 14.3.7 Evaluation Indices 338 -- 14.3.8 Joint ICA-LORETA Approach 338 -- 14.3.9 Partially Constrained BSS Method 340 -- 14.3.10 Constrained Least-Squares Method for Localization of P3a and P3b 341 -- 14.3.11 Spatial Notch Filtering Approach 342 -- 14.3.12 Deflation Beamforming Approach for EEG/MEG Multiple Source Localization 347 -- 14.3.13 Hybrid Beamforming -- Particle Filtering 351 -- 14.4 Determination of the Number of Sources from the EEG/MEG Signals 353 -- 14.5 Conclusions 355 -- References 356 -- 15 Seizure and Epilepsy 360 -- 15.1 Introduction 360 -- 15.2 Types of Epilepsy 362 -- 15.3 Seizure Detection 365 -- 15.3.1 Adult Seizure Detection 365 -- 15.3.2 Detection of Neonate Seizure 371 -- 15.4 Chaotic Behaviour of EEG Sources 376 -- 15.5 Predictability of Seizure from the EEGs 378 -- 15.6 Fusion of EEG -- fMRI Data for Seizure Detection and Prediction 391 -- 15.7 Conclusions 391 -- References 392 -- 16 Joint Analysis of EEG and fMRI 397 -- 16.1 Fundamental Concepts 397 -- 16.1.1 Blood Oxygenation Level Dependent 399 -- 16.1.2 Popular fMRI Data Formats 400 -- 16.1.3 Preprocessing of fMRI Data 401 -- 16.1.4 Relation between EEG and fMRI 401 -- 16.2 Model-Based Method for BOLD Detection 403 -- 16.3 Simultaneous EEG-fMRI Recording: Artefact Removal from EEG 405 -- 16.3.1 Gradient Artefact Removal 405 -- 16.3.2 Ballistocardiogram Artefact Removal 406 -- 16.4 BOLD Detection in fMRI 413 -- 16.4.1 Implementation of Different NMF Algorithms for BOLD Detection 414 -- 16.4.2 BOLD Detection Experiments 416 -- 16.5 Fusion of EEG and fMRI 419 -- 16.5.1 Extraction of fMRI Time-Course from EEG 419 -- 16.5.2 Fusion of EEG and fMRI, Blind Approach 241 -- 16.5.3 Fusion of EEG and fMRI, Model-Based Approach 425 -- 16.6 Application to Seizure Detection 425 -- 16.7 Conclusions 427 -- References 427.…”
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    Handbook of high-frequency trading and modeling in finance

    Published 2016
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    Quantitative modelling in marketing and management

    Published 2013
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    Handbook of image and video processing

    Published 2005
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    Handbook of capture-recapture analysis

    Published 2005
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    Communicating process architectures 2009 : WoTUG-32

    Published 2009
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    Electronic Conference Proceeding eBook
  17. 237

    Non-Gaussian Merton-Black-Scholes theory by Boyarchenko, Svetlana I.

    Published 2002
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