Biological Signals Classification and Analysis


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Sign in. This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems.

This book separates what is random from that which appears to be random and yet is truly deterministic with random appearance.

EEG Signal Classification Matlab Code - EEG Signal Classification Matlab Code Projects

In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently proposed signal processing tools and methods for addressing biological signals is included.

The target audience primarily comprises researchers and expert practitioners but the book may also be beneficial for graduate students. Xiongbiao Luo. The Mathematics of Medical Imaging.

Biological Signals Classification and Analysis : Kamran Kiasaleh :

Timothy G. Analog and Digital Signal Analysis. Computational Intelligence in Biomedical Imaging. Kenji Suzuki. New Trends in Applied Harmonic Analysis.


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Joao Tavares. Multispectral Biometrics. Biosignal processing techniques: - Statistical techniques - Independent Component Analysis - Time domain approaches - Frequency domain approaches - Wavelet based analysis - Biosignal feature extraction Biosignal classification techniques: - Supervised classification techniques - Unsupervised classification techniques - Artificial Neural Networks - Wavelet Networks - Syntactic approaches Biosignal systems: - Acquisition techniques - Handheld systems - Unimodal dedicated systems - Multimodal systems - Wireless transmission of biosignals - Biometric systems based on biosignals Biosignal applications areas: - Health monitoring - Human Computer Interaction - 2D and 3D Medical Imagining - Performance in sports using biosignals - Rehabilitation using biofeedback - Music, arts and entertainment - Biosignals in assistive technologies - Affective state detection - Stress detection - Cognition Overload.

Invited Speakers - Prof. Kevin Warwick , University of Reading, U. Brief Bio: Kevin Warwick is a Professor of Cybernetics at the University of Reading, UK where he carries out research in artificial intelligence, control, robotics and cyborgs. He subsequently held positions at Oxford, Newcastle and Warwick Universities before being offered the Chair at Reading, at the age of As well as publishing over research papers, Kevin has appeared, on 3 separate occasions, in the Guinness Book of Records for his robotics and Cyborg achievements.

His paperback 'In the Mind of the Machine' considered the possibility of machines in the future being more intelligent than humans. His recent Cyborg experiments however led to him being featured as the cover story on the US magazine, 'Wired'.

Biological Signals Classification and Analysis Biological Signals Classification and Analysis
Biological Signals Classification and Analysis Biological Signals Classification and Analysis
Biological Signals Classification and Analysis Biological Signals Classification and Analysis
Biological Signals Classification and Analysis Biological Signals Classification and Analysis
Biological Signals Classification and Analysis Biological Signals Classification and Analysis
Biological Signals Classification and Analysis Biological Signals Classification and Analysis

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