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Singular Spectrum Analysis of Biomedical Signals

or EKGs), oxygen levels, arterial pressure, and electroencephalograms (EEGs). Singular Spectrum Analysis of Biomedical Signals presents;

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Singular Spectrum Analysis of Biomedical Signals

or EKGs), oxygen levels, arterial pressure, and electroencephalograms (EEGs). Singular Spectrum Analysis of Biomedical Signals presents;

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Biomedical Signal Processing for Healthcare Applications

modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights;

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine;

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Singular Spectrum Analysis

eigenvalues, A, are the numbers that make the matrix A -AI singular. The term singular spectrum analysis* is unfortunate since the traditional;

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Acoustic Sensors for Biomedical Applications

In this book, application-related studies for acoustic biomedical sensors are covered in depth. The book features an array of different;

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Neural Engineering Techniques for Autism Spectrum Disorder

Neural Engineering for Autism Spectrum Disorder, Volume One: Imaging and Signal Analysis Techniques presents the latest advances in neural;

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Brain Seizure Detection and Classification Using EEG Signals

extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types;

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Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time;

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Signals and Systems Analysis in Biomedical Engineering

that comprise this field. Updated and revised to include new material as the field has grown, Signals and Systems Analysis in Biomedical;

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Biomedical Signal Analysis

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a;

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Practical Biomedical Signal Analysis Using MATLAB (R)

processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB (R) also offers practical guidance on;

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Advanced Methods of Biomedical Signal Processing

from biomedical signals; higher order analysis in biomedical signals; advanced methods of signal and data processing in genomics and proteomics;

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Biomedical Signal Processing and Artificial Intelligence in Healthcare

analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Deep;

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Biomedical Signal and Image Examination with Entropy-Based Techniques

computerized examination systems. The recent research works on biomedical signal evaluation confirms that signal analysis provides vital information;

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Nonlinear Biomedical Signal Processing, Volume 1

>Uncertainty management Analysis of biomedical signals A guided tour of neural networks Application of algorithms to EEG and;

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Ultra-Low-Voltage Frequency Synthesizer and Successive-Approximation Analog-to-Digital Converter for Biomedical Applications

This book introduces the origin of biomedical signals and the operating principles behind them and introduces the characteristics of common;

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Time-Series Analysis and Cyclostratigraphy

, cross-spectral analysis, filtering, complex demodulation, wavelet and singular spectrum analysis. Practical problems of time-series analysis;

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Time Frequency And Wavelets In Biomedical Signal Processing

> Topics covered include: Time-frequency analysis methods and biomedical applications Wavelets, wavelet packets, and;

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and;

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Computer-aided Design and Diagnosis Methods for Biomedical Applications

Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection;

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Introduction to Applied Statistical Signal Analysis

analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech;

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Biomedical Signal Processing

principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and;

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Fundamentals of Measurement and Signal Analysis

and the spectrum analysis of audio signals in the signal processing part and Arduino examples as well, such as temperature measuring and;

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Modulation Theory

covers signal representations for most known waveforms, Fourier analysis, and presents an introduction to Fourier transform and signal spectrum;

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Modulation Theory

In recent years, a considerable amount of effort has been devoted, both in industry and academia, towards the design, performance analysis;

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Computational Intelligence in Biomedical Engineering

techniques commonly employed in the analysis of biomedical signals and in the improvement of signal to noise ratio. The text covers recent CI;

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