Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques (notice n° 72301)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02327cam a2200277zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88873389 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250107232351.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250108s2019 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780128174449 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88873389 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Subasi, Abdulhamit |
| 245 01 - TITLE STATEMENT | |
| Title | Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques |
| Remainder of title | A MATLAB Based Approach |
| Statement of responsibility, etc. | ['Subasi, Abdulhamit'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Elsevier Science |
| Date of production, publication, distribution, manufacture, or copyright notice | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interactionExplains how to apply machine learning techniques to EEG, ECG and EMG signalsGives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Subasi, Abdulhamit |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88873389">https://international.scholarvox.com/netsen/book/88873389</a> |
| Electronic format type | text/html |
| Host name | |
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