Numerical and statistical methods for bioengineering
applications in MATLAB
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Author
Contributions
- Mody, Nipa A. - Contributor
Publication
2010 - Cambridge University Press, New York, New York (State)
Language
English
Word Count
0 words, Guess
Page Count
0 pages
Identifiers
- Internet Archivenumericalstatist00king
- ISBN-139780521871587
- ISBN-100521871581
- Library of Congress Control Number2010025717
- Open LibraryOL24539112M
Classifications
- DDC610.28
- LCCR857.M34 K56 2010
Description
"The first MATLAB-based numerical methods textbook for bioengineers that uniquely integrates modelling concepts with statistical analysis, while maintaining a focus on enabling the user to report the error or uncertainty in their result. Between traditional numerical method topics of linear modelling concepts, nonlinear root finding, and numerical integration, chapters on hypothesis testing, data regression and probability are interweaved. A unique feature of the book is the inclusion of examples from clinical trials and bioinformatics, which are not found in other numerical methods textbooks for engineers. With a wealth of biomedical engineering examples, case studies on topical biomedical research, and the inclusion of end of chapter problems, this is a perfect core text for a one-semester undergraduate course"-- "Cambridge Texts in Biomedical Engineering provides a forum for high-quality accessible textbooks targeted at undergraduate and graduate courses in biomedical engineering. It will cover a broad range of biomedical engineering topics from introductory texts to advanced topics including, but not limited to, biomechanics, physiology, biomedical instrumentation, imaging, signals and systems, cell engineering, and bioinformatics. The series will blend theory and practice, aimed primarily at biomedical engineering students but will be suitable for broader courses in engineering, the life sciences and medicine"--
Subjects
Series Statement
- Cambridge texts in biomedical engineering
Links
Other Editions
- Numerical and statistical methods for bioengineering: applications in MATLAB
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