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Bibliographic Detail
Publisher
Prentice Hall
Publication date
April 1, 1988
Binding
Paperback
Edition
Facsimile
Book category
Adult Non-Fiction
ISBN-13
9780133075052
ISBN-10
0133075052
Dimensions
1 by 6.50 by 9.50 in.
Weight
1.60 lbs.
Original list price
$198.80
Amazon.com says people who bought this book also bought:
Deep Learning (Adaptive Computation and Machine Learning series) | Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems | Ordinary Differential Equations | Partial Differential Equations for Scientists and Engineers | The Fourier Transform and Its Applications | Understanding Fft Applications | Understanding the Fft | The Fft, Fundamentals and Concepts | The Scientist & Engineer's Guide to Digital Signal Processing
Deep Learning (Adaptive Computation and Machine Learning series) | Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems | Ordinary Differential Equations | Partial Differential Equations for Scientists and Engineers | The Fourier Transform and Its Applications | Understanding Fft Applications | Understanding the Fft | The Fft, Fundamentals and Concepts | The Scientist & Engineer's Guide to Digital Signal Processing
Summaries and Reviews
Amazon.com description: Product Description: The Fast Fourier Transform (FFT) is a mathematical method widely used in signal processing. This book focuses on the application of the FFT in a variety of areas: Biomedical engineering, mechanical analysis, analysis of stock market data, geophysical analysis, and the conventional radar communications field.
Editions
Paperback
The price comparison is for this edition
Facsimile edition from Prentice Hall (April 1, 1988)
9780133075052 | details & prices | 6.50 × 9.50 × 1.00 in. | 1.60 lbs | List price $198.80
About: The Fast Fourier Transform (FFT) is a mathematical method widely used in signal processing.
About: The Fast Fourier Transform (FFT) is a mathematical method widely used in signal processing.
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