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Author: K. M. M. Prabhu
Publisher: CRC Press
ISBN: 1466515848
Category : Computers
Languages : en
Pages : 404
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Book Description
Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture radar
Author: K. M. M. Prabhu
Publisher: CRC Press
ISBN: 1466515848
Category : Computers
Languages : en
Pages : 404
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Book Description
Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture radar
Author: Julius Orion Smith
Publisher:
ISBN:
Category : Computer sound processing
Languages : en
Pages : 654
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Book Description
"Spectral Audio Signal Processing is the fourth book in the music signal processing series by Julius O. Smith. One can say that human hearing occurs in terms of spectral models. As a result, spectral models are especially useful in audio applications. For example, with the right spectral model, one can discard most of the information contained in a sound waveform without changing how it sounds. This is the basis of modern audio compression techniques."--Publisher's description.
Author: Rebecca M. Warner
Publisher: Guilford Press
ISBN: 9781572303386
Category : Social Science
Languages : en
Pages : 244
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Book Description
This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
Author: Canada. Department of National Defence. Research and Development Branch
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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Book Description
Author: K. M. M. Prabhu
Publisher: CRC Press
ISBN: 146651583X
Category : Computers
Languages : en
Pages : 407
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Book Description
Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture radar
Author: Julius O. Smith
Publisher: Julius Smith
ISBN: 097456074X
Category : Fourier transformations
Languages : en
Pages : 323
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Book Description
"The DFT can be understood as a numerical approximation to the Fourier transform. However, the DFT has its own exact Fourier theory, and that is the focus of this book. The DFT is normally encountered as the Fast Fourier Transform (FFT)--a high-speed algorithm for computing the DFT. The FFT is used extensively in a wide range of digital signal processing applications, including spectrum analysis, high-speed convolution (linear filtering), filter banks, signal detection and estimation, system identification, audio compression (such as MPEG-II AAC), spectral modeling sound synthesis, and many others. In this book, certain topics in digital audio signal processing are introduced as example applications of the DFT"--Back cover
Author: Steve F. Russell
Publisher: Steve F. Russell
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 500
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Book Description
This dissertation covers both the theory and practice of estimating the spectrum of signals in noise using digital data. The theory of describing some of the signal processing concepts for digital data are given and various spectral estimation methods are given. The theory of MEM is described in detail using approaches from estimation theory, communication theory, and statistics. The work was intended to give researchers the theory and practice of practical means of spectral estimation using communications or scientific data. The Maximum Entropy Method by John Parker Burg is explained from what was known in 1974-75. KEY WORDS: Calculus-of-Variations, Data Systems, Noise , Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Data Windowing, Ergodic Process, Maximum Entropy Method (MEM, Fourier Transformation, Optimum Order of Estimation, Sampling, Spectral Resolution, Statistical Significance Test, Systems Analysis, Wiener-Khinchine Theorem. From The Smithsonian/NASA Astrophysics Data System -- The practical aspects of spectral analysis are contrasted with the mathematical theory. Treatment is limited to ergodic processes and emphasizes data window and noise effects. The Discrete Fourier Transform (DFT) and Maximum Entropy Method (MEM) are covered extensively both in theory and application with FORTRAN programs and many examples being provided. Several of the chapters are tutorial and discuss the important topics of sampling theory and system analysis. Topics on MEM include a complete calculus-of-variations solution, relationship between MEM and the Wiener-Khinchine relations, spectral resolution, and choosing the optimum order of the estimation. DFT leakage effects are modeled. A statistical significance test was developed to determine the realness of a spectral component. Keywords: Data Systems, Noise (Sound), Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Ergodic Process, Fourier Transformation, Sampling, Systems Analysis [less]
Author: Pieter Kubben
Publisher: Springer
ISBN: 3319997130
Category : Medical
Languages : en
Pages : 219
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Book Description
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Author: Ramiro Moreira-Paredes
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This thesis studies a new data weighting function, which consists of a complex valued window known as the linear complex valued FM chirp window. This type of window, when used with the Fourier transform, produces a magnitude spectrum which permits identification of single sinusoids and multiple sinusoids which can be separated in frequency by less than one DFT bin. This allows determination of whether or not one or multiple signals are present. The chirp window seems to have better resolution properties than classical windows. When the chirp window is used with a signal that contains a frequency step (i.e., FSK), the resultant spectrum is markedly different for the upward shift and downward shift cases. The work of this thesis consists of replicating the results of J. Griffiths in his paper 'A Novel Window For High Resolution Fourier Transform' to establish the signal to noise ratio dependency of this type of window, and to study its behavior when damped sinusoids are present. Additionally, a review of classical windows and sidelobe behavior is presented. All simulations where performed using MATLAB.
Author: Gwilym M. Jenkins
Publisher: Emerson Adams PressInc
ISBN: 9781892803030
Category : Science
Languages : en
Pages : 525
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Book Description
