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Spectral analysis and its applications
, 1968Give us 5 minutes and we will show you the best book to read today. This is it, the spectral analysis and its applications that will be your best choice for better reading book. Your five times will not spend wasted by reading this website.
G. Jenkins, D. G. Watts
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Assessment of autonomic function in humans by heart rate spectral analysis.
American Journal of Physiology, 1985Spectral analysis of spontaneous heart rate fluctuations were assessed by use of autonomic blocking agents and changes in posture. Low-frequency fluctuations (below 0.12 Hz) in the supine position are mediated entirely by the parasympathetic nervous ...
B. Pomeranz +10 more
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, 2009
1. Spectral Analysis – A Tutorial Introduction 2. Selected Applications (presented by instructors) 3. Basic Definitions and the Spectral Analysis Problem Chap. 1 4. Periodogram and Correlogram Methods Sect. 2.1 – 2.3 5. Improved Periodogram Based Methods
Usik Lee
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1. Spectral Analysis – A Tutorial Introduction 2. Selected Applications (presented by instructors) 3. Basic Definitions and the Spectral Analysis Problem Chap. 1 4. Periodogram and Correlogram Methods Sect. 2.1 – 2.3 5. Improved Periodogram Based Methods
Usik Lee
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
We present a spectral approach for detecting and analyzing rotational and reflectional symmetries in n-dimensions. Our main contribution is the derivation of a symmetry detection and analysis scheme for sets of points in IRn and its extension to image analysis by way of local features.
Michael Chertok, Yosi Keller
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We present a spectral approach for detecting and analyzing rotational and reflectional symmetries in n-dimensions. Our main contribution is the derivation of a symmetry detection and analysis scheme for sets of points in IRn and its extension to image analysis by way of local features.
Michael Chertok, Yosi Keller
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Spectral Analysis and Filtering
2000The notion that a time series exhibits repetitive or regular behavior over time is of fundamental importance because it distinguishes time series analysis from classical statistics, which assumes complete independence over time. We have seen how dependence over time can be introduced through models that describe in detail the way certain empirical data
David S. Stoffer, Robert H. Shumway
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1987
Publisher Summary This chapter explores the issues that are central to estimating spectral density functions from time series observations. It describes three classes of rational spectral density functions. The first two classes are the moving average (MA) and the autoregressive (AR) spectral models.
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Publisher Summary This chapter explores the issues that are central to estimating spectral density functions from time series observations. It describes three classes of rational spectral density functions. The first two classes are the moving average (MA) and the autoregressive (AR) spectral models.
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Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics
International Journal of Innovative Science and Research TechnologySpeech is essential to human communication for expressing and understanding feelings. Emotional speech processing has challenges with expert data sampling, dataset organization, and computational complexity in large-scale analysis.
Zewar Shah, Shan Zhiyong, Adnan
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Engineering Applications of Correlation and Spectral Analysis
, 1980Probability Functions and Amplitude Measures. Correlation and Spectral Density Functions. Single-Input/Single-Output Relationships. System Identification and Response. Propagation-Path Identification. Single-Input/Multiple-Output Problems. Multiple-Input/
J. Bendat, A. Piersol
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Spectral-element analysis in seismology
2007We present a review of the application of the spectral-element method to regional and global seismology. This technique is a high-order variational method that allows one to compute accurate synthetic seismograms in three-dimensional heterogeneous Earth models with deformed geometry.
Chaljub, Emmanuel +5 more
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Electroencephalography and Clinical Neurophysiology, 1983
Spectrum analysis of EMG has gained interest during the past decades due to its quantitative nature. Much of the interest can also be traced back to the greater availability of mini-and microcomputers which enable more elaborate analysis.
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Spectrum analysis of EMG has gained interest during the past decades due to its quantitative nature. Much of the interest can also be traced back to the greater availability of mini-and microcomputers which enable more elaborate analysis.
openaire +2 more sources