Discrete random signal processing and filtering primer with MATLAB /
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| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton :
CRC Press,
2018.
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| Edition: | 1st |
| Series: | The electrical engineering and applied signal processing series
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Item Description: | Previously issued in print: 2008. <P><STRONG>Fourier analysis of signals</STRONG></P><P>Introduction</P><P>FT</P><P>Sampling of signals</P><P>Discrete-time FT (DTFT)</P><P>DFT</P><P>Resolution</P><P>Continuous linear systems</P><P>Discrete systems-linear difference equations</P><P>Detrending</P><P><STRONG>Random variables, sequences, and stochastic processes</STRONG></P><P>Random signals and distributions</P><P>Averages</P><P>Stationary processes</P><P>Wiener-Khinchin relations</P><P>Filtering random processes</P><P>PDFs</P><P>Estimators</P><P>Confidence intervals</P><P><STRONG>Nonparametric (classical) spectrums estimation</STRONG></P><P>Periodogram and correlogram spectra estimators</P><P>Daniell periodogram</P><P>Bartlett periodogram</P><P>Blackman-Tukey (BT) method</P><P>Welch method</P><P>Proposed modified methods for Welch periodogram</P><P><STRONG>Parametric and other methods for spectra estimation</STRONG></P><P>AR, MA, and ARMA models</P><P>Yule-Walker (YW) equations</P><P>Least-squares (LS) method and linear prediction</P><P>Minimum variance (MV) method</P><P>Model order</P><P>Levinson-Durbin algorithm</P><P>Maximum entropy method</P><P>Spectrums of segmented signals</P><P>Eigenvalues and eigenvectors of matrices </P><P><STRONG>Optimal filtering-Wiener filters</STRONG></P><P>Mean square error (MSE)</P><P>FIR Wiener filter </P><P>Wiener solution-orthogonal principle</P><P>Wiener filtering examples</P><P><STRONG>Adaptive filtering-LMS algorithm</STRONG></P><P>Introduction</P><P>LMS algorithm</P><P>Examples using the LMS algorithm</P><P>Properties of the LMS method</P><P><STRONG>Adaptive filtering with variations of LMS algorithm.</STRONG></P><P>Sign algorithms</P><P>Normalized LMS (NLMS) algorithm</P><P>Variable step-size LMS algorithm (VSLMS)</P><P>Leaky LMS algorithm</P><P>Linearly constrained LMS algorithm</P><P>Self-correcting adaptive filtering (SCAF)</P><P>Transform domain adaptive LMS filtering</P><P>Convergence in transform domain of the adaptive LMS filtering</P><P>Error-normalized LMS algorithm</P><P><STRONG>Nonlinear filtering</STRONG></P><P>Introduction</P><P>Statistical preliminaries</P><P>Mean filter</P><P>Median filter</P><P>Trimmed-type mean filter</P><P>L-filters</P><P>Ranked-order statistic filter</P><P>Edge-enhancement filters</P><P>R-filters</P><P><STRONG>Appendix A: Suggestions and explanations for MATLAB® use</STRONG></P><P><STRONG>Appendix B: Matrix analysis</STRONG></P><P><STRONG>Appendix C: Lagrange multiplier method</STRONG></P> |
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| Physical Description: | 1 online resource |
| ISBN: | 9781351834452 1351834452 9781420089349 142008934X 9781351825764 1351825763 9781315218564 1315218569 |