Digital signal processing with Matlab examples. Volume 1, Signals and data, filtering, non-stationary signals, modulation /

• Main Author: Giron-Sierra, Jose Maria (Author)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer, [2016]
• Series: Signals and communication technology,
• Subjects: MATLAB.; Signal processing > Digital techniques > Data processing.; elektronické knihy; electronic books
• ISBN: 9789811025341; 9789811025334
• ISSN: 1860-4862
• Physical Description: 1 online resource (xxxvii, 622 pages) : illustrations (some color)

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the t...

Table of Contents:

• Intro; Preface; Contents; List of Figures; Listings; Part I Signals and Data; 1 Periodic Signals; 1.1 Introduction; 1.2 Signal Representation; 1.3 Generation of Periodic Signals; 1.3.1 Sinusoidal; 1.3.2 Square; 1.3.3 Sawtooth; 1.4 Hearing the Signals; 1.5 Operations with Signals; 1.5.1 Adding Signals; 1.5.2 Multiplication; 1.6 Harmonics. Fourier; 1.6.1 Odd Signals; 1.6.2 Even Signals; 1.6.3 Half Wave Symmetry; 1.6.4 Pulse Train; 1.7 Sampling Frequency; 1.8 Suggested Experiments and Exercises; 1.9 Resources; 1.9.1 MATLAB; 1.9.2 Web Sites; References; 2 Statistical Aspects; 2.1 Introduction
• 2.2 Random Signals and Probability Density Distributions2.2.1 Basic Concepts; 2.2.2 Random Signal with Uniform PD; 2.2.3 Random Signal with Normal (Gaussian) PDF; 2.2.4 Random Signal with Log-Normal PDF; 2.3 Expectations and Moments; 2.3.1 Expected Values, and Moments; 2.3.2 Mean, Variance, Etc.; 2.3.3 Transforms; 2.3.4 White Noise; 2.4 Power Spectra; 2.4.1 Basic Concept; 2.4.2 Example of Power Spectral Density of a Random Variable; 2.4.3 Detecting a Sinusoidal Signal Buried in Noise; 2.4.4 Hearing Random Signals; 2.5 More Types of PDFs; 2.5.1 Distributions Related with the Gamma Function
• 2.5.2 Weibull and Rayleigh PDFs2.5.3 Multivariate Gaussian PDFs; 2.5.4 Discrete Distributions; 2.6 Distribution Estimation; 2.6.1 Probability Plots; 2.6.2 Histogram; 2.6.3 Likelihood; 2.6.4 The Method of Moments; 2.6.5 Mixture of Gaussians; 2.6.6 Kernel Methods; 2.7 Monte Carlo Methods; 2.7.1 Monte Carlo Integration; 2.7.2 Generation of Random Data with a Desired PDF; 2.8 Central Limit; 2.9 Bayes' Rule; 2.9.1 Conditional Probability; 2.9.2 Bayes' Rule; 2.9.3 Bayesian Networks. Graphical Models; 2.10 Markov Process; 2.10.1 Markov Chain; 2.10.2 Markov Chain Monte Carlo (MCMC)
• 2.10.3 Hidden Markov Chain (HMM)2.11 MATLAB Tools for Distributions; 2.12 Resources; 2.12.1 MATLAB; 2.12.2 Web Sites; References; Part II Filtering; 3 Linear Systems; 3.1 Introduction; 3.2 Examples About Transfer Functions; 3.2.1 A Basic Low-Pass Electronic Filter; 3.2.2 A Basic Resonant Electronic Filter; 3.3 Response of Continuous Linear Systems; 3.3.1 Frequency Response; 3.3.2 Time Domain Response; 3.4 Response of Discrete Linear Systems; 3.5 Random Signals Through Linear Systems; 3.6 State Variables; 3.7 State Space Gauss
• Markov Model; 3.7.1 A Scalar State Space Case
• 3.7.2 General State Space Case3.8 Time-Series Models; 3.8.1 The Discrete Transfer Function in Terms of the Backshift Operator; 3.8.2 Considering Random Variables; 3.9 Resources; 3.9.1 MATLAB; 3.9.2 Web Sites; References; 4 Analog Filters; 4.1 Introduction; 4.2 Basic First Order Filters; 4.3 A Basic Way for Filter Design; 4.4 Causality and the Ideal Band-Pass Filter; 4.5 Three Approximations to the Ideal Low-Pass Filter; 4.5.1 Butterworth Filter; 4.5.2 Chebyshev Filter; 4.5.3 Elliptic Filter; 4.5.4 Comparison of Filters; 4.5.5 Details of the MATLAB Signal Processing Toolbox