By Boaz Porat
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A accomplished, useful and updated exposition on electronic sign processing. either mathematical and worthwhile, this ebook makes use of a rigorous method of aid readers study the speculation and perform of DSP. It discusses sensible spectral research, together with using home windows for spectral research, sinusoidal sign research, and the influence of noise. It additionally covers FIR and IIR filters, together with precise layout techniques and MATLAB instruments.
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Extra info for A Course in Digital Signal Processing
Two random variables x and y governed by a joint probability distribution have a covariance, defined by Yx,y = E[(x - Jix)(Y The covariance can be positive, negative, inequality? IYx,yl - Jiy)]. 60) :$ axay. Two random variables are said to be uncorrelated if their covariance is zero. If x and yare the same random variable, their covariance is equal to the variance of x. A random signal x(t) has mean and variance at every time point. The mean and the variance depend on t in general, so we denote them as functions of time, Jix (t) and Yx(t), respectively.
Three chapters are devoted to frequency-domain digital signal processing. Chapter 4 introduces the discrete Fourier transform (DFT) and discusses in detail its properties and a few of its uses. This chapter also teaches the discrete cosine transform (DCn, a tool of great importance in signal compression. Chapter 6 is devoted to practical aspects of frequency-domain analysis. It explains the main problems in frequency-domain analysis, and teaches how to use the DFT and FFT for solving these problems.
For example, the complex signal eJwot with Wo > 0 is different from a corresponding signal with Wo < O. Complex signals are similarly difficult for beginners to comprehend, since such signals are not commonly encountered as physical entities. Rather, they usually serve as convenient mathematical representations for real signals of certain types. , in sinusoidal steady-state analysis of electrical circuits). A real voltage Vm cos(wot + >0) is represented by the phasor V = vmeJ