Digital signal processing: An experimental approach by Shlomo Engelberg

By Shlomo Engelberg

Digital sign Processing is a mathematically rigorous yet available therapy of electronic sign processing that intertwines uncomplicated theoretical recommendations with hands-on laboratory guide. Divided into 3 elements, the publication covers a number of facets of the electronic sign processing (DSP) "problem". It starts off with the research of discrete-time signs and explains sampling and using the discrete and speedy Fourier transforms. the second one a part of the book—covering electronic to analog and analog to electronic conversion—provides a realistic interlude within the mathematical content material sooner than half III lays out a cautious improvement of the Z-transform and the layout and research of electronic filters.

MATLAB® and Simulink® are hired generally to permit the reader to event the attractive arithmetic underlying this significant self-discipline, and to illustrate the subject’s engineering relevance. the sensible microprocessor-oriented elements of Digital sign Processing are brought with targeted connection with the ADuC841, a lab handbook for which are downloaded from those labs will be simply transposed for different microprocessors. difficulties are supplied on the finish of every bankruptcy and an digital strategies guide is out there for tutors.

Academic tutors of classes in DSP will locate this booklet to be a useful reduction in explaining the basic arithmetic of electronic sign processing and drawing out its importance for engineers. electric and desktop engineers operating in indications- and communications-related fields can use the booklet as a reference or for self-tuition and for deepening their realizing of the concepts they use. Graduate utilized arithmetic, electric, digital and laptop engineering scholars drawn to DSP will study the underlying arithmetic of an important engineering self-discipline and the way to use it in functional laboratory situations.

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N=0 k=0 Because the Xk are independent, zero-mean random variables, we know that if n = k, then E(Xn Xk ) = 0. Thus, we see that the expected value of |a0 |2 is E(|a0 |2 ) = N E(Xk2 ). 1) We would like to examine the variance of |a0 |2 . First, consider E(|a0 |4 ). We find that E(|a0 |4 ) = N E(Xi4 ) + 3N (N − 1)E 2 (Xi2 ). ) Thus, the variance of the measurement is E(|a0 |4 ) − E 2 (|a0 |2 ) = N E(Xi4 ) + 2N 2 E 2 (Xi2 ) − 3N E 2 (Xi2 ) 2 2 = N σX − N )E 2 (Xi2 ). 2 + 2(N Clearly, the variance of |a0 |2 is O(N 2 ), and the standard deviation of |a0 |2 is O(N ).

We find that for 0 ≤ n ≤ N − 1, N −1 e−2πjm(n−k)/N = m=0 N, 1−e2πj(n−k) 1−e−2πj(n−k)/N n=k = N δnk = 0, otherwise where δnk = 1, n = k, and δnk = 0, n = k. ) We find that ak = N yk . That is, we find that yk = ak /N = N −1 1 N e+2πjkm/N Ym . m=0 This mapping of sequences is known as the inverse discrete Fourier transform (IDFT), and it is almost identical to the DFT. 2, we found that the DFT of the sequence {−1, 1, −1, 1} is {Ym } = {0, 0, −4, 0}. Using the IDFT, we find that y0 = 1 (−4) = −1 4 3 1 eπj/2 y1 = 4 m=0 3 y2 = 1 eπj 4 m=0 y3 = 1 e3πj/2 4 m=0 3 m m Ym = Ym = m 1 (−1) · (−4) = 1 4 1 1 · (−4) = −1 4 Ym = 1 (−1) · (−4) = 1.

Examine the output of each program when the input to the system is a sinewave. Explain the results in terms of the properties of the window function and the DFT. 10 Exercises 1. Use the definition of the Fourier transform to calculate the Fourier transform of ΠT (t). 2. Use the MATLAB wintool command to compare the Hann window and the Hamming window. 3. Calculate the Fourier transform of the function w(t) = ΠT (t)(1 + cos(2πt/T )). 4. Calculate the windowed DFT of the sequence sin(2πf nTs ), n = 0, .

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