Chapter 9, FREQUENCY TRANSFORMATIONS Video Solutions, Design and Analysis of Analog Filters: A Signal Processing Perspective | Numerade (2024)

Paarmann L.D.

Chapter 9

FREQUENCY TRANSFORMATIONS - all with Video Answers

Educators

Chapter Questions

Problem 1

Similar to Example 9.1, determine the transfer function of 3rd-order Butterworth lowpass filter with $\mathrm{an}_c$ of $5000 \mathrm{rad} / \mathrm{s}$.

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Problem 2

Determine the transfer function of a 3rd-order Chebyshev Type I lowpass filter with $A_p=1.5 d B$ and $\omega_p=1000 \mathrm{rad} / \mathrm{s}$.

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Problem 3

Repeat Problem 9.2 for $\omega_c=1000 \mathrm{rad} / \mathrm{s}$.

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Problem 4

Determine the poles for the transfer function of Problem 9.1.

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Problem 5

Determine the poles for the transfer function of Problem 9.2.

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Problem 6

Determine the poles for the transfer function of Problem 9.3.

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Problem 7

Given that the desired specifications of a Butterworth lowpass filter are as follows: $\quad A_p=3 \mathrm{~dB}, \quad A_s=70 \mathrm{~dB}, \quad \omega_p=2,500 \mathrm{rad} / \mathrm{s}, \quad$ and $\omega_s=10,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=3 d B, A_s=70 d B$, $f_p=6,500 \mathrm{~Hz}$, and $f_s=26 \mathrm{kHz}$.

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Problem 8

Given that the desired specifications of a Chebyshev Type I lowpass filter are as follows: $A_p=1.2 \mathrm{~dB}, \quad A_s=75 \mathrm{~dB}, \quad \omega_p=3,500 \mathrm{rad} / \mathrm{s}, \quad$ and $\omega_s=7,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=1.2 d B, A_s=75 d B$, $f_p=6,500 \mathrm{~Hz}$, and $f_s=13 \mathrm{kHz}$.

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04:55
Problem 9

Determine the Filter Selectivity, $F_S$, for each of the two filters in Problem 9.7.

Chapter 9, FREQUENCY TRANSFORMATIONS Video Solutions, Design and Analysis of Analog Filters: A Signal Processing Perspective | Numerade (11)

Amit Srivastava

Numerade Educator

04:55
Problem 10

Determine the Filter Selectivity, $F_S$, for each of the two filters in Problem 9.8.

Chapter 9, FREQUENCY TRANSFORMATIONS Video Solutions, Design and Analysis of Analog Filters: A Signal Processing Perspective | Numerade (14)

Amit Srivastava

Numerade Educator

Problem 11

Determine the Shaping Factor, $S_a^b$, for each of the two filters in Problem 9.7, where $a=3 d B$ and $b=70 d B$.

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Problem 12

Determine the Shaping Factor, $S_a^b$, for each of the two filters in Problem 9.8, where $a=1.2 d B$ and $b=75 d B$.

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Problem 13

Indicate how Figure 3.8 could be used to obtain the plot of phase delay for each of the two filters in Problem 9.7.

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Problem 14

Indicate how Figure 3.9 could be used to obtain the plot of group delay for each of the two filters in Problem 9.7.

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Problem 15

Indicate how Figure 3.10 could be used to obtain the plot of the unit impulse response for each of the two filters in Problem 9.7.

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Problem 16

Indicate how Figure 3.11 could be used to obtain the plot of the unit step response for each of the two filters in Problem 9.7.

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Problem 17

Similar to Example 9.2, determine the transfer function of 3rd-order Butterworth highpass filter with an $\omega_c$ of $5000 \mathrm{rad} / \mathrm{s}$.

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Problem 18

Determine the transfer function of a 3rd-order Chebyshev Type I highpass filter with $A_p=1.5 d B$ and $\omega_p=1000 \mathrm{rad} / \mathrm{s}$.

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Problem 19

Repeat Problem 9.18 for $\omega_c=1000 \mathrm{rad} / \mathrm{s}$.

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Problem 20

Determine the poles and zeros for the transfer function of Problem 9.17.

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Problem 21

Determine the poles and zeros for the transfer function of Problem 9.18.

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Problem 22

Determine the poles and zeros for the transfer function of Problem 9.19.

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Problem 23

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.17.

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Problem 24

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.18.

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Problem 25

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.19.

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Problem 26

Using MATLAB, plot the magnitude frequency response and the phase response for the highpass filter of Example 9.3.

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Problem 27

Given that the desired specifications of a Butterworth highpass filter are as follows: $A_p=3 d B, \quad A_s=70 d B, \quad \omega_{s_{H P}}=2,500 \mathrm{rad} / \mathrm{s}, \quad$ and $\omega_{p_{H P}}=10,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=3 d B, A_s=70$ $d B, f_{s_{H P}}=6,500 \mathrm{~Hz}$, and $f_{p_{H P}}=26 \mathrm{kHz}$.

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Problem 28

Given that the desired specifications of a Chebyshev Type I highpass filter are as follows: $A_p=1.2 \mathrm{~dB}, \quad A_s=75 \mathrm{~dB}, \quad \omega_{s_{d I P}}=3,500 \mathrm{rad} / \mathrm{s}$, and $\omega_{p_{H P}}=7,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specífications. Repeat the above for $A_p=1.2 \mathrm{~dB}, A_s=75 \mathrm{~dB}$, $f_{s_{H P}}=6,500 \mathrm{~Hz}$, and $f_{p_{H P}}=13 \mathrm{kHz}$.

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Problem 29

Determine the Filter Selectivity of the highpass filter of Problem 9.17 in two ways: (a) by use of (9.14) and (3.7), and (b) computationally, using MATLAB.

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Problem 30

Determine the Filter Selectivity of the highpass filter of Problem 9.18 in two ways: (a) by use of (9.14) and (4.9), and (b) computationally, using MATLAB.

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Problem 31

Determine the Filter Selectivity of the highpass filter of Problem 9.19 in two ways: (a) by use of (9.14) and (4.9), and (b) computationally, using MATLAB.

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Problem 32

Determine the Shaping Factor of the highpass filter of Problem 9.17 in two ways: (a) by use of (9.15) and (3.10), and (b) computationally, using MATLAB.

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Problem 33

Determine the Shaping Factor of the highpass filter of Problem 9.18 in two ways: (a) by use of (9.15) and (4.12), and (b) computationally, using MATLAB.

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Problem 34

Determine the Shaping Factor of the highpass filter of Problem 9.19 in two ways: (a) by use of $(\mathbf{9 . 1 5})$ and (4.12), and (b) computationally, using MATLAB.

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Problem 35

For the Butterworth highpass filter of Problem 9.17, determine a closed-form expression for the group delay, similar to Example 9.4. Using MATLAB, plot the response of your expression. For comparison, determine and plot the group delay response as obtained by computational manipulation of the phase response (the traditional computational approach).

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Problem 36

Using MATLAB, plot the magnitude frequency response, phase response, phase delay response, group delay response, unit impulse response, and unit step response for a 10th-order Chebyshev Type I highpass filter with $A_p=1 d B$ and $\omega_{p_{H P}}=1000 \mathrm{rad} / \mathrm{s}$. That is, confirm the results plotted in Figure 9.1 through ${ }^{\text {HPp }}$ Figure 9.7 (Example 9.6).

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Problem 37

Similar to Example 9.11, determine the poles and zeros of an 8th-order Butterworth bandpass filter, with $\omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$.

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Problem 38

Determine the poles and zeros of a 6th-order Chebyshev Type I bandpass filter, with $1 \mathrm{~d} B$ of ripple, $\omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$.

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Problem 39

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.37.

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Problem 40

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.38.

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Problem 41

Given that the desired specifications of a Butterworth bandpass filter are as follows: $\quad A_p=3 d B, \quad A_s=70 d B, \quad B_p=2,500 \mathrm{rad} / \mathrm{s}, \quad$ and $B_s=10,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=3 d B, A_s=70$ $d B, B_p=6,500 \mathrm{~Hz}$, and $B_s=26 \mathrm{kHz}$.

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Problem 42

Given that the desired specifications of a Chebyshev Type I bandpass filter are as follows: $A_p=1.2 \mathrm{~dB}, A_s=75 \mathrm{~dB}, \quad B_p=3,500 \mathrm{rad} / \mathrm{s}$, and $B_s=7,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=1.2 \mathrm{~dB}, A_s=75 \mathrm{~dB}$, $B_p=6,500 \mathrm{~Hz}$, and $B_s=13 \mathrm{kHz}$.

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Problem 43

Determine the Filter Selectivity of the bandpass filter in Problem 9.41 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.31) and (3.7), and (b) computationally, using MATLAB.

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Problem 44

Repeat Problem 9.43 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 45

Determine the Filter Selectivity of the bandpass filter in Problem 9.42 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.31) and (4.9), and (b) computationally, using MATLAB.

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Problem 46

Repeat Problem 9.45 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 47

Determine the Shaping Factor of the bandpass filter in Problem 9.41 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.32) and (3.10), and (b) computationally, using MATLAB.

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Problem 48

Repeat Problem 9.47 for $\omega_0=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 49

Determine the Shaping Factor of the bandpass filter in Problem 9.42 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.32) and (4.12), and (b) computationally, using MATLAB.

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Problem 50

Repeat Problem 9.49 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 51

Using the closed-form procedure of Example 9.14 , compute the group delay of a 6th-order Butterworth bandpass filter at $\omega_{p_1}, \omega_{p_2}$, and $\omega_o$ where $\omega_o=5000 \mathrm{rad} / \mathrm{s}$ and $B_p=500 \mathrm{rad} / \mathrm{s}$.

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Problem 52

Using MATLAB, plot the magnitude frequency response, phase response, phase delay response, group delay response, unit impulse response, and unit step response for a 10th-order Chebyshev Type II bandpass filter with $A_p=3 \mathrm{~dB}, A_s=80 \mathrm{~dB}, \omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$. That is, confirm the results plotted in Figure 9.8 through Figure 9.14 (Example 9. 15).

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Problem 53

Similar to Example 9.20 , determine the poles and zeros of an 8th-order Butterworth bandstop filter, with $\omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$.

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Problem 54

Determine the poles and zeros of a 6th-order Chebyshev Type I bandstop filter, with $1 \mathrm{~dB}$ of ripple, $\omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$.

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Problem 55

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.53.

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Problem 56

Using MATLAB, plot the magnitude frequency response and the phase response for the filter of Problem 9.54.

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Problem 57

Given that the desired specifications of a Butterworth bandstop filter are as follows: $\quad A_p=3 \mathrm{~dB}, \quad A_{\mathrm{s}}=70 \mathrm{~dB}, \quad B_{\mathrm{s}}=2,500 \mathrm{rad} / \mathrm{s}, \quad$ and $B_p=10,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=3 d B, A_s=70$ $d B, \quad B_s=6,500 \mathrm{~Hz}$, and $B_p=26 \mathrm{kHz}$

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Problem 58

Given that the desired specifications of a Chebyshev Type I bandstop filter are as follows: $A_p=1.2 \mathrm{~dB}, \quad A_s=75 \mathrm{~dB}, \quad B_s=3,500 \mathrm{rad} / \mathrm{s}$, and $B_p=7,000 \mathrm{rad} / \mathrm{s}$, determine the minimum required filter order to meet or exceed these specifications. Repeat the above for $A_p=1.2 d B, A_s=75 d B$, $B_s=6,500 \mathrm{~Hz}$, and $B_p=13 \mathrm{kHz}$.

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Problem 59

Determine the Filter Selectivity of the bandstop filter in Problem 9.57 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.45) and (3.7), and (b) computationally, using MATLAB.

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Problem 60

Repeat Problem 9.59 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 61

Determine the Filter Selectivity of the bandstop filter in Problem 9.58 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.45) and (4.9), and (b) computationally, using MATLAB.

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Problem 62

Repeat Problem 9.61 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 63

Determine the Shaping Factor of the bandpass filter in Problem 9.57 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.46) and (3.10), and (b) computationally, using MATLAB.

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Problem 64

Repeat Problem 9.63 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 65

Determine the Shaping Factor of the bandpass filter in Problem 9.58 with $\omega_o=15,000 \mathrm{rad} / \mathrm{s}$ in two ways: (a) by use of (9.46) and (4.12), and (b) computationally, using MATLAB.

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Problem 66

Repeat Problem 9.65 for $\omega_o=10,000 \mathrm{rad} / \mathrm{s}$.

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Problem 67

Using (9.48), and the procedure in Example 9.22, compute the group delay of a 6th-order Butterworth bandstop filter at $\omega_{p_1}, \omega_{p_2}$, and $\boldsymbol{D C}$, where $\omega_o=5000 \mathrm{rad} / \mathrm{s}$ and $B_p=500 \mathrm{rad} / \mathrm{s}$.

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Problem 68

Using MATLAB, plot the magnitude frequency response, phase response, phase delay response, group delay response, unit impulse response, and unit step response for a 10th-order elliptic bandstop filter with $A_p=1 d B$, $A_s=80 \mathrm{~dB}, \omega_o=1000 \mathrm{rad} / \mathrm{s}$, and $B_p=200 \mathrm{rad} / \mathrm{s}$. That is, confirm the results plotted in Figure 9.15 through Figure 9.21 (Example 9.23).

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Chapter 9, FREQUENCY TRANSFORMATIONS Video Solutions, Design and Analysis of Analog Filters: A Signal Processing Perspective | Numerade (2024)

FAQs

Is it possible to design digital filters from analog filters if yes how? ›

Digital filters can be designed using analog design methods by following these steps: Filter specifications are specified in the digital domain. The filter type (highpass, lowpass,bandpass etc.) is specified. An equivalent lowpass filter is designed that meets these specifications.

How does an analog filter work? ›

They use the frequency response of a measuring system to alter the dynamic characteristics of a signal. A common instrumentation filter application is the attenuation of high frequencies to avoid frequency aliasing in the sampled data. Filters can be broadly classified as: Low-pass eliminate high frequency components.

What is the formula for digital signal processing? ›

y(n)=x(n)*h(n) Page 12 DIGITAL SIGNAL PROCESSING Page 12 Z transform: The convolution property of z transform of the convolution of input and impulse response is equa to the product of their individual z transforms. i.e the response y(n) of an LTI system is obtained by taking inverse Z transform of X(Z) and H(Z).

What is the subject of digital signal processing? ›

Digital signal processing (DSP) refers to various techniques for improving the accuracy and reliability of digital communications. This can involve multiple mathematical operations such as compression, decompression, filtering, equalization, modulation and demodulation to generate a signal of superior quality.

What is the difference between analog and digital signal filtering? ›

Analog filters can offer several advantages over digital filters, such as the ability to handle high-frequency signals without aliasing, a faster response time and lower latency, a lower power consumption and a smaller size, as well as a higher dynamic range and lower noise.

How to convert analog filter to digital? ›

The procedure consists of three main parts: first the state-space of the analog filter is computed based on diagram or netlist of the analog circuit, then a conversion from analog domain to digital domain is used. Finally the digital filter is delivered in system function form.

What math do you need for DSP? ›

To be able to perform these tasks, some knowledge of trigonometric functions, complex numbers, complex analysis, linear algebra, and statistical methods is required.

What math is used in signal processing? ›

Definitely calculus, statistics and probability. Linear algebra too, linear algebra is always good to know. What math content do signals and systems cover (e.g. calculus, etc.)? Most introductory courses in Signals and Systems require Calculus, Linear Algebra, and Complex Analysis basics.

Is digital signal processing hard? ›

DSP appears hard because of its mathematical basis and inherent operations. The best way to learn DSP is to understand the physics behind any DSP routine and its application.

What is taught in signal processing? ›

Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, images, potential fields, seismic signals, altimetry processing, and scientific measurements.

What is the difference between analog signal processing and digital signal processing? ›

The major difference between both signals is that the analog signals have continuous electrical signals, while digital signals have non-continuous electrical signals. The difference between analog and digital signal can be observed with the examples of different types of waves.

What is digital signal processing for dummies? ›

Digital Signal Processing converts signals from real world sources (usually in analog form) into digital data that can then be analyzed. Analysis is performed in digital form because once a signal has been reduced to numbers, its components can be isolated and manipulated in more detail than in analog form.

What are the methods used for digitizing the analog filter into a digital filter? ›

Which of the following methods are used to convert analog filter into digital filter? Explanation: There are many techniques which are used to convert analog filter into digital filter of which some of them are Approximation of derivatives, bilinear transformation, impulse invariance and many other methods.

Which filter design involves both analog and digital filters? ›

Explanation: IIR filters have infinite-duration impulse responses, hence they can be matched to analog filters, all of which generally have infinitely long impulse responses. The basic techniques of IIR filter design transform well-known analog filters into digital filters using complex-valued mappings..

What are the methods of analog filter design? ›

The filter design methods are:
  • Butterworth — The magnitude response of a Butterworth filter is maximally flat in the passband and monotonic overall. ...
  • Chebyshev I — The magnitude response of a Chebyshev I filter is equiripple in the passband and monotonic in the stopband.

How IIR filters are designed from analog filters? ›

IIR filter design primarily concentrates on the magnitude response of the filter and regards the phase response as secondary. The most common design method for digital IIR filters is based on designing an analogue IIR filter and then converting it to an equivalent digital filter.

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