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Chapter 5 Frequency Domain Analysis of Systems

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Consider the following CT LTI system: absolutely integrable,Assumption: the impulse response h(t) is absolutely integrable, i.e., CT, LTI Systems system stability (this has to do with system stability)

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What’s the response y(t) of this system to the input signal We start by looking for the response y c (t) of the same system to Response of a CT, LTI System to a Sinusoidal Input

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The output is obtained through convolution as Response of a CT, LTI System to a Complex Exponential Input

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By defining it is Therefore, the response of the LTI system to a complex exponential is another complex exponential with the same frequency The Frequency Response of a CT, LTI System is the frequency response of the CT, LTI system = Fourier transform of h(t)

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Since is in general a complex quantity, we can write Analyzing the Output Signal y c (t) output signal’s magnitude output signal’s phase

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With Euler’s formulas we can express x(t) as Using the previous result, the response is Response of a CT, LTI System to a Sinusoidal Input

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Response of a CT, LTI System to a Sinusoidal Input – Cont’d If h(t) is real, then and Thus we can write y(t) as

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Thus, the response to is amplitudescaled by the factor which is also a sinusoid with the same frequency but with the amplitude scaled by the factor and with the phase shifted by amount Response of a CT, LTI System to a Sinusoidal Input – Cont’d

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Suppose that the frequency response of a CT, LTI system is defined by the following specs: Example: Response of a CT, LTI System to Sinusoidal Inputs

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If the input to the system is Then the output is Example: Response of a CT, LTI System to Sinusoidal Inputs – Cont’d

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Consider the RC circuit shown in figure Example: Frequency Analysis of an RC Circuit

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From EEE2032F, we know that: complex impedance 1.The complex impedance of the capacitor is equal to 2.If the input voltage is, then the output signal is given by Example: Frequency Analysis of an RC Circuit – Cont’d

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Setting, it is whence we can write where Example: Frequency Analysis of an RC Circuit – Cont’d and

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The knowledge of the frequency response allows us to compute the response y(t) of the system to any sinusoidal input signal since Example: Frequency Analysis of an RC Circuit – Cont’d

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Suppose that and that Then, the output signal is Example: Frequency Analysis of an RC Circuit – Cont’d

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Suppose now that Example: Frequency Analysis of an RC Circuit – Cont’d Then, the output signal is

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Example: Frequency Analysis of an RC Circuit – Cont’d lowpass filter The RC circuit behaves as a lowpass filter, by letting low- frequency sinusoidal signals pass with little attenuation and by significantly attenuating high-frequency sinusoidal signals

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periodic signalSuppose that the input to the CT, LTI system is a periodic signal x(t) having period T Fourier seriesThis signal can be represented through its Fourier series as Response of a CT, LTI System to Periodic Inputs where

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By exploiting the previous results and the linearity of the system, the output of the system is Response of a CT, LTI System to Periodic Inputs – Cont’d

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Example: Response of an RC Circuit to a Rectangular Pulse Train Consider the RC circuit with input

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We have found its Fourier series to be with Example: Response of an RC Circuit to a Rectangular Pulse Train – Cont’d

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Magnitude spectrum of input signal x(t) Example: Response of an RC Circuit to a Rectangular Pulse Train – Cont’d

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The frequency response of the RC circuit was found to be Thus, the Fourier series of the output signal is given by Example: Response of an RC Circuit to a Rectangular Pulse Train – Cont’d

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filter more selective

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Example: Response of an RC Circuit to a Rectangular Pulse Train – Cont’d filter more selective

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Example: Response of an RC Circuit to a Rectangular Pulse Train – Cont’d filter more selective

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Consider the following CT, LTI system Its I/O relation is given by which, in the frequency domain, becomes Response of a CT, LTI System to Aperiodic Inputs

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magnitude spectrumFrom, the magnitude spectrum of the output signal y(t) is given by phase spectrum and its phase spectrum is given by Response of a CT, LTI System to Aperiodic Inputs – Cont’d

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Example: Response of an RC Circuit to a Rectangular Pulse Consider the RC circuit with input

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The Fourier transform of x(t) is Example: Response of an RC Circuit to a Rectangular Pulse – Cont’d

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The response of the system in the time domain can be found by computing the convolution where Example: Response of an RC Circuit to a Rectangular Pulse – Cont’d

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filter more selective

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Example: Attenuation of High- Frequency Components

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The response of a CT, LTI system with frequency response to a sinusoidal signal FilteringFiltering: if or then or Filtering Signals is

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Four Basic Types of Filters lowpass bandstop bandpass highpass passband cutoff frequency stopband stopband

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Filters are usually designed based on specifications on the magnitude response The phase response has to be taken into account too in order to prevent signal distortion as the signal goes through the system linear phase no distortionIf the filter has linear phase in its passband(s), then there is no distortion Phase Function

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Consider the ideal sampler: It is convenient to express the sampled signal as where Ideal Sampling..

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Thus, the sampled waveform is is an impulse train whose weights (areas) are the sample values of the original signal x(t) Ideal Sampling – Cont’d

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Fourier seriesSince p(t) is periodic with period T, it can be represented by its Fourier series Ideal Sampling – Cont’d sampling frequency (rad/sec) where

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Therefore and whose Fourier transform is Ideal Sampling – Cont’d

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Suppose that the signal x(t) is bandlimited with bandwidth B, i.e., Then, if the replicas of in interpolation filter do not overlap and can be recovered by applying an ideal lowpass filter to (interpolation filter) Signal Reconstruction

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Interpolation Filter for Signal Reconstruction

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The impulse response h(t) of the interpolation filter is and the output y(t) of the interpolation filter is given by Interpolation Formula

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But whence Moreover, Interpolation Formula – Cont’d

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A CT bandlimited signal x(t) with frequencies no higher than B can be reconstructed from its samples if the samples are taken at a rate The reconstruction of x(t) from its samples is provided by the interpolation formula Shannon’s Sampling Theorem

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The minimum sampling rate is called the Nyquist rate Question: Why do CD’s adopt a sampling rate of 44.1 kHz? Answer: Since the highest frequency perceived by humans is about 20 kHz, 44.1 kHz is slightly more than twice this upper bound Nyquist Rate

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Aliasing

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Because of aliasing, it is not possible to reconstruct x(t) exactly by lowpass filtering the sampled signal Aliasing results in a distorted version of the original signal x(t) It can be eliminated (theoretically) by lowpass filtering x(t) before sampling it so that for Aliasing –Cont’d

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