Filter Outline (Chapter 11) Amplitude Ratio Phase Shift
Highpass Filter Frequency Response Bode Plot Draw frequency
response Ch 11.4 Ch 11.1 Ch 11.2 Lowpass Filter Notch Filter
Bandpss Filter
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Review Network Function Output depends on input and complex
frequency s.
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Frequency Response Only focus on the change of frequency In
this lecture, we only focus on s=j. H(j) is the frequency response.
That is, only consider H(j)
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Frequency Response H(j) is a complex number, so frequency
response is usually represented by two curves Magnitude Ratio Phase
Shift
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Example 11.1 Network Function: Frequency Response:
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Example 11.1 Based on Superposition:
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Example 11.1 InputOutput
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Example 11.2 Assume C=1/aR Find Network Function a=1/RC
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Example 11.2 Set s=j The amplitude ratio is constant.
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Example 11.2 Magnitude Ratio Phase Shift Distance of j to a
Distance of j to -a
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Example 11.2 Phase shift network: Waveform distortion
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Another Example for Phase Shift Network
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Computing Frequency Response by Poles and Zeros
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Frequency Response K: gain factor p 1, p 2, : poles z 1, z 2, :
zeros
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Frequency Response - Magnitude Ratio Distance of j to z 1
Distance of j to p 1 Distance of j to p 2 Distance of j to z 2
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Frequency Response - Magnitude Ratio Gain factor is K Magnitude
ratio at =| Gain factor| all distance to zeros all distance to
poles X
Range of Hearing Range of Audio: 300Hz 3.4KHz Frequency Range
of hearing: 20Hz - 20KHz dB
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Equal Loudness Contour Red Curve: Equal loudness Blue Line:
Same Energy 60 phon means as loud as the 60dB 1kHz sound. phon
(unit): dB
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Hearing v.s. Age Application: 68 ( )
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Phase and Sound Pass a Phase shift network
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Structure of Ear
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Cochlea ( ) to brain Each neuron only passes a specific
frequency. Pass high frequency Pass low frequency Pass 20kHz Pass
20Hz
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Cochlea ( ) to brain Neuron for =300 Neuron for =100 Neuron for
=20 =300, Amplitude=10 =20, Amplitude=10
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Machine Hearing Each triangle is the amplitude ratio of a
filter How? Ear of machine A set of filters (filter bank) Energy of
the signal of the output of the filter Send to computer How to
write a program for speech recognition? a. Observe data, and write
down some rules b. Simulate human brain, and let the computer learn
by itself. Feature
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Speech Signal ? ? Acoustic Model Language Model Text Machine
Learning Deep Neural Network (Brain) Features Speech Recognition
Signal Processing (Filter Bank)