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Learning Introductory Signal Processing Using Multimedia
1
Outline•Overview of Information and Communications
•Some signal processing concepts
•Tools available for use in the laboratory
•A selection of exercises
Learning Introductory Signal Processing Using Multimedia
Roger Browne
Institute of Information Sciences and Technology Massey University
Learning Introductory Signal Processing Using Multimedia
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Overview of Information and Communications
The learning outcomes involve describing:
• the nature of information
• how information can be measured
• a basic communication systems model
• the nature of noise and its affect on communications
• A/D and D/A conversion, signals, modulation and Fourier theory
• some common coding schemes and how they can be used to combat the affect of noise
•application of discrete mathematics to simple linear systems
A second year paper that underpins the BTech (Information Engineering) and BE (Information and Telecommunication Engineering) degrees
Learning Introductory Signal Processing Using Multimedia
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Overview of Information and Communications
The learning outcomes involve describing:
• the nature of information
• how information can be measured
• a basic communication systems model
• the nature of noise and its affect on communications
• A/D and D/A conversion, signals, modulation and Fourier theory
• some common coding schemes and how they can be used to combat the affect of noise
• application of discrete mathematics to simple linear systems
The relevant sections are:
Learning Introductory Signal Processing Using Multimedia
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Some signal processing concepts
Source Encoder Tx Rx Decoder Output
Channel
+
Noise Usually electronic noise
Standard communications model:
Learning Introductory Signal Processing Using Multimedia
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Some signal processing concepts
Time domain and frequency domain views of signals
Time domain:
Learning Introductory Signal Processing Using Multimedia
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Some signal processing concepts
Time domain and frequency domain views of signals
Frequency domain:
Learning Introductory Signal Processing Using Multimedia
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Some signal processing concepts
Conversion from analogue to digital involves:
• sampling
• aliasing
Learning Introductory Signal Processing Using Multimedia
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Tools
• PC and its multi-media facilities (sound card, microphone, speakers)
• Signal processing software (Matlab)
• Very sophisticated personal signal processing facilities:
(our ears)
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Exercise One: Spectrum Analysis
Square wave:
This has been studied using Fourier analysis in lectures
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Sound Recorder
Document
Sound of a square wave:
Spectrum of a square wave
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Spectrum of a square wave
A filter selects a range of frequencies.
For instance, selecting frequencies between 500Hz and 2000Hz results in a different sound:
Sound Recorder
Document
Filtered signal at original volume:
Amplified version of filtered signal:
Learning Introductory Signal Processing Using Multimedia
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Viewing this in frequency space: Sound Recorder
Document
Learning Introductory Signal Processing Using Multimedia
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Exercise Two - Noise in Communications
Noise usually refers to electronic noise, but could be acoustic noise.
Sound Recorder
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Original signal:
SNR = 0dB
SNR = -10dB
Sound Recorder
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Sound Recorder
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Learning Introductory Signal Processing Using Multimedia
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Sound Recorder
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SNR = -20dB
SNR = -30dB Sound Recorder
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•The signal frequency is 1300Hz
•The noise is ‘wide-band’ or ‘white’ noise, occupying the full frequency spectrum.
Objective: design a filter to retrieve the signal in the case of SNR = -30dB
Noise in Communications
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Noise in Communications
Technique: develop a narrow-band filter centred on 1300Hz.
Sound Recorder
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Filter = 1200Hz to 1400Hz:
Filter = 1290Hz to 1310Hz:
Filter = 1298Hz to 1302Hz:
Sound Recorder
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Sound Recorder
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Learning Introductory Signal Processing Using Multimedia
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Sound Recorder
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What about noisy speech signals?
Noise in Communications
Original:
SNR = 0dB:
Band-pass filter, 200Hz to 1500Hz:
Sound Recorder
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Sound Recorder
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No amount of filtering achieves a clear speech signal
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Noise in Communications
The way in which the frequencies are spread across the spectrum can be viewed pictorially:
Hence a narrow-band filter is not effective.
Learning Introductory Signal Processing Using Multimedia
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Exercise Three - Aliasing
This is a concept that students often find difficult.
It is a characteristic of the process of converting from an analogue signal to a digital signal.
A fundamental law in signal processing states that the sampling frequency must be at least twice the highest frequency present in the signal.
For example, CDs are sampled at 44.1kHz so the highest frequency that can be present in the signal is 22kHz.
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Aliasing
If a higher frequency is present it ‘folds over’ into the lower frequencies.
This can be illustrated by taking a simple signal of 1000Hz and steadily reducing the sampling frequency.
The minimum sampling frequency for correctly recording the sound is 2000Hz.
Learning Introductory Signal Processing Using Multimedia
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Aliasing
Sound Recorder
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Original:
Sampled at 3000Hz:
Sampled at 1800Hz:
Sampled at 1500Hz:
Sampled at 1200Hz:
Sound Recorder
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Sound Recorder
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Students are asked to estimate the frequency in each case.
Sound Recorder
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Sound Recorder
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(1000Hz)
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Aliasing
Their estimates are plotted against sampling frequency:
1000Hz 2000Hz
Sampling frequency
Est
imat
ed f
requ
ency
1000Hz
normal
aliased
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Aliasing
What is the affect on speech?
Original:
Sampled at 2000Hz:
Sampled at 1000Hz:
Filtered 0-500Hz:
Sound Recorder
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Sound Recorder
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Sound Recorder
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Frequencies greater than 500Hz sound as lower frequencies, creating distortion
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• The modern multimedia computer offers excellent facilities for basic experiments in signal processing.
• By making use of:
� audible signals
� the sophisticated signal processing of the human ear,
a number of basic concepts can be exemplified in a concrete and readily-assimilated form.
Conclusions