06 - Digital Signal Processing

Question 1

What does DSP stand for?

Answer 1

Digital Signal Processing

Question 2

What are some examples of where you might find DSP being used?

Answer 2

Everywhere!
Hearing aids
Otoacoustic systems
Audiometers
Aural rehab software
ABR's
Cell phones
Voice over internet
CD/DVD/DAT players
MP3 players
Biomedical monitoring equipment...

Question 3

How does DSP compare to Analog (e.g. time, amplitude, etc)?

Answer 3

Analog:

• continuous in time
• continuous in amplitude
• circuits deal with continuous voltages and currents

DSP:

• discrete in time
• discrete in amplitude
• circuits deal with “1’s” and “0’s”

Question 4

Analog systems transmit signals from the ______ domain, to the ______ domain, back to the ______ domain

Answer 4

Acoustical
Electrical
Acoustical

Question 5

Name one reason digital systems are so popular?

Answer 5

• Programmability: instructions can be manipulated “on the fly”
• Flexibility: don’t need to rebuild the circuit, like you would with analog
• Advanced signal processing: multichannel compression, precise frequency shaping, feedback cancellation, noise reduction, directional processing
• Features like bluetooth

Question 6

What domains to digital systems cross when processing an acoustic signal?

Answer 6

Acoustic -> Electrical -> Digital -> Electrical -> Acoustic

Question 7

How do we discretize time of an analog signal?

Answer 7

Sampling

Question 8

What does “quantization” refer to?

Answer 8

The discretization of the amplitude of a signal

• the sampled values are converted into bit representation
• the performance of a quantizer is dependent on the number of bits (also called bit resolution)

Question 9

As we increase the frequency of our signal, we need a _______ (slower/faster) sample rate

Answer 9

Faster

Question 10

Describe the Nyquist Sampling Theorem

Answer 10

The sampling rate must be more than 2x the highest frequency of the input signal, otherwise there will be distortion

Question 11

Will a signal processor be able to undo the distortion (aliasing) caused by undersampling?

Answer 11

No

Question 12

What is “aliasing”?

Answer 12

A waveform that is caused by undersampling, and is not actually part of the input signal
- the digital signal processor cannot tell if these come from the true signal or not

Question 13

How do we follow the Nyquist criterion if the highest frequency of a signal is unknown?

Answer 13

Anti-aliasing Filter:

• Use a low pass filter to remove unwanted frequencies
• Set the sampling rate greater than 2x the bandwidth of the low pass filter

Question 14

Are anti-aliasing filters part of the analog or digital circuit?

Answer 14

Analog - they are low pass filters applied before sampling (digital domain)

Question 15

Why don’t we just increase the sampling rate to get better quality phone calls, hearing aids, etc?

Answer 15

Cell phones and hearing aids are working in real time, so the processor has to deal with that many samples each second
-as we increase the sampling rate, it puts constraints on the processor

Question 16

Put the following items in order (lowest to highest), based on their typical sampling rate:
CD player
Cell phone
DVD player
Hearing Aid

Answer 16

Cell phone (8,000 samples/sec)
CD players and Hearing Aids (44,100 samples/sec)
DVD players (96,000 samples/sec)

Question 17

How many “bits” equal a “byte”?

Answer 17

A string of 8 bits = a byte

Question 18

What does the binary string 1101 equal?

Answer 18

1 x 2^3 = 8
1 x 2^2 = 4
0 x 2^1 = 0
1 x 2^0 = 1

= 8+4+0+1 = 13

Question 19

Every time we add one more bit, the number of possibilities (“levels”) _______ (stays the same/doubles/triples)

Answer 19

Doubles

E.g.
2^3 = 8
2^4 = 16
8 x 2 = 16 possibilities

Question 20

Increasing the number of bits increases the ______ of the quantizer

Answer 20

Resolution

Question 21

In quantization, the # of combinations = 2^b where b = _______

Answer 21

b = the number of bits

e.g. 3 bit = 2^3

Question 22

When we’re reverse mapping our digitized signal, the step configuration of the signal is essentially made up of high frequency changes (directly up between 2 points), so how to we reconstruct our analogue wave to smooth it out?

Answer 22

Use low pass filter (high frequency steps are filtered out)

Question 23

Describe the following characteristics of an A/D converter:
Input range
Resolution

Answer 23

Input range - the voltage range that the A/D converter can handle
- can be unipolar (+ve or -ve voltages) or bipolar (+ve and -ve voltages)

Resolution - represented by the number of bits (2^N where N=# of bits)

Question 24

Match the following quantization values to their corresponding modern device:
Telecommunication system, DVD player, Hearing aid

8 bits/sample, 16 bits/sample, 24 bits/sample

Answer 24

Telecommunication system: usually 8 bits/sample

Hearing aids: 16 bits/sample or better

DVD player: 24 bits/sample

Question 25

If an analogue to digital converter was operating in real time and was sampling 8000 samples/second with a quantization of 8 bits/sample, how many bits would it be dealing with per second?

Answer 25

8000 samples/sec x 8 bits/sample = 64000 bits/second

Question 26

True or false: the complete A/D/A setup consists of: | Anti-alias filter -> S/H (sample and hold) -> ADC -> DAC -> S/H -> Reconstruction Filter

Answer 26

True

Question 27

Name one commonly used signal processing technique

Answer 27

Fast Fourier Transform (FFT) for spectral analysis and transfer function measurements Digital filtering and filterbanks for frequency shaping, compression, and noise reduction