Lecture One Flashcards Preview

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Flashcards in Lecture One Deck (34):
1

What is a signal?

The representation of how a quantity i.e pressure, voltage etc changes over time

2

Describe the recording of a signal:

1) Capture (Data Acquisition)
2) Filter (Signal Conditioning)
3) Measure (Feature Extraction)
4) Question (Hypothesis testing)

3

What does Data Acquisition break down into?

1) Signal transduction
2) Conditioner
- A/D converter-
3) Sampler
4) Quantizer

4

What is transduction?

Converts one form of energy i.e pressure into another i.e voltage


Voltage used as this is the only format computers can use

5

What is notable about the output of the transducer signal?

The analogue voltage (output) waveform of a transducer should be identical to the original waveform

6

Convert degrees to radians;

90 = Pi/2 radians
180 = Pi radians
270 = 3 Pi / 2 radians
360 = 2 Pi

7

What is trig?

SohCahToa

Opposite = Y
Adjacent = X


X = A cos (2ft . Phase)
Y = A sin (2ft . Phase)

8

What are signals most commonly?

Sinusoidal

9

How can a sinusoid wave be described?

Amplitude (A)
Frequency (Hz)
Phase

10

What is phase?

Amount a sinusoid has been shifted relative to another

(in radians)

11

Are all periodic signals sinusoidal?

Not all periodic (cyclic) signals are sinusoidal HOWEVER, all periodic signals can be constructed by superpostion (summation) of sinusoids of different frequencies, amplitudes and phases.

12

What sort of signals are not periodic?

Transient signals

13

Describe each stage of the data acquisition in terms of notation?

Conditioner x(t)
Sampler x[n]
Quantizer Xq[n]

14

What conditions do x(t) meet?

original signal/waveform
Continuous in both time (t) and value (amplitude)

15

What conditions do x[n]?

Sampled signal
Discrete-time (fixed number of samples), but continuous value (amplitude)
n(also N) denotes a single sample

16

What conditions do Xq[n]?

Discrete in bothtime and value
Sampled and quantized signal
‘Final’ computer-friendly format

17

Why do sample?

We sample an analogue signal to get it to a form suitable for storage and processing on a computer

Analogue to Digital conversion (A/D converter; ADC)

18

Describe sampling notation?

Sampling interval (sampling period; T) is the time interval between samples (e.g. xseconds)

Sampling frequency (fs) is the number of samples in a second (e.g. xHz)

19

Whats the problem with too many samples?

If too many samples are made (oversampling), then the resulting dataset could be unmanageable (storage and/or processing)

Less of a problem these days (computer storage is getting cheaper)

20

Whats the problem with too few samples?

It should be obvious that too few samples will result in a poor representation of the original signal

Remember that our transducer selection should also ensure that transducer voltage output reflects original signal –so too should the sampled data

21

What is aliasing?

When a sinusoid is sampled at too low a frequency, a sinusoid of lower frequency results

22

What is the equation for aliasing?

Fresult = Fsample- f original

Check slide for further examples

23

What does aliasing result in?

High frequency components will be aliased to low-frequency components and will interact with genuine low-frequency components

Irreversible loss of information (i.e. unable to reconstruct original signal)

Destructive (out of phase) or constructive (in phase)

24

What is the nyquist criterion?

If a signal contains no frequencies higher than W, then the original can be reconstructed when sampled at 2W

Typically sample at greater frequency than 2Wto be safe

25

What is nyquist frequency?

NyquistFrequency is one half the sampling frequency, and is the highest frequency component that can be accurately reconstructed)

26

Does nyquist sampling prevent aliasing?

it will not prevent aliasing occurring

27

What can generate aliasing when sampling rate is good?

High frequency noise (> Nyquistfrequency) present (but unwanted) in the original signal will be aliased to low-frequencies (from 0 Hz to Nyquistfrequency)

28

What can avoid aliasing?

This aliasing can be avoided using a filter to remove (or attenuate) frequency components from the signal prior to sampling

29

What are the two base systems used?

Base ten (10^0-3) i.e 142 = 1x10^2 + 4x10^1 + 2 x10 ^ 0 (1-4 numbers)

Base Two (1-8 Numbers)

2^(0-7)

30

What is quantization?

A quantizertakes a discrete-time (x-axis), continuous-value (y-axis) signal x[n] and produces a quantized value xq[n] that can only take a finite number of values (look at slides if necessary)


Produces an interger from a real number

31

What can happen during quantization?

Clipping can also occur if the signal x[n] is greater or less than the largest or smallest integer value

32

What is the typical AD converter?

Typically 12 or 16 bit A/D converters these days (reduce error)

33

What is the error associated with quantiziation?

There is an error associated with quantization (q[n])

q[n] is the difference between original and quantized signal

34

What is the max error proportional to?

Maximum quantization error (Q) is proportional to the number of bits of A/D conversion

q = max x - min x / 2^n-1