Flashcards in Lecture One Deck (34)

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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