2. What is DSP?
Converting a continuously changing waveform
(analog) into a series of discrete levels (digital)
3. What is DSP?
The analog waveform is sliced into equal segments
and the waveform amplitude is measured in the middle
of each segment
The collection of measurements make up the digital
representation of the waveform
5. Binary Search
The speed the binary search is accomplished depends
on:
The clock speed of the ADC
The number of bits resolution
Can be shortened by a good guess (but usually is not
worth the effort)
6. How Does It Work?
Faithful Duplication
Now that we can slice up a waveform and convert it
into digital form, let’s take a look at how it is used in
DSP
Draw a simple waveform on graph paper
Scale appropriately
“Gather” digital data points to represent the waveform
10. How Does It Work?
Faithful Duplication
Compare the original with the recreating, note
similarities and differences
11. How Does It Work?
Faithful Duplication
Once the waveform is in digital form, the real power of
DSP can be realized by mathematical manipulation of
the data
Using EXCEL spreadsheet software can assist in
manipulating the data and making graphs quickly
Let’s first do a little filtering of noise
12. How Does It Work?
Faithful Duplication
Using your raw digital data, create a new table of data
that averages three data points
Average the point before and the point after with the point
in the middle
Enter all data in EXCEL to help with graphing
14. How Does It Work?
Faithful Duplication
Let’s take care of some static crashes that cause some
interference
Using your raw digital data, create a new table of data
that replaces extreme high and low values:
Replace values greater than 100 with 100
Replace values less than -100 with -100
15. Modulation
Discrete signals are rarely transmitted over long distances or stored
in large quantities in their raw form.
Signals are normally modulated to match their frequency
characteristic to those of the transmission and/or storage media to
minimize signal distortion, to utilize the available bandwidth
efficiently, or to ensure that the signal have some desirable
properties.
Two application areas where the idea of modulation is extensively used
are:
1. telecommunications
16. Three most commonly used digital modulation schemes for
transmitting
Digital data over bandpass channels are:
Amplitude shift keying (ASK)
Phase shift keying (PSK)
Frequency shift keying (FSK)
When digital data is transmitted over an all digital
network a scheme known
As pulse code modulation (PCM) is used.
17. Digital Signal Processing And Its Benefits
By a signal we mean any variable that carries or contains some kind
of information that can be conveyed, displayed or manipulated.
Examples of signals of particular interest are:
- speech, is encountered in telephony, radio, and everyday life
- biomedical signals, (heart signals, brain signals)
- Sound and music, as reproduced by the compact disc player
- Video and image,
- Radar signals, which are used to determine the range and bearing
of distant targets
18. Attraction of DSP comes from key advantages such as :
* Guaranteed accuracy: (accuracy is only determined by the
number of bits used)
* Perfect Reproducibility: Identical performance from unit to unit
ie. A digital recording can be copied or reproduced several
times with no
loss in signal quality
* No drift in performance with temperature and age
* Uses advances in semiconductor technology to achieve:
(i) smaller size
(ii) lower cost
(iii) low power consumption
19. Disadvantages of DSP
* Speed and Cost
DSP designs can be expensive, especially when large bandwidth signals
are involved. ADC or DACs are either to expensive or do not have sufficient
resolution for wide bandwidth applications.
* DSP designs can be time consuming plus need the necessary resources
(software etc)
* Finite word-length problems
If only a limited number of bits is used due to economic considerations
serious degradation in system performance may result.
21. Convolution
Convolution is one of the most frequently used operations in DSP.
Specially in digital filtering applications where two finite and causal
sequences x[n] and h[n] of lengths N1 and N2 are convolved
0
][][][][][][][
kk
knxkhknxkhnxnhny
where, n = 0,1,…….,(M-1) and M = N1 + N2 -1
This is a multiply and accumulate operation and DSP device
manufacturers have developed signal processors that perform this
action.
22. Correlation
There are two forms of correlation :
1. Auto-correlation
2. Cross-correlation
1. The cross-correlation function (CCF) is a measure of the similarities or shared
properties between two signals. Applications are cross-spectral
analysis, detection/recovery of signals buried in noise, pattern matching etc.
Given two length-N sequences x[k] and y[k] with zero means, an estimate of their
cross-correlation is given by:
,...2,1,0
00 2
1 n
rr
nr
n
yyxx
xy
xy
Where, rxy(n) is an estimate of the cross covarience
23. The cross-covarience is defined as
1
0
2
1
0
2
1
0
1
0
][
1
)0(,][
1
)0(
,...2,1,0][][
1
,...2,1,0][][
1
N
k
yy
N
k
xx
nN
k
nN
k
xy
ky
N
rkx
N
r
nkynkx
N
nnkykx
Nnr
24. 2. An estimate of the auto-correlation of an length-N sequence
x[k] with zero mean is given by
][nxx
2,1,0,
]0[
][
][ n
r
nr
n
xx
xx
xx
25. Application Areas
Image Processing Instrumentation/Control Speech/Audio
Military
Pattern recognition spectrum analysis speech recognition secure
communications
Robotic vision noise reduction speech synthesis radar
processing
Image enhancement data compression text to speech sonar
processing
Facsimile position and rate digital audio missile guidance
animation control equalization
Telecommunications Biomedical Consumer applications
Echo cancellation patient monitoring cellular mobile phones
