presentation on digital signal processing

2.  INTRODUCTION
 TERMS AND COMPONENTS
 WORKING OF DIGITAL SIGNAL PROCESSOR
 COMPARISIONWITH MICROPROCESSORS
 DIGITAL FILTERAND ITSTYPES
 APPLICATIONS

3.  DIGITAL: Operating by the use of discrete signals to
represent data in the form of numbers.
 SIGNAL: A variable parameter by which information is
conveyed through an electronic circuit.
 PROCESSING: To perform operations on data
according to the programmed instructions.
 Digital signal processing :IT can be defined as
analysis, interpretation, and manipulation of signals like
sound, images time-varying measurement values and
sensor data

4.  Converting a continuously changing
waveform (analog) into a series of discrete
levels (digital)

6.  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

7. 0
0.22
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8.  A waveform is sliced up and converted it into
digital form
 Draw a simple waveform on graph paper
 Scale appropriately
 “Gather” digital data points to represent the
waveform

11.  Compare the original with the recreating,
note similarities and differences

12. Raw
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Time
Amplitude
Ave before/after
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Time
Amplitude

14. 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.

15.  A microprocessor with its limited speed is
meant for low speed applications whereas
the DSP is meant for fast real time
applications.
 Generally microprocessors useVan-nuemann
architecture whereas most of the DSP
processors use a modified Harvard
architecture with two or three memory
buses.

16. Texas DSP Processors
16-bit Fixed point arithmetic processors
 TMS320C1X
 TMS320C2X
 TMS320C5X
 TMS320C8X
32-bit floating point arithmetic processors
 TMS320C3X
 TMS320C4X

17. Digital filter:numerical procedure or algorithm
that transforms a given sequence of numbers
into second set of sequence that has some more
desirable properties.
DIGITAL FILTER
INPUT SEQUENCE
Output sequence

18. Broadly speaking ,two types of digital filters
exists.
 FIR Filters(Finite impulse response filters)
 IIR Filters (Infinite Impulse response filters)

22. FIR filter: uses only current and past input digital samples to
obtain a current output sample value. It does not utilize past
output samples. Simple FIR equation is mention below.
y(n)= h(0)x(n) + h(1)x(n-1) + h(2)x(n-2) + h(3)x(n-3) + h(4)x(n-4)
IIR filter: uses current input sample value, past input and output
samples to obtain current output sample value. Simple IIR
equation is mention below.
y(n)= b(0)x(n) + b(1)x(n-1) + b(2)x(n-2) + b(3)x(n-3) + a(1)y(n-1) +
a(2)y(n-2) + a(3)y(n-3)

23. An ideal filter is transmits signal under the
pass band without attenuation and
completely suppress the signal in stop band.
Characteristics –
 it have constant gain in pass band and zero
gain in the stop band.
 It has linear phase response.
 It must be causal .

24. Desired features depend on the application.
INPUT SIGNAL OUTPUT SIGNAL
Generated by sensing Having less noise
Device(microphone) or interference
Speech With reduced
redundancy for better
efficiency of
transmission

25.  An analog filter is constructed using active, passive
components like resistors, capacitors and op amps
but a digital filter constitutes adder, multiplier and delay
elements.
 Digital filters are software programmable, which makes
them easy to build and test.
 Digital filters require only the arithmetic operations of
addition, subtraction, and multiplication.
 Digital filters do not drift with temperature or humidity .
 Digital filters have a superior performance-to-cost ratio.

26. Digital signal processing has variety of
applications in diverse fields like
 Digital filtering
 Spectral analysis
 Speech processing
 Image processing
 Radar processing

27.  Robot control
 Telecommunication
 Consumer electronics
 Biomedical engineering
 Military applications

28. In graphic equalizers sound as well as frequency
levels can varied to produce special sound effects
and compensate for the lower sensitivity of the ear .
• enhancement of edges in images
improve recognition of object (by human or
computer)
edge – a sharp transition in the image brightness,
sharp
transitions in a signal (from Fourier theory) appear as
high-frequency components which can be amplified