1. Digital Signal Processor
The Heart of Modern Real-Time Control Systems

2. DIGITAL SIGNAL PROCESSING
CHAPTER 1
AN INTRODUCTION TO
DIGITAL SIGNAL PROCESSING

3. What is Digital Signal Processing? Why process signals digitally?
Learning Objectives
What is Digital Signal Processing?
Why process signals digitally?
Definition of a real-time application.
Why use Digital Signal Processing processors?
What are the typical DSP algorithms?
Programmable vs. ASIC DSP.
A DSP system design flow.
Selecting the DSP device.
Texas Instruments’ TMS320 family.

4. What Is Digital Signal Processing ?
The Digital Signal Processing can be defined as:
First detect your signal by an electronic sensor.
Convert it into digital signal using a A/D converter.
Pass it to a Digital Computer or a Digital Signal Processor (DSP).
Make the desired processing operations using the digital processor.
Convert it again to an analogue signal using a D/A converter.
Finally pass the converted signal to an actuator.

5. What Is Digital Signal Processing ?
We can use electronic sensors to convert pressure, sound, temperature, etc.., to electrical signals.
We have to change these into numbers to be passed to a digital computer for processing.
The conversion process is called Analog-to-Digital, or A/D, conversion.
The processing that we apply to the signal is carried out by the digital computer and is thus called Digital Signal Processing, DSP for short.

6. What Is Digital Signal Processing ?
A single-chip microcomputer specially designed for digital processing is usually used.
These special microcomputers are known as Digital Signal Processors, or DSPs for short.
Once the signal has been processed by the DSP it converted back to an analog signal before passed back to an actuator.
This process is called Digital-to-Analog, or D/A, conversion. The complete conversion and processing chain is shown in the following Figure.

7. A Simple Digital Signal Processing System
DSP
A/D
Converter
D/A
Converter
A Simple Digital Signal Processing System

8. Why Go Digital?
Digital signal processing techniques are now so powerful that sometimes it is extremely difficult, if not impossible, for analogue signal processing to achieve similar performance.
Examples:
FIR filter with linear phase.
Adaptive filters.

9. Why Go Digital?
Analogue signal processing is achieved by using analogue components such as:
Resistors.
Capacitors.
Inductors.
The inherent tolerances associated with these components, temperature, voltage changes and mechanical vibrations can dramatically affect the effectiveness of the analogue circuitry.

10. Why Go Digital? With DSP it is easy to: Additionally DSP reduces:
Change applications.
Correct applications.
Update applications.
Additionally DSP reduces:
Noise susceptibility.
Chip count.
Development time.
Cost.
Power consumption.

11. Why Not Go Digital?
High frequency signals cannot be processed digitally because of two reasons:
Analog to Digital Converters, ADC cannot work fast enough.
The application can be too complex to be performed in real-time.

12. Real-Time Processing
DSP processors have to perform tasks in real-time, so how do we define real-time?
The definition of real-time depends on the application.
Example: a 100-tap FIR filter is performed in real-time if the DSP can perform and complete the following operation between two samples:

13. Real-Time Processing
Processing Time
Waiting Time n
n+1
Sample Time
We can say that we have a real-time application if:
Waiting Time  0

14. Why Do We Need DSP Processors?
Why not use a General Purpose Processor (GPP) such as a Pentium instead of a DSP processor?
What is the power consumption of a Pentium and a DSP processor?
What is the cost of a Pentium and a DSP processor?

15. Why Do We Need DSP Processors?
Use a DSP processor when the following are required:
Cost saving.
Smaller size.
Low power consumption.
Processing of many “high” frequency signals in real-time.
Use a GPP processor when the following are required:
Large memory.
Advanced operating systems.

16. What Are The Typical DSP Algorithms?
The Sum of Products (SOP) is the key element in most DSP algorithms:

17. DSP In Space -Space photograph enhancement. -Data compression.
-Intelligent sensory analysis by remote space probes.

18. DSP In Medical -Medical-Diagnostic imaging (CT, MRI, ultra-
sound, and others).
-Electrocardiogram analysis.
-Medical image storage/retrieval.

19. DSP In Commercial -Image and sound compression for multimedia
presentation.
-Movie special effects.
-Video conference calling.

20. DSP In Telephone -Voice and data compression. -Echo reduction.
-Signal multiplexing.
-Filtering.

21. DSP In Military -Radar. -Sonar. -Ordnance guidance.
-Secure communication.

22. DSP In Industrial -Oil and mineral prospecting.
-Process monitoring & control.
-Nondestructive testing.
-CAD and design tools.

23. DSP In Scientific -Earthquake recording & analysis. -Data acquisition.
-Spectral analysis.
-Simulation and modeling.

24. Hardware vs. Microcode Multiplication
DSP processors are optimized to perform multiplication and addition operations.
Multiplication and addition are done in hardware and in one cycle.
Example: 4-bit multiply (unsigned).
Hardware
Microcode
1011
x 1110
1011
x 1110
Cycle 1
0000
1011.
Cycle 2
1011..
Cycle 3
Cycle 4
Cycle 5

25. Floating vs. Fixed Point Processors
Applications which require:
High precision.
Wide dynamic range.
High signal-to-noise ratio.
Ease of use.
Need a floating point processor.
Drawback of floating point processors:
Higher power consumption.
Can be higher cost.
Can be slower than fixed-point counterparts and larger in size.

26. Floating vs. Fixed Point Processors
It is the application that dictates which device and platform to use in order to achieve optimum performance at a low cost.

27. General Purpose DSP vs. DSP in ASIC
Application Specific Integrated Circuits (ASICs) are semiconductors designed for dedicated functions.
The advantages and disadvantages of using ASICs are listed below:
Advantages
Disadvantages
High throughput
Lower silicon area
Lower power consumption
Improved reliability
Reduction in system noise
Low overall system cost
High investment cost
Less flexibility
Long time from design to market

28. Define systems requirements
A DSP System Design Flow
Application
Define systems requirements
Select DSP device
Software
Hardware
Code writing
Schematic
Debug code
Prototype
System integration
System test and debug

29. Selecting The DSP Device
The processing requirements of the system you are to design, which select the DSP device.
Many devices can be eliminated from consecration at an early stage due to lack of power, insufficient resolution, cost and so on.
Texas Insturmants’ TMS320 Family DSPs have a wide range of applications and seems to be a practical solution for many design issues.

30. Texas Instruments’ TMS320 Family
Different families and sub-families exist to support different markets.
Lowest Cost
Control Systems
Motor Control
Storage
Digital Ctrl Systems
C2000
C5000
Efficiency
Best MIPS per
Watt / Dollar / Size
Wireless phones
Internet audio players
Digital still cameras
Modems
Telephony
VoIP
C6000
Multi Channel and Multi Function App's
Comm Infrastructure
Wireless Base-stations
DSL
Imaging
Multi-media Servers
Video
Performance &
Best Ease-of-Use

31. End of
Chapter 1