1. DIGITAL SIGNAL PROCESSING
DIGITAL SIGNAL PROCESSOR
FUNDAMENTALS

2. Introduction What is DSP ?
DSP(Digital signal processor) is used to manipulate real- world signals after they have been converted into a digital form.
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3. 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
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4. 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
(iv) higher operating speed
* Greater flexibility: Reprogrammable , no need to modify the hardware
* Superior performance
ie. linear phase response can be achieved
complex adaptive filtering becomes possible
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5. DSP designs can be expensive, especially when large bandwidth signals
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.
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6. DSPs Features High speed DSP computations
Specialized instruction set
High performance repetitive numeric calculations
Fast & efficient memory accesses
Special mechanism for real-time I/O
Low power consumption
Low cost in comparison with GPPs
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7. The entire input signal resides in the computer as the same time.
Off-line processing
The entire input signal resides in the computer as the same time.
All of the information is simultaneously available to the processing program.
Example : medical imaging, such as computed tomography and MRI.
PC and mainframes.
On-line processing
The output signal is produced at the same time that the input signal is being acquired. E.g. telephone, radar, hearing aids.
Real-time applications must be have the information immediately available,although it can be delayed by a short amount.
Real-time applications is input a sample, perform the algorithm, and output a sample, over-and-over.
This is the world of Digital Signal Processors.
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8. Time between samples = 1/40KHz =25 microseconds
The definition of real-time depends on the applications, for instance, an Audio application
Requires a sampling frequency of 40 KHz.
Needing 100 serial instructions to complete and using a DSP processor with 30 ns cycle time.
Then in 3 microseconds the calculation is completed.
Time between samples = 1/40KHz =25 microseconds
100 instructions
3 microseconds
Waiting time
Sample n+1
Sample n
What applications DSP can do?
Complex system control.
Multimedia processing (Video ,Audio ,Speech , Image , etc.)
Intelligent signal processing using soft computing(Fuzzy inference, Neural networks, etc.)
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9. DSPs General Applications
Digital cellular phones
Satellite communications
Seismic analysis
Vehicle collision avoidance
Secure communications
Voice over Internet
Tape less answering machines
Motor control
Sonar
Voice mail
Digital cameras
Navigation equipment
Modems (POTS, ISDN, cable,...)
Audio production
Noise cancellation
Videoconferencing
Medical ultrasound
Music synthesis, effects
Radar
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10. DSPs μPs Applications Speech and audio compression Filtering
Modulation and demodulation
Error correction coding and decoding
Audio processing (e.g., surround sound, noise reduction, equalization, sample rate conversion, echo cancellation)
Signaling (e.g., DTMF detection)
Speech recognition
Signal synthesis (e.g., music, speech synthesis)
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11. DSPs Characteristics Data path & internal ALU architecture
Specialized instruction set
External memory architecture
Specialized addressing modes
Specialized execution control
Specialized peripherals for DSP
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12. 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 Adaptive equalization scanners UMTS ADPCM trans-coders EEG brain mappers digital television Spread spectrum ECG Analysis digital cameras Video conferencing X-Ray storage/enhancement internet phone etc.
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13. TYPES OF DSP PROCESSORS
• 32-BIT FLOATING POINT (5% of market):
– TI TMS320C3X, TMS320C67xx
– AT&T DSP32C
– ANALOG DEVICES ADSP21xxx
– Hitachi SH-4
• 16-BIT FIXED POINT (95% of market):
– TI TMS320C2X, TMS320C62xx
– Infineon TC1xxx (TriCore1)
– MOTOROLA DSP568xx, MSC810x
– ANALOG DEVICES ADSP21xx
– Agere Systems DSP16xxx, Starpro2000
– LSI Logic LSI140x (ZPS400)
– Hitachi SH3-DSP
– Star Core SC110, SC140
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14. END
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