A signal is any
variable that carries information. Examples of the types of signals of interest
are Speech (telephony, radio, everyday communication), Biomedical signals (EEG
brain signals), Sound and music, Video and image,_ Radar signals (range and
bearing).
Digital signal
processing (DSP) is concerned with the digital representation of signals and
the use of digital processors to analyse, modify, or extract information from signals.
Many signals in DSP are derived from analogue signals which have been sampled
at regular intervals and converted into digital form. The key advantages of DSP
over analogue processing are Guaranteed accuracy (determined by the number of
bits used), Perfect reproducibility, No drift in performance due to temperature
or age, Takes advantage of advances in semiconductor technology, Greater
exibility (can be reprogrammed without modifying hardware), Superior
performance (linear phase response possible, and_ltering algorithms can be made
adaptive), Sometimes information may already be in digital form. There are
however (still) some disadvantages, Speed and cost (DSP design and hardware may
be expensive, especially with high bandwidth signals) Finite word length
problems (limited number of bits may cause degradation).
Application
areas of DSP are considerable: _ Image processing (pattern recognition, robotic
vision, image enhancement, facsimile, satellite weather map, animation), Instrumentation
and control (spectrum analysis, position and rate control, noise reduction,
data compression) _ Speech and audio (speech recognition, speech synthesis,
text to Speech, digital audio, equalisation) Military (secure communication,
radar processing, sonar processing, missile guidance) Telecommunications (echo
cancellation, adaptive equalisation, spread spectrum, video conferencing, data
communication) Biomedical (patient monitoring, scanners, EEG brain mappers, ECG
analysis, X-ray storage and enhancement).
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