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Abstract : 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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