Digital Signal Processing
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Introduction
Digital Signal Processing (DSP) is the study of digital representation of signals. This is a technique intended to analyze and process real time signals (or analog signals). Analog signals are those, which are represented for all values of time. Digital Signals are obtained from analog signals by a process called Sampling, which involves extracting sample values of the analog signals at regular intervals of time. This process is called Analog-to-Digital Conversion and the system performing this activity is called the Analog-to-Digital Converter (ADC).
DSP makes use of mathematical methods in order to handle and analize the object of study, which are the signals. The use of such mathematical methods allow us to extract information and even modify the signal, in order to use it as we desire. One may ask why is DSP so widespread today and applied in everything around us. The reason is quite simple: there are digital computers at any corner wherever we go. The ease of getting a computer today is so high that almost anyone is able to have such a tool at home. Since digital computers are able to represent only finite quantities, digital signal processing methods developed so fast and had been so widespread.
Some reasons for the application of DSP may include -
- [a] "Cheap" processing due so widespread digital computers;
- [b] Allows the develpoment of fast algorithms;
- [c] Allows the simulation of real filters only using digital circuitry.
--Diego F. G. Coelho (discuss • contribs) 17:18, 2 July 2013 (UTC)
Advantages of DSP
The following are a few of the advantages of Digital Signal Processing:
- [a] Programmability: a digital system can be programmably changed to change the functionality
- [b] Versatility - Ease of upgrading and Flexibility
- [c] Stability (Tolerance)
- [d] Cost effectiveness
- [e] Special applications like lossless compression
- [f] DSP based systems can be easily modified
Limitations of DSP
The following are a few of the limitations of Digital Signal Processing:
- [a] Processing of signals involves more power consumption
- [b] Processing of signals beyond higher frequencies (beyond GHz) and below lower frequencies (a few Hz) involves limitations
- [c] Information is lost because we only take samples of the signal at intervals .