Primarily because of its advantages, Digital Signal Processing (DSP) is now becoming a first choice in many technologies and applications, such as consumer electronics, communications, wireless telephones, and medical imaging.
In addition, DSP approach makes it possible to convert an inexpensive personal computer into a powerful signal processor. System using the DSP approach can be developed using software running on a general-purpose computer. In consequence, DSP is relatively convenient to develop and test, and the software is portable.
Most DSP operations can be categorized as being either signal analysis tasks or signal filtering tasks:
Signal analysis: This tasks deal with the measurement of signal properties. It is generally a frequency-domain operation. Some of its applications are:
- Spectrum (frequency or/and phase analysis)
- Speech recognition
- Speaker verification
- Target detection
Signal filtering: This task is characterized by the signal-in signal-out situation. The systems that perform this task are generally called filters. It is usually (but not always) a time-domain operation. Some of the applications are:
- Removal of unwanted background noise
- Removal of interference
- Separation of frequency bands
- Shaping of the signal spectrum
In some applications, such as voice synthesis, a signal is first analyzed to study its characteristics, which are the used in digital filtering to generate a synthetic voice.
Following:
Source:
- Digital Signal Processing Using Matlab, 3erd ed
Literature review by:
Prof. Larry Francis Obando – Technical Specialist – Educational Content Writer
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