Saturday, 1 June 2019

Digital signal processing

Digital signal processing and analog signal processing are subfields of signal processing. DSP applications include audio and speech processing , sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing , digital image processing , signal processing for telecommunication , control systems, biomedical engineering , seismology, among others.
DSP can involve linear or nonlinear operations. Nonlinear signal processing is closely related to non-linear system identification and can be implemented in the time, frequency and spatio-temporal domains.
The application of digital computation to signal processing allows for many advantages over analog processing in many applications, such as error detection and correctiom in transmission as well as data compression. DSP is applicable to both streaming data and static (stored) data.
Anything that carries information can be called as signal. It can also be defined as a physical quantity that varies with time, temperature, pressure or with any independent variables such as speech signal or video signal.
The process of operation in which the characteristics of a signal (Amplitude, shape, phase, frequency, etc.) undergoes a change is known as signal processing.
Note − Any unwanted signal interfering with the main signal is termed as noise. So, noise is also a signal but unwanted.

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