Digital Signal Processing

The term known as (DSP) or Digital signal processing is concerned with the representation of signals by a sequence of numbers or symbols and the processing of these signals.  Analog signal and Digital signal processing are subfields of signal processing. DSP consists of subfields like: audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, control of systems, biomedical signal processing, seismic data processing, etc.

The ultimate aim of DSP is to measure, filter and/or compress continuous real-world analog signals. The first process is to convert the signal from an analog to a digital form, by sampling it using an analog-to-digital converter (ADC), which turns the analog signal into a stream of numbers. The required output signal is another analog output signal requires a digital-to-analog converter (DAC).  The Digital signal processing process is more complex than analog processing and has a discrete value range, the application of computational power to digital signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression.

Digital Signal Processing Domains:

In digital signal processing, the engineers usually study digital signals in one of the following domains: time domain (one-dimensional signals), spatial domain (multidimensional signals), frequency domain, autocorrelation domain, and wavelet domains. They choose such domain in which to process a signal by making an informed guess (or by trying different possibilities) as to which domain best represents the essential characteristics of the signal. A sequence that of many samples from a measuring device produces a time or spatial domain representation, whereas a discrete Fourier transform produces the frequency domain information, which is the frequency spectrum. Autocorrelation is known as the cross correlation of the signal with itself over varying intervals of time or space.