11 Facts About Signal processing

Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals such as sound, images, and scientific measurements.

Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted signals, subjective video quality and to detect or pinpoint components of interest in a measured signal.

Signal processing matured and flourished in the 1960s and 1970s, and digital signal processing became widely used with specialized digital signal processor chips in the 1980s.

Analog signal processing is for signals that have not been digitized, as in most 20th-century radio, telephone, and television systems.

Continuous-time signal processing is for signals that vary with the change of continuous domain .

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Methods of signal processing include time domain, frequency domain, and complex frequency domain.

Discrete-time signal processing is for sampled signals, defined only at discrete points in time, and as such are quantized in time, but not in magnitude.

Analog discrete-time signal processing is a technology based on electronic devices such as sample and hold circuits, analog time-division multiplexers, analog delay lines and analog feedback shift registers.

Concept of discrete-time signal processing refers to a theoretical discipline that establishes a mathematical basis for digital signal processing, without taking quantization error into consideration.

Nonlinear signal processing involves the analysis and processing of signals produced from nonlinear systems and can be in the time, frequency, or spatio-temporal domains.

Statistical signal processing is an approach which treats signals as stochastic processes, utilizing their statistical properties to perform signal processing tasks.