Signal processing is an area of electrical engineering, systems engineering and applied mathematics that deals with operations on or analysis of signals, in either discrete or continuous time to perform useful operations on those signals. Signals of interest can include sound, images, timevarying measurement values and sensor data, for example biological data such as electrocardiograms, control system signals, telecommunication transmission signals such as radio signals, and many others. Signals are analog or digital electrical representations of timevarying or spatialvarying physical quantities. In the context of signal processing, arbitrary binary data streams and onoff signals are not considered as signals, but only analog and digital signals that are representations of analog physical quantities.
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Processing of signals includes the following operations and algorithms with application examples^{[1]}:
In communication systems, signal processing may occur at OSI layer 1, the Physical Layer (modulation, equalization, multiplexing, etc) in the seven layer OSI model, as well as at OSI layer 6, the Presentation Layer (source coding, including analogtodigital conversion and data compression).
According to Alan V. Oppenheim and Ronald W. Schafer, the principles of signal processing can be found in the classical numerical analysis techniques of the 17th century. They further state that the "digitalization" or digital refinement of these techniques can be found in the digital control systems of the 1940s and 1950s. ^{[2]}
Analog signal processing is for signals that have not been digitized, as in classical radio, telephone, radar, and television systems. This involves linear electronic circuits such as passive filters, active filters, additive mixers, integrators and delay lines. It also involves nonlinear circuits such as compandors, multiplicators (frequency mixers and voltagecontrolled amplifiers), voltagecontrolled filters, voltagecontrolled oscillators and phaselocked loops.
Discrete time signal processing is for sampled signals that are considered as defined only at discrete points in time, and as such are quantized in time, but not in magnitude.
Analog discretetime signal processing is a technology based on electronic devices such as sample and hold circuits, analog timedivision multiplexers, analog delay lines and analog feedback shift registers. This technology was a predecessor of digital signal processing (see below), and is still used in advanced processing of gigahertz signals.
The concept of discretetime signal processing also refers to a theoretical discipline that establishes a mathematical basis for digital signal processing, without taking quantization error into consideration.
Digital signal processing is for signals that have been digitized. Processing is done by generalpurpose computers or by digital circuits such as ASICs, fieldprogrammable gate arrays or specialized digital signal processors (DSP chips). Typical arithmetical operations include fixedpoint and floatingpoint, realvalued and complexvalued, multiplication and addition. Other typical operations supported by the hardware are circular buffers and lookup tables. Examples of algorithms are the Fast Fourier transform (FFT), finite impulse response (FIR) filter, Infinite impulse response (IIR) filter, Wiener filter and Kalman filter.
Signal Processing for Communications – free online textbook by Paolo Prandoni and Martin Vetterli (2008)
Signal processing is the analysis, interpretation and manipulation of signals. Signals of interest include sound, images, biological signals such as ECG, radar signals, and many others.
Processing of such signals includes storage and reconstruction, separation of information from noise (e.g., aircraft identification by radar), compression (e.g., image compression), and feature extraction (e.g., speechtotext conversion).
For analog signals, signal processing may involve the amplification and filtering of audio signals for audio equipment or the modulation and demodulation of signals for [telecommunications]http://en.wikipedia.org/wiki/Telecommunication. For digital signals, signal processing may involve the compression, error checking and error detection of digital signals.
Signal processing is the analysis, interpretation and manipulation of acquired signals. Acquired signals must to be processed depending on the purpose of measurement, a method of measurement, and a property of acquired signals.
When signals are processed, statistics is used because it's essential to know a distribution of data and represent data by numerical formulas. In other words, to study signal processing, it's demanded to study statistics (like the theory of error, the arithmetical mean, probability, a stochastic variable, accuracy, and detailed drawing, etc.).
In most cases, signals are regular, as it is acquired from electric instruments like telemeter, or communications equipment, etc. But there are also many accidentally occurred irregular signals which make it difficult to find formulas that fit exactly. Here, the irregular means it's hard to predict the result which is not yet occurred. When irregular signals are acquired, photon is necessary, so it is measured, and caculated.
