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Signal processing is a numerical analysis technique that combines math in electrical engineering to represent information. Measurable phenomena that can create a numerical signal can be analyzed, modified, synthesized, and interpreted through signal processing. Examples of signal processing measurement technology include electrocardiograms and other biological measurement equipment, oscilloscopes for sound, seismographs for seismic activity, financial charts, and other tools that depict numerical values that represent a signal along a linear scale.
Signal processing is used in speech recognition, video processing, image processing, wireless communications, process control, financial forecasting, genomics, audio processing, and a variety of additional fields. Additional processes can be added to signal processors to modify or control information that is depicted, including filters and noise reduction technology in efforts to create a better signal. These additional processes can result in a clearer audio recording or to get a better image of the factors that are causing some problems with a system.