Introduction to the working principle of signal filter
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2018-03-17
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In signal processing, a filter is a device or process that removes unwanted components or features from a signal. Filtering is a type of signal processing that is characterized by complete or partial suppression of certain aspects of the signal. This usually means removing some frequencies or bands. However, filters are not specific to the frequency domain; in particular, there are many other filtering targets in the field of image processing. Correlation may be for certain frequency components rather than for other frequency components without having to act in the frequency domain. Filters are widely used in electronics and telecommunications, broadcasting, television, recording, radar, control systems, music synthesis, image processing and computer graphics.
Classification filters have many different foundations, and they overlap in many different ways; there is no simple hierarchical classification. The filter might be:
Linear or nonlinear
Time constant or time variable, also known as shift invariance. If the filter is running in the spatial domain, the representation is spatially invariant.
Causality or non-causality: If the current output of the filter depends on future inputs, the filter is non-causal. The filter that processes the time domain signal in real time must be causal, but not the delay processing of the filter or time domain signal acting on the spatial domain signal.
Analog or digital
Discrete time (sampling) or continuous time
Passive or active type continuous time filter
A discrete-time or digital filter of the infinite impulse response (IIR) or finite impulse response (FIR) type.
