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Environmental noise can be any external noise that can potentially impact the effectiveness of communication. [2] These noises can be any type of sight (i.e., car accident, television show), sound (i.e., talking, music, ringtones), or stimuli (i.e., tapping on the shoulder) that can distract someone from receiving the message. [3]
Received noise power, noise at a telecommunications receiver; Circuit noise level, ratio of circuit noise to some reference level; Channel noise level, some measure of noise in a communication channel; Noise-equivalent target, intensity of a target when the signal-to-noise level is 1 [2]
The process of communication can fail in various ways. For example, the message may be distorted by external noise. But errors can also occur at the stages of encoding and decoding when the source does not use the correct signs or when the pattern of decoding does not match the pattern of encoding.
Many models of communication include the idea that a sender encodes a message and uses a channel to transmit it to a receiver. Noise may distort the message along the way. The receiver then decodes the message and gives some form of feedback. [1] Models of communication simplify or represent the process of communication.
Different types of noise are generated by different devices and different processes. Thermal noise is unavoidable at non-zero temperature (see fluctuation-dissipation theorem), while other types depend mostly on device type (such as shot noise, [1] [3] which needs a steep potential barrier) or manufacturing quality and semiconductor defects, such as conductance fluctuations, including 1/f noise.
Throughout the communication process, the message is subject to irrelevant factors that can distort or interfere with its reception. Noise is the physical or Psychological fundamentals either from inside or outside of the process of communication. Noise acts as a barrier as it makes the message less accurate, less productive and unclear.
For example, in wireless communications the channel is often modeled by a random attenuation (known as fading) of the transmitted signal, followed by additive noise. The attenuation term is a simplification of the underlying physical processes and captures the change in signal power over the course of the transmission.
In signal processing theory, Gaussian noise, named after Carl Friedrich Gauss, is a kind of signal noise that has a probability density function (pdf) equal to that of the normal distribution (which is also known as the Gaussian distribution). [1] [2] In other words, the values that the noise can take are Gaussian-distributed.