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The Shannon–Weaver model is one of the earliest models of communication. [2] [3] [4] It was initially published by Claude Shannon in his 1948 paper "A Mathematical Theory of Communication". [5] The model was further developed together with Warren Weaver in their co-authored 1949 book The Mathematical Theory of Communication.
Shannon–Weaver model of communication [86] The Shannon–Weaver model is another early and influential model of communication. [10] [32] [87] It is a linear transmission model that was published in 1948 and describes communication as the interaction of five basic components: a source, a transmitter, a channel, a receiver, and a destination.
Berlo's model was influenced by earlier models like the Shannon–Weaver model and Schramm's model. [17] [18] [19] Other influences include models developed by Theodore Newcomb, Bruce Westley, and Malcolm MacLean Jr. [20] [4] [17] The Shannon–Weaver model was published in 1948 and is one of the earliest and most influential models of ...
Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise) This work is known for introducing the concepts of channel capacity as well as the noisy channel coding theorem. Shannon's article laid out the basic elements of communication:
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]
The foundation of the uncertainty reduction theory stems from the information theory, originated by Claude E. Shannon and Warren Weaver. [2] Shannon and Weaver suggests, when people interact initially, uncertainties exist especially when the probability for alternatives in a situation is high and the probability of them occurring is equally high. [6]
In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible (in theory) to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel.
In information theory, the Shannon–Hartley theorem tells the maximum rate at which information can be transmitted over a communications channel of a specified bandwidth in the presence of noise. It is an application of the noisy-channel coding theorem to the archetypal case of a continuous-time analog communications channel subject to ...