The signal transmission model is similar to a communication system. It has five essential elements:
-Information source is a source like person or machine who input different kinds of message.
-Transmitter is to encode or tokenize the information mentioned above, into specific pattern that fit the independent medium.
-Channel is the independent medium. Actually the information in the channel is unobservable, but we can control patterns of electrical current for signals so that the signals could be measurable.
-Receiver is to decoding information from the signal or we can say invert the operation of the transmitter.
-Destination is a person or machine who receive the decoded information.
In the theory, one important matter is the design of the transmitter and the receiver which are related to the method for encoding and decoding. In addition, noise is also a factor that the theory focuses on. To overcome the noise source through the transmission and enable error correction, the model adds redundancy, namely uses extra symbols.
However, the model does not include the meaning. When Shannon built the model, he tried to eradicate the meaning of the message and focused on the engineering problem without meaning or semantics which are made by human’s collective practice or shared ideas. When transmission, the information will be converted into bits when transmission and bits could not become information, let alone the meaning, until structured in a encodable pattern and output to human interpretable representations. What’s more, meanings, values, and interpretations are not physical properties or features of a symbolic medium (not an electrical structures); they are inferences and correlations made by symbol using communities. In other words, meaning cannot be in the channel or other physical things. The model only provides an essential abstraction layer in the designs of all electronic and digital systems which the meaning could not be described in.
Like Newton bridged the physics and the formula, Shannon made a bridge between information and uncertainty, entropy and chaos. The bridge made the information into quantities, suitable for use in mathematical formula and finally link the human logic and symbolic values with electronic media. In other words, the theory forms a semiotic system for digital electronic data representation. In the system, representation, or instance, will be tokenized (encoded) and re-tokenize (decoded). However, as I mentioned above, the process only provides abstraction layer in the digital system, but not includes the interpretations of other symbolic structures, like language and graphs. Information theory cannot provide different kinds of abstract layers and cannot interpret instances unrelated to digital things. Therefore, it can only be a subsystem of the whole sign and symbol systems.
Irvine, Introducing Information Theory: The Context of Electrical Signals Engineering and Digital Encoding (2021).
James Gleick, & OverDrive, I. (2011). The Information. Knopf Doubleday Publishing Group. http://api.overdrive.com/v1/collections/v1L2BowAAAC4HAAA1k/products/d46545f2-0229-430c-b61f-314458ac6ed1