To understand the information theory and its application in the engineering field, we must forget its daily life meaning, which represents the knowledge obtained during investigation and instruction. Signal transmission or processing happens when the content we send or receive in any form of electrical formations like text, sounds, images, films… and even the files we uploaded and converted these into signals. The main feature is simple but puts simple steps repeatedly into layers and layers, contributing to complex transmission functions. First, the message source takes the content, refers to the codebook, and turns the content but detached the meanings into electric signals, then the abstract signals pass through the psychical wires or tubes for transmitting these signals to the destinations. Before I finish this. “
end to end” signal journey, the password will be transferred back to the content with meanings that apply to the social environment using the same codebook (Martell, 2015).

As professor Irvine mentioned in his article: “The model provides an essential abstraction layer…The meaning and social uses of communication are left out of the signal transmission model because they are everywhere assumed or presupposed as what motivates using signals and E-information at all” (Irvine, 2020). For this reason, I think to expect another practical sense of why the signal-code transmission model is not a description of meaning may also relate to the limitation of signal transformation. According to Shannon’s A Mathematical Theory of Communication, the large amount of signal will reduce its accuracy and activity due to the long-distance process of transforming. And the interference like noise will also disturb its preciseness. Two ways to solve it are using enough energy to boost a strong enough signal not to get affected by surrounding irrelevant signal resources. The second is to have bandwidth large enough to allow these massive amounts of signal to pass through without getting deducted.

Speaking of big data, the description of meaning applied in social content represents a lot of information if conducted into signals. That’s why Shannon uses “bit” instead of other decimal systems. It leaves the machines less opportunity to make mistakes and gives them more chance to represent more meanings and contents by reducing the input choices. Because the more we use as input, the less we get as output. And the reason why the information theory is only sufficient as substrates is that without the comprehension of semiotic meaning human uses every day, it loses the purpose of encoding, decoding, and transforming.

References 

Denning, P. J., & Martell, C. H. (2015). Great principles of computing. The MIT Press.

Irvine, M. (2020). Introduction to Computer System Design.