According to Claude Shannon, “A Mathematical Theory of Communication”, communication is defined as conversion between energy and order over time, in the context of noise or errors, as follows in Shannon’s “noisy-channel coding theorem”: 

For information source-1 (an order quanta):

→ transmitter converts information source-1 to signal-1 and transmits signal-1 in a channel 

(this can be understood as an order→energy conversion event)

→ noise interacts with signal-1 in the channel to produce signal-2 

(this can be understood as an energy→order→energy event; this is optional) 

→ receiver connected to the channel receives signal-2 and converts signal-2 into information source-2

(this can be understood as an energy→order event) 

If source-1 and source-2 are modeled to be the same, Shannon’s noisy-channel coding theorem determines a rate at which source-1 can be transmitted and found in source-2 for a given data compression (source encoding), a rate of noise in the channel and in the encoding and decoding processes, and for an error correction or channel coding rate at the receiver. 

In general terms, the rate of information transmission is a function of the channel media, how redundant the signal encoding is for error correction purposes, and the level of noise in the system. Above is a simplified model with noise only in the channel; noise may also occur at both ends, during conversion between information source and signal. 

Shannon’s channel coding theorem is used to determine information carrying capacity of genetic code, the spoken word, letters on a page, Morse Code, analog audio and video encoded in radio, and binary code transmitted in various media.

Shannon defines communication as conversion between order and energy and energy and order over time. 

Order is one of the quanta of meaning. Energy is the other quanta of meaning. 

During communication, the two quanta convert, from one to the other, over time.