Aya K, Nakahama H, Fujii H
Biol Cybern. 1985;52(6):357-66. doi: 10.1007/BF00449592.
The operations of encoding and decoding in communication agree with filtering operations of convolution and deconvolution for Gaussian signal processing. In an analogy with power transmission in thermodynamics, an autoregressive model of information transmission is proposed for representing a continuous communication system which requires a pair of an internal noise source and a signal source to encode or decode a message. In this model transinformation (informational entropy) equals the increase in stationary nonequilibrium organization formed through the amplification of white noise by a positive feedback system. The channel capacity is finite due to the existence of inherent noise in the system. The maximum entropy criterion in information dynamics corresponds to the 2nd law of thermodynamics. If the process is stationary, the communication system is invertible, and has the maximum efficiency of transformation. The total variation in informational entropy is zero in the cycle of the invertible system, while in the noninvertible system the entropy of decoding is less than that of encoding. A noisy autoregressive coding which maximizes transinformation is optimum, but is also ideal.
通信中的编码和解码操作与高斯信号处理中的卷积和反卷积滤波操作一致。类似于热力学中的功率传输，提出了一种信息传输的自回归模型，用于表示一个连续通信系统，该系统需要一对内部噪声源和信号源来对消息进行编码或解码。在这个模型中，互信息（信息熵）等于通过正反馈系统对白噪声进行放大而形成的稳态非平衡组织的增加量。由于系统中存在固有噪声，信道容量是有限的。信息动力学中的最大熵准则对应于热力学第二定律。如果过程是平稳的，通信系统是可逆的，并且具有最大的变换效率。在可逆系统的循环中，信息熵的总变化为零，而在不可逆系统中，解码的熵小于编码的熵。使互信息最大化的有噪自回归编码是最优的，但也是理想的。
