From the perspective of the omnipresent information and communication technologies, we are living now in a digital society, but our natural world remains mainly an analog one. Therefore, going from real data sources and transmission channel examples, James Stone intuitively rediscovers for the reader the principles and the elementary mathematical models for measuring, coding, and conveying information for both types of communication systems, discrete and continuous.

The core of the book, focusing first on discrete information sources, presents the definition, evaluation, and interpretation of discrete variable entropy and also source coding principles, illustrated by grey-level images and English text coding examples.

Second, the subject of discrete noisy channels is addressed, including topics such as channel input-output, joint entropy, and mutual information, and an overview on the principles of noisy channel coding is provided.

The next step is to get from discrete random variables to continuous sources and channels via the introduction of uniform, exponential, and Gaussian distribution differential entropies and mutual continuous information concepts. They are used to define channel capacity and to find out the coding function that maximizes the amount of information through the channel.

Following the historical development of information theory, the entropy of a data source is correlated to the entropy of a thermodynamic system in terms of the relationship between the amount of information acquired by a technical or biological system and the smallest quantity of energy expended for that.

Finally, some easy-to-follow examples of information theory within the fields of digital telecommunication, the human genome, and species evolution are presented.

The accessible and cohesive style of presentation, due to the presence of a large number of figures and suggestive examples, a comprehensive glossary, and some useful mathematical appendices, makes the text attractive for those seeking to learn information transmission basics for a better understanding of modern approaches in linguistics, biology, genetics, and neuroscience. On the other hand, taking into account the MATLAB and Python code of the examples and PDF files of the figures used in the text and available online, the book could also serve as support for teaching essential information theory and coding to this type of audience, with no interest in engineering.

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