<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The aim of our paper is to evaluate the maximum Shannon (syntactic) information carried through a video lecture. To achieve the aim, we have considered a natural lecture delivered by a lecturer as a signal transmitted over the physical communication channel consisting of a sound sub-channel and light sub-channel. Receivers are eyes and ears of listeners whose physical characteristics are taken into account. The physiological, neurological and cognitive aspects of the problem are neglected in calculations. The method has been developed to calculate the absolute maximum values of Shannon information characteristics of a natural lecture basing on the capacity formula of continuous communication channel and physical considerations taken into account for the first time, to our knowledge. Maximum Shannon information characteristics (entropies of sound and light frames, amounts of total acoustical and optical information, capacities of sound and light sub-channels, total amount of information and total capacity) of a natural lecture perceived by the audience have been calculated. These values are the upper bounds of a video lecture. The obtained results are discussed in the paper. After some modification, the proposed method can be practically applied for the optimization of both natural and video lectures because there is some correlation between syntactic and semantic information characteristics.</p>
</abstract>

The aim of our paper is to evaluate the maximum Shannon (syntactic) information carried through a video lecture. To achieve the aim, we have considered a natural lecture delivered by a lecturer as a signal transmitted over the physical communication channel consisting of a sound sub-channel and light sub-channel. Receivers are eyes and ears of listeners whose physical characteristics are taken into account. The physiological, neurological and cognitive aspects of the problem are neglected in calculations. The method has been developed to calculate the absolute maximum values of Shannon information characteristics of a natural lecture basing on the capacity formula of continuous communication channel and physical considerations taken into account for the first time, to our knowledge. Maximum Shannon information characteristics (entropies of sound and light frames, amounts of total acoustical and optical information, capacities of sound and light sub-channels, total amount of information and total capacity) of a natural lecture perceived by the audience have been calculated. These values are the upper bounds of a video lecture. The obtained results are discussed in the paper. After some modification, the proposed method can be practically applied for the optimization of both natural and video lectures because there is some correlation between syntactic and semantic information characteristics.

Maximum Shannon Information Delivered in a Lecture

Faculty of Electronics and Telecommunications

Latvian Journal of Physics and Technical Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Maximum Shannon Information Delivered in a Lecture"}

The aim of our paper is to evaluate the maximum Shannon (syntactic) information carried through a video lecture. To achieve the aim, we have considered a...

Maximum Shannon Information Delivered in a Lecture

Data publikacji: 22 kwi 2022

Zakres stron: 12 - 22

DOI: https://doi.org/10.2478/lpts-2022-0008

Słowa kluczowe
Channel capacity, communication channel, entropy, lecture, semantic information, syntactic information, video lecture

© 2022 L. Alksne et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Maximum Shannon Information Delivered in a Lecture

Data publikacji: 22 kwi 2022

Zakres stron: 12 - 22

DOI: https://doi.org/10.2478/lpts-2022-0008

Słowa kluczoweChannel capacity, communication channel, entropy, lecture, semantic information, syntactic information, video lecture

© 2022 L. Alksne et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Channel capacity, communication channel, entropy, lecture, semantic information, syntactic information, video lecture