Abstract. In this paper, the main measure, an amount of information, of the information theory is analyzed and corrected. The three conceptions of the theory on the microstate, dissipation path-ways, and self-organization levels with a tight connection to the statistical physics are discussed. The concepts of restricted information were introduced as well as the proof of uniqueness of the entropy function, when the probabilities are rational numbers, is presented. The artificial neural network (ANN) model for mapping the evaluation of transmitted information has been designed and experimentally approbated in the biological area. Key words: information theory, entropy, amount of information, artificial neural networks. 1
ABSTRACT During the last twenty years, Akaike\u27s Information Criterion (AIC) has had a fundamental...
According to the classical efficient-coding hypothesis, biological neurons are naturally adapted to ...
This report is a survey of information representations in both biological and artificial neural netw...
In this paper, the main measure, an amount of information, of the information theory is analyzed and...
This chapter discusses the role of information theory for analysis of neural networks using differen...
Information theory is a practical and theoretical framework developed for the study of communication...
The goal of this thesis was to investigate how information theory could be used to analyze artificia...
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This ...
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This ...
This report is a survey of information representations in both biological and artificial neural netw...
Neuroscience extensively uses the information theory to describe neural communication, among others,...
Information theory is a practical and theoretic framework developed for the study of communication o...
that has attracted a number of researchers is the mathematical evaluation of neural networks as info...
© World Scientific Publishing CompanyThe information channel capacity of neurons is calculated in th...
Sensitive or unstable information has an impact in life in various fields, and they have the potenti...
ABSTRACT During the last twenty years, Akaike\u27s Information Criterion (AIC) has had a fundamental...
According to the classical efficient-coding hypothesis, biological neurons are naturally adapted to ...
This report is a survey of information representations in both biological and artificial neural netw...
In this paper, the main measure, an amount of information, of the information theory is analyzed and...
This chapter discusses the role of information theory for analysis of neural networks using differen...
Information theory is a practical and theoretical framework developed for the study of communication...
The goal of this thesis was to investigate how information theory could be used to analyze artificia...
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This ...
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This ...
This report is a survey of information representations in both biological and artificial neural netw...
Neuroscience extensively uses the information theory to describe neural communication, among others,...
Information theory is a practical and theoretic framework developed for the study of communication o...
that has attracted a number of researchers is the mathematical evaluation of neural networks as info...
© World Scientific Publishing CompanyThe information channel capacity of neurons is calculated in th...
Sensitive or unstable information has an impact in life in various fields, and they have the potenti...
ABSTRACT During the last twenty years, Akaike\u27s Information Criterion (AIC) has had a fundamental...
According to the classical efficient-coding hypothesis, biological neurons are naturally adapted to ...
This report is a survey of information representations in both biological and artificial neural netw...