Inicio  /  Information  /  Vol: 15 Par: 1 (2024)  /  Artículo
ARTÍCULO
TITULO

Is Short-Term Memory Made of Two Processing Units? Clues from Italian and English Literatures down Several Centuries

Emilio Matricciani    

Resumen

We propose that short-term memory (STM), when processing a sentence, uses two independent units in series. The clues for conjecturing this model emerge from studying many novels from Italian and English Literature. This simple model, referring to the surface of language, seems to describe mathematically the input-output characteristics of a complex mental process involved in reading/writing a sentence. We show that there are no significant mathematical/statistical differences between the two literary corpora by considering deep-language variables and linguistic communication channels. Therefore, the surface mathematical structure of alphabetical languages is very deeply rooted in the human mind, independently of the language used. The first processing unit is linked to the number of words between two contiguous interpunctions, variable Ip, approximately ranging in Miller?s 7 ± 2 range; the second unit is linked to the number of Ip?s contained in a sentence, variable MF, ranging approximately from 1 to 6. The overall capacity required to process a sentence fully ranges from 8.3 to 61.2 words, values that can be converted into time by assuming a reading speed, giving the range 2.6~19.5 s for fast-reading and 5.3~30.1 s for the average reader. Since a sentence conveys meaning, the surface features we have found might be a starting point to arrive at an information theory that includes meaning.

 Artículos similares

       
 
Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu    
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co... ver más
Revista: Aerospace

 
Jia-Ling Xie, Wei-Feng Shi, Ting Xue and Yu-Hang Liu    
The fault detection and diagnosis of a ship?s electric propulsion system is of great significance to the reliability and safety of large modern ships. The traditional fault diagnosis method based on mathematical models and expert knowledge is limited by ... ver más

 
Haibo Chu, Zhuoqi Wang and Chong Nie    
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ... ver más
Revista: Water

 
Shiplu Das, Sanjoy Pratihar, Buddhadeb Pradhan, Rutvij H. Jhaveri and Francesco Benedetto    
The main purpose of a detection system is to ascertain the state of an individual?s eyes, whether they are open and alert or closed, and then alert them to their level of fatigue. As a result of this, they will refrain from approaching an accident site. ... ver más
Revista: Information

 
Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh    
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o... ver más
Revista: Algorithms