Highly accurate fluorogenic DNA sequencing with information theory–based error correction

2017 ◽  
Vol 35 (12) ◽  
pp. 1170-1178 ◽  
Author(s):  
Zitian Chen ◽  
Wenxiong Zhou ◽  
Shuo Qiao ◽  
Li Kang ◽  
Haifeng Duan ◽  
...  
2020 ◽  
Author(s):  
Divy S. Kangeyan ◽  
Shile Zhang ◽  
Sigrid Katz ◽  
Brian Crain ◽  
Janel Lee ◽  
...  

Author(s):  
Per Ola Kristensson

In this chapter we explain how methods from statistical language processing serve as a foundation for the design of probabilistic text entry methods and error correction methods. We review concepts from information theory and language modelling and explain how to design a statistical decoder for text entry—a generative probabilistic model based on the token-passing paradigm. We then present five example applications of statistical language processing for text entry: correcting typing mistakes, enabling fast typing on a smartwatch, improving prediction in augmentative and alternative communication, enabling dwell-free eye-typing and intelligently supporting error correction of probabilistic text entry. We then discuss the limitations of the models presented in this chapter and highlight the importance of establishing solution principles based on engineering science and empirical research in order to guide the design of probabilistic text entry.


2021 ◽  
Author(s):  
Aiden Bruen ◽  
Mario Forcinito ◽  
James McQuillan

2011 ◽  
Vol 47 (4) ◽  
pp. 236 ◽  
Author(s):  
A.R. Krishnan ◽  
M. Sweeney ◽  
J. Vasic ◽  
D.W. Galbraith ◽  
B. Vasic

Author(s):  
H. D. Arora ◽  
Anjali Dhiman

In coding theory, we study various properties of codes for application in data compression, cryptography, error correction, and network coding. The study of codes is introduced in Information Theory, electrical engineering, mathematics, and computer sciences for the transmission of data through reliable and efficient methods. We have to consider how coding of messages can be done efficiently so that the maximum number of messages can be sent over a noiseless channel in a given time. Thus, the minimum value of mean codeword length subject to a given constraint on codeword lengths has to be founded. In this paper, we have introduced mean codeword length of orderαand typeβfor 1:1 codes and analyzed the relationship between average codeword length and fuzzy information measures for binary 1:1 codes. Further, noiseless coding theorem associated with fuzzy information measure has been established.


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