Robust Computation of 3D Apollonius Diagrams

2020 ◽  
Vol 39 (7) ◽  
pp. 43-55
Author(s):  
Peihui Wang ◽  
Na Yuan ◽  
Yuewen Ma ◽  
Shiqing Xin ◽  
Ying He ◽  
...  
Keyword(s):  
2017 ◽  
Author(s):  
Soumya Banerjee

An immune system inspired Artificial Immune System (AIS) algorithm is presented, and is used for the purposes of automated program verification. Relevant immunological concepts are discussed and the field of AIS is briefly reviewed. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invariants encapsulate the computability of a particular program, e.g. whether it performs a particular function correctly and whether it terminates or not. This work also lays the foundation for applying concepts of theoretical incomputability and undecidability to biological systems like the immune system that perform robust computation to eliminate pathogens.


2019 ◽  
Vol 116 (3) ◽  
pp. 91a
Author(s):  
Harsh Bhatia ◽  
Helgi I. Ingolfsson ◽  
Timothy S. Carpenter ◽  
Felice C. Lightstone ◽  
Peer-Timo Bremer

2008 ◽  
Vol 16 ◽  
pp. C79-C88
Author(s):  
Hiroyuki Nakamura ◽  
Masatake Higashi ◽  
Mamoru Hosaka

2002 ◽  
Vol 38 (22) ◽  
pp. 1314 ◽  
Author(s):  
L. Tarassenko ◽  
L. Mason ◽  
N. Townsend

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Andreea Sterian ◽  
Alexandru Toma

For modeling and controlling dynamic phenomena it is important to establish with higher accuracy some significant quantities corresponding to the dynamic system. For fast phenomena, such significant quantities are represented by the derivatives of the received signals. In case of advanced computer modeling, the received signal should be filtered and converted into a time series corresponding to the estimated values for the dynamic system through a sampling procedure. This paper will show that present-day methods for computing in a robust manner the first derivative of a received signal (using an oscillating system working on a limited time interval and a supplementary differentiation method) can be extended to the robust computation of higher order derivatives of the received signal by using a specific set of second-order oscillating systems (working also on limited time intervals) so as estimative values for higher-order derivatives are to be directly generated (avoiding the necessity of additional differentiation or amplifying procedures, which represent a source of supplementary errors in present-day methods).


2019 ◽  
Vol 81 ◽  
pp. 61-72 ◽  
Author(s):  
Yunku Kang ◽  
Seung-Hyun Yoon ◽  
Min-Ho Kyung ◽  
Myung-Soo Kim

2020 ◽  
Vol 69 (4) ◽  
pp. 4417-4425
Author(s):  
Zhikun Wu ◽  
Bin Li ◽  
Zesong Fei ◽  
Zhong Zheng ◽  
Bin Li ◽  
...  

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