Handbook of Unconventional Computing

10.1142/12232 ◽  
2021 ◽  
Author(s):  
Andrew Adamatzky
Keyword(s):  
Unconventional Computing

Feedforward Micro-Extended-Analog-Computer Array

2012 ◽  
Vol 263-266 ◽  
pp. 1304-1309
Author(s):  
Jia Si Wang ◽  
Ying Zhang ◽  
Di Ming Ai ◽  
Feng Pan
Keyword(s):  
Research And Development ◽  
Pattern Classification ◽  
Numerical Experiments ◽  
Classification Problem ◽  
Analog Computer ◽  
Unconventional Computing ◽  
Particle Swarm Optimizer ◽  
Computing Model ◽  
Classic Pattern ◽  
Array Structure

The micro-Extended-Analog-Computater(uEAC) is a newly emergent unconventional computing model under research and development. Although, a single uEAC unit can achieve some classic pattern classification problem, the slop of the classification face generated by uEAC is a constant and moves parallely. So a feedforward array structure is proposed for the improvement of uEAC, and Particle Swarm Optimizer(PSO) is utilized to configure the uEAC array. The analysis of the mapping characteristics and numerical experiments both illustrate the effectiveness of the improvement.

Design Method for Unconventional Computing

2006 ◽  
Author(s):  
Lambert Spaanenburg ◽  
Benny Akesson ◽  
Andreas Hansson ◽  
Kees Goossens
Keyword(s):  
Design Method ◽  
Unconventional Computing

scholarly journals Understanding memristive switching via in situ characterization and device modeling

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Wen Sun ◽  
Bin Gao ◽  
Miaofang Chi ◽  
Qiangfei Xia ◽  
J. Joshua Yang ◽  
...  
Keyword(s):  
Recent Progress ◽  
Device Modeling ◽  
Device Performance ◽  
Unconventional Computing ◽  
Large Parameter ◽  
In Situ Characterization ◽  
Research Attention ◽  
Non Volatile Memory ◽  
Synergistic Approach

Abstract Owing to their attractive application potentials in both non-volatile memory and unconventional computing, memristive devices have drawn substantial research attention in the last decade. However, major roadblocks still remain in device performance, especially concerning relatively large parameter variability and limited cycling endurance. The response of the active region in the device within and between switching cycles plays the dominating role, yet the microscopic details remain elusive. This Review summarizes recent progress in scientific understanding of the physical origins of the non-idealities and propose a synergistic approach based on in situ characterization and device modeling to investigate switching mechanism. At last, the Review offers an outlook for commercialization viability of memristive technology.

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