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903 results on '"Sirakoulis, Georgios Ch."'

204. Unconventional Logic on Memristor-Based Oscillatory Medium

Author

Panagiotis Chatzinikolaou, Theodoros, primary, Fyrigos, Iosif-Angelos, additional, Ntinas, Vasileios, additional, Kitsios, Stavros, additional, Bousoulas, Panagiotis, additional, Tsompanas, Michail-Antisthenis, additional, Tsoukalas, Dimitris, additional, and Sirakoulis, Georgios Ch., additional

Published
2021
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205. An Interactive Cellular Automata Based Application to Foster Sustainable Forms of Movement in the Urban Fabric.

Author

GEORGIADI, IRENE, GEORGOUDAS, IOAKEIM G., TRUNFIO, GIUSEPPE A., and SIRAKOULIS, GEORGIOS CH.

Abstract

This study presents an application that estimates all possible paths within an urban environment and proposes the optimal one according to objective criteria and individualized options. The application grounds its functionality on a Cellular Automaton (CA) that models the area of interest and provides the rule that activates the processing of input data. The model incorporates the term walkability as a discrete magnitude that integrates qualitative features of pedestrian mobility. The proposed application fosters sustainable forms of movement at a local level that undoubtedly improves the human physical status and upgrades civilian living conditions. In the context of this paper, we provide a thorough description of the operational principles of the model, and we test its validity by applying it in Xanthi, a medium size city located in northeastern Greece. Finally, we describe variants of the initial scenario to demonstrate the sensibility of the model in external assessments as well as its resilience in biasing manipulations. [ABSTRACT FROM AUTHOR]

Published
2022

206. On Edge Image Processing Acceleration with Low Power Neuro-Memristive Segmented Crossbar Array Architecture.

Author

VASILEIADIS, NIKOLAOS, NTINAS, VASILEIOS, KARAKOLIS, PANAGIOTIS, DIMITRAKIS, PANAGIOTIS, and SIRAKOULIS, GEORGIOS CH.

Subjects
IMAGE processing, BIOLOGICALLY inspired computing, EDGE computing
Abstract

Computational acceleration for image processing tasks on the edge is becoming increasingly important for many applications. This work presents a new neuro-inspired architecture which incorporates inmemory computing properties for image processing complex computational tasks in addition to analog memory. The proposed architecture was based on segmented crossbar topology, which, as it turns out, reduces many phenomena that affect the performance on such systems. The extended architectural capabilities of this structure were also tested in a systematic analysis that was performed on a novel depth map extraction application from a single defocused image. All results were validated through Spice simulations using a novel moving barrier memristor model. [ABSTRACT FROM AUTHOR]

Published
2022

211. Memristor Crossbar Design Framework for Quantum Computing

Author

Fyrigos, Iosif-Angelos, primary, Chatzinikolaou, Theodoros Panagiotis, additional, Ntinas, Vasileios, additional, Vasileiadis, Nikolaos, additional, Dimitrakis, Panagiotis, additional, Karafyllidis, Ioannis, additional, and Sirakoulis, Georgios Ch., additional

Published
2021
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212. Emergence of Chimera States with Re-Programmable Memristor Crossbar Arrays

Author

Tsakalos, Karolos-Alexandros, primary, Ntinas, Vasileios, additional, Karamani, Rafailia-Eleni, additional, Fyrigos, Iosif-Angelos, additional, Chatzinikolaou, Theodoros Panagiotis, additional, Vasileiadis, Nikolaos, additional, Dimitrakis, Panagiotis, additional, Provata, Astero, additional, and Sirakoulis, Georgios Ch., additional

Published
2021
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215. Unconventional Computing With Memristive Nanocircuits

Author

Tsipas, Evangelos, Chatzinikolaou, Theodoros Panagiotis, Tsakalos, Karolos-Alexandros, Rallis, Konstantinos, Karamani, Rafailia-Eleni, Fyrigos, Iosif-Angelos, Kitsios, Stavros, Bousoulas, Panagiotis, Tsoukalas, Dimitrios, and Sirakoulis, Georgios Ch.

Abstract

Computing demands are growing rapidly as bigdata and artificial intelligence applications become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be quite promising for the development of novel circuits and systems. These systems can contribute to the resolution of a wider variety of problems while also providing improvements to existing techniques. As the von Neumann architecture’s expected performance, which has been dominant for the past several decades, is now hindered by physical limitations, novel computing architectures, assisted by novel materials and circuit devices, are starting to emerge and provide promising results. The topic of this work is to examine the memory and computing capabilities of emergent memristor-based nanocircuits and demonstrate their advantages compared to their classical counterparts.

Published
2022
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216. Unconventional Memristive Nanodevices

Author

Tsipas, Evangelos, Chatzinikolaou, Theodoros Panagiotis, Tsakalos, Karolos-Alexandros, Rallis, Konstantinos, Karamani, Rafailia-Eleni, Fyrigos, Iosif-Angelos, Kitsios, Stavros, Bousoulas, Panagiotis, Tsoukalas, Dimitrios, and Sirakoulis, Georgios Ch.

Abstract

One of the most enticing candidates for next-generation computing systems is the memristor. Memristor-based novel architectures have demonstrated considerable promise in replacing or augmenting traditional computing platforms based on the Von Neumann architecture, which faces many issues in the big-data era, as well as in newly developed neuromorphic tasks. Although the current classical computing architecture is unlikely to be abandoned in the foreseeable future, the growing trend of neuromorphic, quantum, and bio-inspired computing schemes calls for more specialized beyond Von Neumann platforms. Memristors showcase multiple advantages in terms of small area footprint, energy efficiency, high endurance, bio-compatibility, and their inherent synaptic and neuromorphic behavior. The topic of this work is to present the memristive devices that meet the requirements for the implementation of the novel beyond Von Neumann applications and examine their switching mechanism and material selection, as well as to conduct a performance comparison between the fabricated devices paving the way for future computing applications.

Published
2022
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217. Introducing the Editorial Board

Author

Sheu, Bing, Kao, Shao-Ku, Jiang, Xiaoning, Lai, Chao-Sung, Yang, Hui-Ying, Hu, Vita Pi-Ho, Huang, Hsiao-Chun, Liu, Huan, Yun, Ilgu, Sakata, Toshiya, Ottavi, Marco, Dimitrakis, Panagiotis, Sirakoulis, Georgios Ch., Elara, Mohan Rajesh, Lin, Lin, Xu, Yang, Puliafito, Vito, Bonyar, Attila, Hwang, Yuh-Shyan, and Chang, Ruey-Dar

Abstract

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Published
2022
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221. Understanding the role of defects in Silicon Nitride-based resistive switching memories through oxygen doping

Author

Vasileiadis, Nikolaos, primary, Karakolis, Panagiotis, additional, Mandylas, Panagiotis, additional, Ioannou-Sougleridis, Vassilios, additional, Normand, Pascal, additional, Perego, Michele, additional, Komninou, Philomela, additional, Ntinas, Vasileios, additional, Fyrigos, Iosif-Angelos, additional, Karafyllidis, Ioannis G., additional, Sirakoulis, Georgios Ch., additional, and Dimitrakis, Panagiotis, additional

Published
2021
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231. Error Detection and Correction Algorithms for the Firing Squad Synchronization Problem.

Author

KYRITSIS, APOSTOLOS, LIOLIS, ORESTIS, and SIRAKOULIS, GEORGIOS CH.

Subjects
SYNCHRONIZATION, CELLULAR automata, ALGORITHMS, COMPUTER science
Abstract

One of the most famous problems in computer science and cellular automata (CAs) is the Firing Squad Synchronization Problem (FSSP). In the FSSP, a one-dimensional CA with just a single active cell (initially called "General") eventually reaches a state in which all the CA cells (called "soldiers" in analogy to real-world firing squad) are simultaneously active. Since the introduction of the FSSP as a well known problem in the 60's, and during the last decades, many FSSP solution algorithms have been proposed in the literature. Nevertheless, the inherited error correction capabilities of these algorithms have not been extensively studied. In this paper, an error detection and correction algorithm that utilizes the patterns appearing in 1-D Mazoyer's 8-state solution is analyzed and presented. Furthermore, the patterns of 2-D Umeo's FSSP algorithm are also thoroughly investigated. In such a case, extra patterns emerge from CA cells grouping, during the application of 1-D FSSP solution to 2-D CA grid, enhancing the error tolerance of the proposed algorithm, i.e. almost every possible error can be detected. Finally, another version, even more efficient, of error detection and correction algorithm with memory effect considering previous CA states usage, is also introduced. Although the usage of previous CA states results to increased utilization of computational resources, at the same time it enables the proposed algorithm to detect every possible error state in every possible CA cell, advancing significantly the algorithm's performance. [ABSTRACT FROM AUTHOR]

Published
2022

234. Memristive Learning Cellular Automata: Theory and Applications

Author

Karamani, Rafailia-Eleni, primary, Fyrigos, Iosif-Angelos, additional, Ntinas, Vasileios, additional, Liolis, Orestis, additional, Dimitrakopoulos, Giorgos, additional, Altun, Mustafa, additional, Adamatzky, Andrew, additional, Stan, Mircea R., additional, and Sirakoulis, Georgios Ch., additional

Published
2020
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243. Randomblocks: A transparent, verifiable blockchain-based system for random numbers

Author

Klitos Christodoulou, Chatzichristofis, Savvas A, Sirakoulis, Georgios Ch, and Christodoulou, Panayiotis

Subjects
Cellular automata, Computer and Information Sciences, Blockchain, Pseudo-random number generation, Natural Sciences
Abstract

Games-of-chance require high-levels of trust between participants that is often uncertain and difficult to enforce. The unique characteristics introduced by the blockchain technology can be leveraged to inform a verifiable but transparent pseudo-random generation process that at the same time eliminates the need of an external trustee service or oracle to guarantee the fair execution of the process. We propose a process that builds on a one-dimensional Cellular Automaton (CA) where the evolution of the CA aligns to the evolution of a blockchain. Given an initial seed defined as the point in time where the evolution of the CA is triggered, the set of transition rules, along with the finite number of evolution steps, any external oracle is able to verify and backtrack (but not predict) the outcome of the process. The effectiveness of the implemented system is confirmed by the use of various statistical testing suites that confirm the existence of a set of statistical properties required to produce sufficient pseudo-random number sequences.

Published
2019

244. A pragmatic gaze on stochastic resonance based variability tolerant memristance

Author

Ntinas, Vasileios, Rubio Sola, Jose Antonio, Sirakoulis, Georgios Ch., Cotofana, Sorin, Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica, and Universitat Politècnica de Catalunya. HIPICS - Grup de Circuits i Sistemes Integrats d'Altes Prestacions

Subjects
Time-frequency analysis, Integrated circuit modeling, Resistance, Nonlinear systems, Integrated circuits, Enginyeria electrònica::Microelectrònica::Circuits integrats [Àrees temàtiques de la UPC], Circuits integrats, White noise, Memristors, Stochastic resonance
Abstract

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Stochastic Resonance (SR) is a nonlinear system specific phenomenon, which was demonstrated to lead to system unexpected (counter-intuitive) performance improvements under certain noise conditions. Memristor, on the other hand, is a fundamentally nonlinear circuit element, thus susceptible to benefit from SR, which recently came in the spotlight of the emerging technologies potential candidates. However, at this time, the variability exhibited by manufactured memristor devices within the same array constitutes the main hurdle in the road towards the commercialisation of memristor-based memories and/or computing units. Thus, in this paper, memristor SR effects are explored, assuming various memristor models, and SR-based memristance range enhancement, tolerant to device-to-device variability, is demonstrated. Our experiments reveal that SR can induce significant R MAX /R MIN ratio increase under up to 60% variability, getting as high as 3.4× for 29 dBm noise power.

Published
2019

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