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2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)最新文献

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A Triangular Systolic Array Based Digital Architecture for Computing Eigenvalues of Asymmetric Matrix 一种基于三角收缩阵列的非对称矩阵特征值计算数字架构
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610808
E. Ozturk, Ilayda Koseoglu, M. Yalçin
{"title":"A Triangular Systolic Array Based Digital Architecture for Computing Eigenvalues of Asymmetric Matrix","authors":"E. Ozturk, Ilayda Koseoglu, M. Yalçin","doi":"10.1109/CNNA49188.2021.9610808","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610808","url":null,"abstract":"This paper proposes a time-efficient parallel architecture for computing eigenvalues of asymmetric matrix with real values. The QR algorithm is used to compute the eigenvalues of asymmetric matrices. The QR decomposition process is required for the QR algorithm. The Modified Gram Schmidt (MGS) Orthogonalization is structurally suitable for parallel implementation by creating a triangular systolic array architecture. This architecture is created by placing boundary cell (BC) and internal cell (IC) modules in a triangle. In each iteration, Q column vector and R diagonal element are produced within the BC module, R upper diagonal elements are produced in IC modules. In the TSA model created for the next matrix, n diagonal (BC) modules, (n (n-l)) / 2 off-diagonal (IC) modules were used. Diagonal elements are produced, 4 BC, 6 ICs are used for the 4x4 matrix input in the implemented structure. The intended time efficiency is achieved thanks to the parallel IC modules.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115420353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multifunctional Spatially-Expanded Logic Gate for Unconventional Computations with Memristor-Based Oscillators 基于忆阻器振荡器的非常规计算的多功能空间扩展逻辑门
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610749
Theodoros Panagiotis Chatzinikolaou, Iosif-Angelos Fyrigos, V. Ntinas, Stavros Kitsios, P. Bousoulas, Michail-Antisthenis I. Tsompanas, D. Tsoukalas, G. Sirakoulis
{"title":"Multifunctional Spatially-Expanded Logic Gate for Unconventional Computations with Memristor-Based Oscillators","authors":"Theodoros Panagiotis Chatzinikolaou, Iosif-Angelos Fyrigos, V. Ntinas, Stavros Kitsios, P. Bousoulas, Michail-Antisthenis I. Tsompanas, D. Tsoukalas, G. Sirakoulis","doi":"10.1109/CNNA49188.2021.9610749","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610749","url":null,"abstract":"There is a great variety of unconventional computing approaches trying to compete with and even surpass the classical computers in providing a solution to high complexity problems. Unconventional computation functionality has been verified and implemented successfully on chemical reactions, paving the way to the development of Chemical Computers. This functionality is investigated here, aiming to transfer chemical reaction's working principle on a circuit capable of processing information, involving the interaction of propagating voltage signals in a geometrically constrained electrical medium. In this work such a circuit has been developed utilizing Memristor-Resistor-Capacitor (MemRC) oscillators and their computing capabilities have been verified by demonstrating multiple Boolean logic calculations in the same medium. More specifically, a variety of Boolean gates is implemented in a versatile topology of oscillating nodes, exploiting the same electrical medium geometry.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116442611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Optimization and Application of Niobium Oxide based Memristive NDR devices 氧化铌基记忆电阻NDR器件的优化与应用
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610782
T. Mikolajick, M. Herzig, S. Slesazeck, M. Weiher, A. Ascoli, R. Tetzlaff
{"title":"Optimization and Application of Niobium Oxide based Memristive NDR devices","authors":"T. Mikolajick, M. Herzig, S. Slesazeck, M. Weiher, A. Ascoli, R. Tetzlaff","doi":"10.1109/CNNA49188.2021.9610782","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610782","url":null,"abstract":"Memristive devices showing negative differential resistance in part of their I- V curve are interesting circuit elements for novel computing paradigms since they can generate signal amplification even in a two-terminal device. To enable the integration of such devices into highly integrated systems in the future, we need to tailor and tightly control the parameters of the I-V curve such as the threshold voltage. In this paper we show the state of the art in optimizing NDR devices based on niobium oxide. Moreover, we show examples of how the devices can be applied to electronic circuits.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115938367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
UAV obstacle detection with bio-motivated computer vision 基于生物动机计算机视觉的无人机障碍物检测
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610823
Máté Pethő, T. Zsedrovits
{"title":"UAV obstacle detection with bio-motivated computer vision","authors":"Máté Pethő, T. Zsedrovits","doi":"10.1109/CNNA49188.2021.9610823","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610823","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are becoming more and more common. They show excellent potential for multiple types of autonomous work, although they must achieve these tasks safely. For flight safety, it must be assured that the UA V will not endanger its surroundings during autonomous operations; it will avoid collision with any objects in its flight path. Camera-based computer vision and artificial neural networks have shown to be effective in many applications. However, biological vision systems and the brain areas responsible for visual processing may hold solutions capable of acquiring information effectively. Previous work has shown the usability of biologically motivated algorithms using vision systems of insects or even behavioral patterns to solve computer vision problems. We are proposing a novel system, which performs visual cue extraction with algorithms based on the structure and functionality of the retina and the visual cortex of the mammalian visual system. We are also developing a modular artificial neural network with a training dataset, which will perform autonomous obstacle recognition tasks using the data from the image processing algorithm.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131737297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Towards an automatic generalized machine learning approach to map lava flows 一种自动广义机器学习方法来绘制熔岩流图
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610813
C. Corradino, E. Amato, F. Torrisi, C. Negro
{"title":"Towards an automatic generalized machine learning approach to map lava flows","authors":"C. Corradino, E. Amato, F. Torrisi, C. Negro","doi":"10.1109/CNNA49188.2021.9610813","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610813","url":null,"abstract":"Volcano-related resurfacing processes can be monitored by complementary using radar and optical sensors. Combining both data sources with machine learning (ML) approaches is fundamental to automatically extract volcano-related features. Here, a generalized ML approach is developed in Google Earth Engine (GEE) to map lava flows in both near-real time (NRT) and no-time critical (NTC) time scales. A first attempt towards a generalized classification to automatically map new lava flows is proposed.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124445696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Gas Sensing Discrimination using a Cellular Nonlinear Network 基于元胞非线性网络的气体传感识别
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610754
M. M. Al Chawa, R. Picos, L. Panes-Ruiz, Leif Riemenschneider, B. Ibarlucea, G. Cuniberti, R. Tetzlaff
{"title":"Gas Sensing Discrimination using a Cellular Nonlinear Network","authors":"M. M. Al Chawa, R. Picos, L. Panes-Ruiz, Leif Riemenschneider, B. Ibarlucea, G. Cuniberti, R. Tetzlaff","doi":"10.1109/CNNA49188.2021.9610754","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610754","url":null,"abstract":"In this work, we developed a signal processing Cellular Nonlinear Network (CNN) for the detection and classification of real sensor data obtained from a memristive gas sensors matrix. Applying a gas sensor CNN we can discriminate between hazardous gases such as Ammonia (NH3) and Hydrogen Sulfide (H2S) and determine their concentration levels.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124539969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Automatic Visual Inspection Machine for Pharmaceutical Infusion Bags Implementing Cellular Neural Networks 基于细胞神经网络的药物输液袋自动视觉检测机
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610794
Francesco Marrone, Gianluca Zoppo, Luca Vescovi, Filippo Begarani, Ada Palama, Jacopo Secco, F. Corinto
{"title":"Automatic Visual Inspection Machine for Pharmaceutical Infusion Bags Implementing Cellular Neural Networks","authors":"Francesco Marrone, Gianluca Zoppo, Luca Vescovi, Filippo Begarani, Ada Palama, Jacopo Secco, F. Corinto","doi":"10.1109/CNNA49188.2021.9610794","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610794","url":null,"abstract":"Automation procedures and machines in the pharmaceutical field are required to implement a series of methodologies, designed parting from international standards, in order to ensure the high quality of the products. Regarding infusion bags, the standards require to thoroughly assess the conformity of the product before being used in patients. The inspection procedures are usually operator-based and therefore subject to human factor errors. A novel inspection machine has been designed and developed with the use of a specifically designed cellular neural network (CNN) coupled with an off-the-shelf neural network trainable solution. The novel machine, thanks to the computational versatility of the CNN, is capable of reaching high standards of assessment drastically decreasing the risk of operator-based errors in the procedure.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Array computing based system for visual servoing of neuroprosthesis of upper limbs 基于阵列计算的上肢神经假体视觉伺服系统
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610783
Attila Fejár, Z. Nagy, J. Benois-Pineau, P. Szolgay, Aymar de Rugy, J. Domenger
{"title":"Array computing based system for visual servoing of neuroprosthesis of upper limbs","authors":"Attila Fejár, Z. Nagy, J. Benois-Pineau, P. Szolgay, Aymar de Rugy, J. Domenger","doi":"10.1109/CNNA49188.2021.9610783","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610783","url":null,"abstract":"A hardware-software system implemented for visual servoing of prosthetic arms. The prosthetic system comprises glass worn eye-tracker and video camera and a prosthesis - mounted stereo camera system. The proposed light-weight architecture has to be implemented as a wearable device. We propose a hybrid solution which contains object selection and recognition, in glass camera view, object matching to the prosthesis-mounted camera to compute depth map for object reaching by the prosthetic arm. The object selection and object matching both use the Scale Invariant Feature Transform (SIFT) algorithm. The SIFT algorithm is time-consuming, so the FPGA acceleration is proposed for the light-weight device. The proposed implementation is compatible with real-time servoing of the prosthetic arm.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115074686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Another look at Cellular Neural Networks 再看看细胞神经网络
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610763
G. Manganaro
{"title":"Another look at Cellular Neural Networks","authors":"G. Manganaro","doi":"10.1109/CNNA49188.2021.9610763","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610763","url":null,"abstract":"The CNN architecture, introduced in 1988, mimicked the retina's functionality. Our understanding of how the sensory nervous system works, including vision, has significantly improved. At the same time, both integrated circuit design technology and signal processing have made extraordinary progress. While the latter have enabled numerous applications, traditional paradigms of sensing and real time processing are reaching a breakpoint caused by a deluge of sensory data requiring excessive processing power to extract the underlying information that leads to desirable action. Fundamental breakthroughs are required to overcome multiple obstacles presently limiting the pace of progress. In this contribution it is advocated that renewing the CNN architecture, enabled by today's technologies, and inspired by clearer knowledge of the visual system, is a better way to resolve data acquisition and processing paradigm's bottlenecks in a variety of emerging industrial applications.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123850061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Neuromorphic hybrid systems based on polarizable thin film-coated silicon nanowire field-effect transistors 基于极化薄膜包覆硅纳米线场效应晶体管的神经形态杂化系统
2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) Pub Date : 2021-09-29 DOI: 10.1109/CNNA49188.2021.9610819
L. Panes-Ruiz, B. Ibarlucea, Eunhye Baek, SangWook Park, C. Baek, Xinliang Feng, G. Cuniberti
{"title":"Neuromorphic hybrid systems based on polarizable thin film-coated silicon nanowire field-effect transistors","authors":"L. Panes-Ruiz, B. Ibarlucea, Eunhye Baek, SangWook Park, C. Baek, Xinliang Feng, G. Cuniberti","doi":"10.1109/CNNA49188.2021.9610819","DOIUrl":"https://doi.org/10.1109/CNNA49188.2021.9610819","url":null,"abstract":"We present two approaches for the development of hybrid neurotransistors based on the combination of polarizable thin films on silicon nanowires field-effect transistors for the emulation of signal processing by neurons. The polarizing properties of the films coming from the ion redistribution under bias voltage provide the systems with a memristive behavior needed to achieve the neuronal intrinsic plasticity using ionic migration in the neuron membrane at a hardware level.","PeriodicalId":325231,"journal":{"name":"2021 17th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131105791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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