1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)最新文献

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Frequency-domain intrachip communication schemes for CNN CNN的频域芯片内通信方案
A. Mondragón-Torres, R. González-Carvajal, J. Pineda de Gyvez, E. Sánchez-Sinencio
{"title":"Frequency-domain intrachip communication schemes for CNN","authors":"A. Mondragón-Torres, R. González-Carvajal, J. Pineda de Gyvez, E. Sánchez-Sinencio","doi":"10.1109/CNNA.1998.685411","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685411","url":null,"abstract":"A frequency-domain scheme to share a communications channel among the cells of a CNN is proposed. The scheme is based on a modification of the wave-parallel-computing technique and addresses the problem of reducing the number of communication links. Reduction in the communication paths is achieved by frequency multiplexing. This makes it possible to have simultaneous full-parallel access to all the cells of the array. The approach also takes advantage of the parallelism inherent in wave-parallel-computing to solve part of the state equation within the same channel during a transmission operation. Moreover, with this architecture, the CNN array is not required to have a physical matrix array of cells, providing in this form even more flexibility for the hardware implementation. A system level simulation was done and operating ranges were found as an aid to propose a final system architecture of a tentative VLSI IC.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124140296","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: 5
A cellular system for pattern recognition using associative neural networks 一种利用联想神经网络进行模式识别的细胞系统
C. Orovas, J. Austin
{"title":"A cellular system for pattern recognition using associative neural networks","authors":"C. Orovas, J. Austin","doi":"10.1109/CNNA.1998.685353","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685353","url":null,"abstract":"A cellular system for pattern recognition is presented. The cells are placed in a two dimensional array and they are capable of performing basic symbolic processing and exchanging messages about their state. Following a cellular automata like operation the aim of the system is to transform an initial symbolic description of a pattern to a correspondent object level representation. To this end, a hierarchical approach for the description of the structure of the patterns is followed. The underlying processing engine of the system is the AURA model of associative memory. The system is endowed with a learning mechanism utilizing the distributed nature of the architecture. A dedicated hardware platform is also available.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116326761","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: 16
Challenges in mixed-signal IC design of CNN chips in submicron CMOS 亚微米CMOS CNN芯片混合信号集成电路设计的挑战
Á. Rodríguez-Vázquez, R. Domínguez-Castro, S. Espejo
{"title":"Challenges in mixed-signal IC design of CNN chips in submicron CMOS","authors":"Á. Rodríguez-Vázquez, R. Domínguez-Castro, S. Espejo","doi":"10.1109/CNNA.1998.685322","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685322","url":null,"abstract":"Summary form only given. The contrast observed between the performance of artificial vision machines and \"natural\" vision system is due to the inherent parallelism of the former. In particular, the retina combines image sensing and parallel processing to reduce the amount of data transmitted for subsequent processing by the following stages of the human vision system. Industrial applications demand CMOS vision chips capable of flexible operation, with programmable features and standard interfacing to conventional equipment. The CNN Universal Machine (CNN-UM) is a powerful methodological framework for the systematic development of these chips. Basic system-level targets in the design of these chips are to increase the cell density and operation speed. As the technology scales down to submicron all the lateral dimensions decrease by the scaling factor /spl lambda/, and the vertical dimensions scale as /spl lambda//sup -a/, where a is typically around 1/2. Ideally, cell density /spl prop//spl lambda//sup 2/ and time constant /spl prop//spl lambda//sup -2/. The article explains why this is not strictly true, and addresses the challenges involved in the design of CNN chips in submicron technologies.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123605475","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: 8
Four-quadrant one-transistor-synapse for high-density CNN implementations 高密度CNN实现的四象限单晶体管突触
R. Domínguez-Castro, Á. Rodríguez-Vázquez, S. Espejo, R. Carmona
{"title":"Four-quadrant one-transistor-synapse for high-density CNN implementations","authors":"R. Domínguez-Castro, Á. Rodríguez-Vázquez, S. Espejo, R. Carmona","doi":"10.1109/CNNA.1998.685377","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685377","url":null,"abstract":"Presents a linear four-quadrants, electrically-programmable, one-transistor synapse strategy applicable to the implementation of general massively-parallel analog processors in CMOS technology. It is specially suited for translationally-invariant processing arrays with local connectivity, and results in a significant reduction in area occupation and power dissipation of the basic processing units. This allows higher integration densities and therefore, permits the integration of larger arrays on a single chip.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129851577","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: 23
Efficient DTCNN implementations for large-neighborhood functions 大邻域函数的高效DTCNN实现
M. ter Brugge, J. H. Stevens, J. Nijhuis, L. Spaanenburg
{"title":"Efficient DTCNN implementations for large-neighborhood functions","authors":"M. ter Brugge, J. H. Stevens, J. Nijhuis, L. Spaanenburg","doi":"10.1109/CNNA.1998.685336","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685336","url":null,"abstract":"Most image processing tasks, like pattern matching, are defined in terms of large-neighborhood discrete time cellular neural network (DTCNN) templates, while most hardware implementations support only direct-neighborhood ones (3/spl times/3). Literature on DTCNN template decomposition shows that such large-neighborhood functions can be implemented as a sequence of successive direct-neighborhood templates. However, for this procedure the number of templates in the decomposition is exponential in the size of the original template. This paper shows how template decomposition is induced by the decomposition of structuring elements in the morphological design process. It is proved that an upper bound for the number of templates found in this way is quadratic in the size of the original template. For many cases more efficient and even optimal decompositions can be obtained.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122197315","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: 10
CNN models of receptive field dynamics of the central visual system neurons 中枢视觉系统神经元感受野动力学的CNN模型
L. Orzó, K. László, László Négyessy, J. Hámori, T. Roska
{"title":"CNN models of receptive field dynamics of the central visual system neurons","authors":"L. Orzó, K. László, László Négyessy, J. Hámori, T. Roska","doi":"10.1109/CNNA.1998.685363","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685363","url":null,"abstract":"Deals with the biological aspects of the receptive field (RF) concept and its possible cellular neural network (CNN) modeling. Three kinds of receptive field definitions are discussed: the experimentally measured RF, the mathematical model of the RF and its anatomical background. Previously, new RF-mapping techniques have revealed that neurons in the visual pathway exhibit striking RF dynamics, which implies that for adequate characterization the RF profile has to be examined in the space-time domain. Starting from these findings in the present study the neurons' static RF definition is purified and some experimental results of De Angelis et al. (1995) are modeled by the CNN. Our CNN model indicates that the spatio-temporal RF dynamics can be generated by time invariant synaptic strength values.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130732796","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
On CNN boundary conditions in Turing pattern formation 图灵模式形成中的CNN边界条件
L. Goras, T. Teodorescu
{"title":"On CNN boundary conditions in Turing pattern formation","authors":"L. Goras, T. Teodorescu","doi":"10.1109/CNNA.1998.685345","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685345","url":null,"abstract":"Several new boundary conditions are studied for 2D CNN. Spatial eigenvectors and eigenvalues allowing the use of the differential equations decoupling are presented and computer simulations are given.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124235781","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: 8
A new CNN based tool for an automated morphometry analysis of the corneal endothelium 一种新的基于CNN的工具,用于角膜内皮的自动形态分析
M. Salerno, F. Sargeni, V. Bonaiuto, P. Amerini, L. Cerulli, F. Ricci
{"title":"A new CNN based tool for an automated morphometry analysis of the corneal endothelium","authors":"M. Salerno, F. Sargeni, V. Bonaiuto, P. Amerini, L. Cerulli, F. Ricci","doi":"10.1109/CNNA.1998.685358","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685358","url":null,"abstract":"Cellular neural networks show high performance capabilities in real time image processing applications. For this reason, their use in biomedical image analysis can be a useful aid to the doctor in clinical diagnosis. In this research area the improvements in systems for clinical specular microscopy in vivo made a strong contribution to the study and the comprehension of the physiopathology of corneal endothelium. The more recent systems allow acquisition of the images and morphometric analysis. Nevertheless, the results (i.e. the automated reconstruction of the endothelium cell borders) are often inaccurate. Moreover, they do not allow the correct recognition of the cell shapes. On the other hand, even if the semiautomatic systems allow an effective evaluation of the cell shape, they are highly time consuming and provide results that could be affected by the criterion used by the operator in the cell corner detection. In this paper a software tool for the full automated morphometric analysis of corneal endothelium images is presented. The tool makes use of an analogue cellular neural network algorithm that allows both cell shape recognition and endothelial cell area measurement.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125717700","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: 13
Focal-plane optical flow computation by foveated CNNs 聚焦cnn计算焦平面光流
M. Balsi
{"title":"Focal-plane optical flow computation by foveated CNNs","authors":"M. Balsi","doi":"10.1109/CNNA.1998.685354","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685354","url":null,"abstract":"Optical flow computation is instrumental in robot guidance. Optoelectronic smart-pixel sensors for such computation may be realized on a single chip, by making use of a suitable cellular neural network architecture defined on a log-polar space-variant grid. Simulations confirm validity of the filtering system, and possible realizable structures are discussed.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131982840","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: 8
Generalization of CNN with hysteresis nonlinearity 具有滞后非线性的CNN的推广
A. Slavova
{"title":"Generalization of CNN with hysteresis nonlinearity","authors":"A. Slavova","doi":"10.1109/CNNA.1998.685330","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685330","url":null,"abstract":"We introduce a general class of neural networks. This new model covers some of the known neural network architectures, including cellular neural networks and Hopfield networks. Hysteresis feedback networks are introduced and compared to the general Hopfield networks in order to prove the existence of hysteresis phenomena in the network.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122209679","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: 3
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