{"title":"Networks of language processors: a language theoretic framework for mainly locally connected processor arrays","authors":"E. Csuhaj-Varjú, T. Roska","doi":"10.1109/CNNA.1998.685351","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685351","url":null,"abstract":"We offer a new framework for describing mainly locally connected processor arrays, where the cell processors are defined by rewriting systems (grammars). The notion of the CNN template is defined by the local communication rules and the rewriting process following the communication. A striking similarity of the dynamics of the cellular network of language processors to the analog CNN dynamics can be demonstrated. As a future example, the dynamic activity pattern of the Internet could also be modelled in this way. In addition to the concepts and results pertinent to locally connected arrays, this contribution can be considered as a tutorial on networks of language processors as well. The introduction of coloring above the strings, the signals of the array, may lead to an analogic CNN system where strings and analog signals could be used in interaction.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"109 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":"124068989","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}
{"title":"A CNN solution for depth estimation from binocular stereo imagery","authors":"A. Radványi, T. Kozek, L. Chua","doi":"10.1109/CNNA.1998.685368","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685368","url":null,"abstract":"Novel results and experiments are presented on the application of cellular neural networks to binocular stereo vision. A cellular neural network (CNN) universal machine (UM) algorithm is described for depth estimation as part of a stereo-vision-based guidance system for autonomous vehicles. Being most amenable to revealing stereo correspondence, extraction of vertical edges is performed first. Then their distance from the observer in 3D space is established through a stereo matching scheme. The performance of the algorithm is demonstrated on real-life highway imagery and it is shown that very low latency real-time operation is attainable via the CNN-UM.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"4 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":"127647364","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}
{"title":"Improvement of discrete-time cellular neural networks for associative memory using 2-dimensional discrete Walsh transform","authors":"T. Kamio, H. Asai","doi":"10.1109/CNNA.1998.685420","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685420","url":null,"abstract":"The conventional synthesis procedure of discrete-time cellular neural networks (DTCNNs) for associative memory may generate the cells with only self-feedback due to the sparsely interconnected structure. Although this problem is solved by increasing the number of interconnections, hardware implementation becomes very difficult. In this paper we propose the DTCNN system which stores the 2-dimensional discrete Walsh transforms (DWTs) of memory patterns. As each element of DWT involves the information of whole sample data, our system can associate the desired memory patterns which the conventional DTCNN fails to do.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"79 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":"127732789","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}
{"title":"Analogic CNN computing: architectural, implementation, and algorithmic advances-a review","authors":"T. Roska","doi":"10.1109/CNNA.1998.685320","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685320","url":null,"abstract":"In this paper, first, an overview is given about the whole scenario of analogic cellular neural net (CNN) computing. Next, two areas of CNN computing technology are considered briefly: (i) the architectural advances, especially variable resolution and adaptation in space, time, and value and (ii) the computational infrastructure from high-level language and compiler to physical implementations. Three basic physical implementations are considered: analogic CMOS, emulated digital CMOS and optical. The computational infrastructure is the same for all implementations, except the physical interfaces.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"10 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":"131346912","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}
{"title":"Model of a system synchronizing large oscillations in ring neuronal large structures","authors":"S. Kaschenko, V. Mayorov, I. Myshkin","doi":"10.1109/CNNA.1998.685335","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685335","url":null,"abstract":"The state of a neuron in biological system can be described by membrane potential. We deal with the exciting synapses. Under the mediator influence there arises a post-synaptic potential on that part of the membrane of the neuron-receiver that adjoins the synapse. In our model we characterize the synaptic influence effectiveness by two parameters: its duration and power (synaptic weight). We have developed the system of two coupled neuronal rings that realized synchronization of wave packages. The assumption concerning the existence of such synchronization mechanisms in human brain is a basis in the hypothesis about memory wave nature. Under synchronization the total system signal intensifies.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"16 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":"132196729","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}
{"title":"Integration of sensor/processor under cellular neural networks paradigm for multimedia applications","authors":"B. Sheu, K. Cho, W. C. Young","doi":"10.1109/CNNA.1998.685327","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685327","url":null,"abstract":"Compact, high computing power systems become feasible with significant progress in the research and development of advanced computing architecture and array processing. A scalable image sensor array processor with frame memory buffer and cellular neural network (CNN) for nearest neighbor interaction has been developed in a 0.5 mm HP CMOS technology. A CNN with analog programmable weights was constructed with compact mixed-signal circuit components in the current-mode technique. The low voltage, low power operation is supported with the current mode scheme which scales appropriately with the supply voltage. Design of a variable gain neuron circuit can be incorporated into the prototype to realize the optimal solution capability using hardware annealing.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"46 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":"133912664","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}
R. Buczyński, H. Thienpont, S. Jankowski, T. Szoplik, I. Veretennicoff
{"title":"Programmable CNN based on optical thyristors for early image processing","authors":"R. Buczyński, H. Thienpont, S. Jankowski, T. Szoplik, I. Veretennicoff","doi":"10.1109/CNNA.1998.685382","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685382","url":null,"abstract":"An optoelectronic model of discrete time cellular neural networks (DTCNN) is presented. Connections between cells and parallel input-output are realized using optoelectronic devices. As an emitter-receiver device an optical thyristor is applied. Connections between cells are realized by diffractive Damman gratings. We propose a dual rail system for early processing of binary images. The CNN system performs mathematical morphology and space logic operations.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"42 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":"126529578","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}
{"title":"Lyapunov diagonally stable matrices to design cellular neural networks for associative memories","authors":"G. Grassi","doi":"10.1109/CNNA.1998.685418","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685418","url":null,"abstract":"Lyapunov diagonally stable matrices are used to design cellular neural networks for associative memories. The proposed technique, which guarantees the global asymptotic stability of the equilibrium point, generates neural circuits where the input data are fed via external inputs, rather than initial conditions. This feature makes the suggested approach particularly suitable for hardware implementation techniques. Simulations results are reported to show the advantages and the usefulness of the proposed design method.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"7 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":"125191201","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}
{"title":"Cellular nonlinear network implementation for packet selection","authors":"A. Paasio, A. Kananen, V. Porra","doi":"10.1109/CNNA.1998.685355","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685355","url":null,"abstract":"A cellular neural network design is presented suitable for packet selection in a fast packet switching fabric. The design consists of 8/spl times/8 cells network. The cell contents are described and also simulation results are given.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"15 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":"133887011","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}
{"title":"1-D discrete time CNN with multiplexed template hardware","authors":"Gabriele Manganaro, J. P. D. Gyvez","doi":"10.1109/CNNA.1998.685384","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685384","url":null,"abstract":"While VLSI of CNNs has seen significant progress in two-dimensional signal processing little has been done for one-dimensional applications such as audio signal processing and 1-D filtering. The paper presents a discrete-time programmable cellular neural network suitable for these kind of applications. The proposed VLSI implementation is based on the well-known S/sup 2/I technique that among other properties minimizes clock feedthrough effects. This feature renders an accurate signal processing unit. The system's main building blocks are an analog shift register and a switched current multiplier. Yet, the system architecture is novel by itself. Namely, the number of multipliers has been minimized by sharing the multipliers between the A*y and B*u products during the various phases of the controlling clock. The paper presents detailed simulation results of the system architecture.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"605 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":"116377443","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}