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

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A time-multiplexing simulator for cellular neural network 细胞神经网络的时间复用模拟器
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685370
A. El-Shafei, M. Sobhy
{"title":"A time-multiplexing simulator for cellular neural network","authors":"A. El-Shafei, M. Sobhy","doi":"10.1109/CNNA.1998.685370","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685370","url":null,"abstract":"A cellular neural network (CNN) simulator and a time-multiplexing algorithm implementation are described. The model for the CNN cell is simulated by SIMULINK/sup R/ but the multiplexing algorithm could be used with any other implementation. The CNN model was tested using several templates, and the test results using connected components detection (CCD) templates are given. This simulator provides a simple and user friendly environment for studying and analyzing CNN dynamics. The time-multiplexing algorithm is tested using the edge detection and CCD templates and the results are attached.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"125 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":"127515070","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
Electro-optical measurement system for the DC characterization of visible detectors for CMOS compatible CNN vision chips 用于CMOS兼容CNN视觉芯片的可见探测器直流特性的电光测量系统
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685388
E. Roca, F. Frutos, S. Espejo, R. Domínguez-Castro, Á. Rodríguez-Vázquez
{"title":"Electro-optical measurement system for the DC characterization of visible detectors for CMOS compatible CNN vision chips","authors":"E. Roca, F. Frutos, S. Espejo, R. Domínguez-Castro, Á. Rodríguez-Vázquez","doi":"10.1109/CNNA.1998.685388","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685388","url":null,"abstract":"An electro-optical measurement system for the DC characterization of visible detectors for CMOS compatible CNN chips is presented which can help designers to characterize these detectors. The measurement system has been designed to be versatile, fast and easily expandable and used. Two different set-up's for the measurement of the spectral response and the optical dynamic range of the detectors are described in detailed. Measurements of the spectral response are done with a fully computer controlled set-up, avoiding tedious and inaccurate measurements. A description of the different detectors available in a CMOS process is also given, together with the parameters affecting their response and a set of test structures which can be useful for the characterization of the detectors.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"40 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113985569","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
Some methods for practical halftoning on the CNN universal machine 在CNN万能机上进行实际半调色的一些方法
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685397
K. R. Crounse, T. Roska, L. Chua
{"title":"Some methods for practical halftoning on the CNN universal machine","authors":"K. R. Crounse, T. Roska, L. Chua","doi":"10.1109/CNNA.1998.685397","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685397","url":null,"abstract":"This paper explores two issues which are relevant in practical halftoning situations on the CNN universal machine: block processing of large images with small CNN arrays, and the use of no larger than 3/spl times/3 templates. It is shown that block processing can be performed without noticeable boundary artifacts by careful selection of boundary cell values. In this example, a standard 3/spl times/3 halftoning template is used; higher quality halftones can be obtained only by using larger templates. A CNNUM algorithm is introduced which uses only a 3/spl times/3 template but emulates a much larger effective template through an iterative procedure. The method is to discretize the CNN transient in time and then implement the spatial correlations at each time step with a CNN transient. An A-B-template pair was designed for a single CNN transient to approximate a very simple linear filter model of the human visual system. The resulting discrete-time system was analyzed. The iterative procedure is demonstrated to produce a visually pleasing halftone.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"29 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":"127173315","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
Cellular neural network simulator for image processing applications 用于图像处理的细胞神经网络模拟器
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685402
Riccardo Caponetto, M. Lavorgna, A. Martinez, L. Occhipinti
{"title":"Cellular neural network simulator for image processing applications","authors":"Riccardo Caponetto, M. Lavorgna, A. Martinez, L. Occhipinti","doi":"10.1109/CNNA.1998.685402","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685402","url":null,"abstract":"This paper presents a cellular neural network simulator software, called SIMUL CN/sup 2/, for image-processing applications. The software is designed to handle both black-and-white and 256 gray levels images. All the template matrices used are assumed space-invariant with dimension 3/spl times/3 or 5/spl times/5. The software simulator acts as a development system and an evaluation tool for VLSI chips which are currently under study. An automatic optimization tool together with some experimental applications are also reported.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"27 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":"125044060","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: 9
CNN with non-integer order cells 非整数阶单元的CNN
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685404
P. Arena, L. Bertucco, L. Fortuna, G. Nunnari, L. Occhipinti, D. Porto
{"title":"CNN with non-integer order cells","authors":"P. Arena, L. Bertucco, L. Fortuna, G. Nunnari, L. Occhipinti, D. Porto","doi":"10.1109/CNNA.1998.685404","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685404","url":null,"abstract":"A new kind of cellular neural network (CNN) is introduced. Its feature consists of a state representation using q-order derivatives, with q being a non-integer quantity. This approach can be considered as a generalisation of the traditional CNN model, which is obtained from the one presented in the paper as a particular case setting q=1. It is shown that this more general CNN structure exhibits suitable performance in terms of processing speed. Various examples are reported to show the suitability of non-integer order CNNs.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"8 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":"123359446","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
Image compression by orthogonal decomposition and dynamic segmentation using cellular nonlinear network chips 基于元胞非线性网络芯片的正交分解和动态分割图像压缩
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685392
Tamás Szirányi, L. Czúni, I. Kopilovic, T. Gyimesi
{"title":"Image compression by orthogonal decomposition and dynamic segmentation using cellular nonlinear network chips","authors":"Tamás Szirányi, L. Czúni, I. Kopilovic, T. Gyimesi","doi":"10.1109/CNNA.1998.685392","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685392","url":null,"abstract":"A method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimensional (2D) orthogonal transformations. Using the 2D basis functions of the Hadamard or Cosine functions, the transformation coefficients of the basic block of the image are measured by the CNN. Meanwhile, the CNN can produce the inverse transformation of the measured coefficients and the actual distortion-rate can be computed. If a required distortion-rate is reached, the coding process could be stopped (the use of even more coefficients would increase bit-rate needlessly). Effects of noise and VLSI computing accuracy are also considered to optimise the architecture. We also give a short description of how to join the transform coding method and the object-oriented image model.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"62 8 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":"116443186","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
Solution of the super-resolution problem by multi-valued nonlinear filtering, and its implementation using cellular neural networks 用多值非线性滤波解决超分辨率问题，并利用细胞神经网络实现
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685401
I. Aizenberg, N. Aizenberg, J. Vandewalle
{"title":"Solution of the super-resolution problem by multi-valued nonlinear filtering, and its implementation using cellular neural networks","authors":"I. Aizenberg, N. Aizenberg, J. Vandewalle","doi":"10.1109/CNNA.1998.685401","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685401","url":null,"abstract":"An original approach to the solution of a super-resolution problem is considered. A solution is reduced to the iterative process by which the coefficients of the orthogonal spectrum corresponding to the highest frequencies, which are unknown, may be obtained. Supposing that unknown values of the signal are corrupted by uniform noise with the small dispersion, iterative procedure for obtaining the highest spectral coefficients is proposed. To remove the remaining noise, and to correct the spectral coefficients obtained in the first step, multi-valued nonlinear filters are proposed. Since the CNN with multi-valued neurons is the best instrument for an implementation of these filters, the corresponding templates are used.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"168 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":"132868773","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
Applications of CNN processing by template decomposition 模板分解在CNN处理中的应用
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685405
B. Mirzai, D. Lim, G. Moschytz
{"title":"Applications of CNN processing by template decomposition","authors":"B. Mirzai, D. Lim, G. Moschytz","doi":"10.1109/CNNA.1998.685405","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685405","url":null,"abstract":"High connectivity cellular neural network (CNN) templates are inherently less robust than templates of lower connectivity. However, some types of detection tasks requiring a high degree of connectivity can be decomposed and realized by an algorithmic approach, instead of a single CNN template. The processing comprises several robust template types and logical operations. The basic template type proposed for the decomposition is at an intermediate point between high-connectivity CNN template processing and processing using digital logic exclusively.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"217 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":"132067518","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: 4
An emulated digital architecture implementing the CNN Universal Machine 实现CNN通用机的仿真数字架构
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685378
Á. Zarándy, P. Keresztes, T. Roska, P. Szolgay
{"title":"An emulated digital architecture implementing the CNN Universal Machine","authors":"Á. Zarándy, P. Keresztes, T. Roska, P. Szolgay","doi":"10.1109/CNNA.1998.685378","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685378","url":null,"abstract":"An emulated digital VLSI CMOS architecture is described, where the main features are as follows: (i) variable accuracy, (ii) a complete CNN Universal Machine on the silicon, (iii) a good area time trade off. The whole architecture was defined on VHDL and the following key parameters of the implementation were computed namely, (i) the speed (1 ns/virtual cell/iteration), (ii) the number of the physical processing cells per cm/sup 2/ is 24 by using 0.35 /spl mu/m three metal layer CMOS technology.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"17 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":"122169025","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: 18
Minimizing the effects of tolerance faults on hardware realizations of cellular neural networks 最小化容错对细胞神经网络硬件实现的影响
1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI: 10.1109/CNNA.1998.685407
R. Tetzlaff, R. Kunz, G. Geis, D. Wolf
{"title":"Minimizing the effects of tolerance faults on hardware realizations of cellular neural networks","authors":"R. Tetzlaff, R. Kunz, G. Geis, D. Wolf","doi":"10.1109/CNNA.1998.685407","DOIUrl":"https://doi.org/10.1109/CNNA.1998.685407","url":null,"abstract":"In this paper a procedure for minimizing the effects of tolerance faults in cellular neural network (CNN) chips is presented. The simulation system SCNN was connected with the \"CNN prototyping system\" for adjusting the parameter values of the cp300 CNN chip. Results showing the erroneous outputs of the VLSI chip are presented, together with a suitable way for adapting parameter directly to a CNN realization.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"99 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":"122028476","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: 6
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