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1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)最新文献

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Stability analysis of cellular neural networks with hysteresis nonlinearity in the feedback system 反馈系统中具有滞后非线性的细胞神经网络稳定性分析
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566516
A. Slavova
{"title":"Stability analysis of cellular neural networks with hysteresis nonlinearity in the feedback system","authors":"A. Slavova","doi":"10.1109/CNNA.1996.566516","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566516","url":null,"abstract":"A new class of cellular neural networks is considered, where nonlinearity in the feedback system is hysteresis type. Stability analysis of the equilibrium points of this circuit is made using a new approach of dividing M/spl times/N Euclidean space into three different types of regions.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115109432","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
Classification of acoustical alarm signals with CNN using wavelet transformation 基于小波变换的CNN声报警信号分类
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566603
I. Genç, C. Guzelis, I. Goknar
{"title":"Classification of acoustical alarm signals with CNN using wavelet transformation","authors":"I. Genç, C. Guzelis, I. Goknar","doi":"10.1109/CNNA.1996.566603","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566603","url":null,"abstract":"This paper presents a wavelet transformation (WT) based technique for reducing the size of cellular neural network (CNN) used for an acoustic alarm signals classification system proposed by Osuna et al. The system consists of three processing units: i) transformation of a 1-dimensional (1-D) signal into a sequence of 2-dimensional (2-D) signals, so called images obtained by a low pass filter cascade incorporated with a grid like correlation process ii) concentrating an image sequence into a single image by a linear threshold template CNN, iii) classification of the resulting image by discrete-valued perceptrons. In this paper, a discrete WT incorporating a grid like correlation process has been used for transforming a 1-D acoustic signal into an image sequence. All other operations needed for the classification has been performed for the sake of comparison. The WT based technique proposed in this paper gives the possibility of acoustic alarm signal classification by using CNNs of small size, e.g., 13/spl times/13. By using the WT based technique, CNN of size 13/spl times/13 becomes sufficient.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121877427","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
A learning algorithm for the dynamics of CNN with nonlinear templates. I. Discrete-time case 具有非线性模板的CNN动态学习算法。1 .离散时间情况
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566618
R. Tetzlaff, D. Wolf
{"title":"A learning algorithm for the dynamics of CNN with nonlinear templates. I. Discrete-time case","authors":"R. Tetzlaff, D. Wolf","doi":"10.1109/CNNA.1996.566618","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566618","url":null,"abstract":"A learning algorithm for the dynamics of discrete-time cellular neural networks (DTCNN) with gradient-based nonlinear templates is presented. For modeling the dynamics of nonlinear spatio-temporal systems with DTCNN, the algorithm is applied to find the network parameters. Results for two different nonlinear discrete-time systems are discussed in detail.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128784482","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
Design of discrete-time cellular neural networks based on mathematical morphology 基于数学形态学的离散时间细胞神经网络设计
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566479
M. ter Brugge, R. J. Krol, J.A.G. Nijhuts, L. Spaanenburg
{"title":"Design of discrete-time cellular neural networks based on mathematical morphology","authors":"M. ter Brugge, R. J. Krol, J.A.G. Nijhuts, L. Spaanenburg","doi":"10.1109/CNNA.1996.566479","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566479","url":null,"abstract":"Mathematical morphology is a discipline that provides a formal framework for the analysis and manipulation of images. Its theoretical foundations have been well-established in the last forty years and it has shown to be a power fool tool in the development of a large number of image processing applications. This paper shows that a lot of knowledge that is developed in the field of mathematical morphology can be applied to discrete-time cellular neural networks (DTCNNs). DTCNN equivalencies of the elementary morphological operators, which are the basic building blocks for complex image operations, are introduced and the correctness of these templates is formally proved.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124633139","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
A learning algorithm for the dynamics of CNN with nonlinear templates. II. Continuous-time case 具有非线性模板的CNN动态学习算法。2连续时间情况下
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566619
F. Puffer, R. Tetzlaff, D. Wolf
{"title":"A learning algorithm for the dynamics of CNN with nonlinear templates. II. Continuous-time case","authors":"F. Puffer, R. Tetzlaff, D. Wolf","doi":"10.1109/CNNA.1996.566619","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566619","url":null,"abstract":"A gradient-based learning algorithm for the dynamics of continuous-time CNN with nonlinear templates is presented. It is applied in order to find the parameters of CNN that model the dynamics of certain multidimensional nonlinear systems, which are characterized by partial differential equations (PDE). The efficiency of the algorithm is compared to that of a non-gradient-based learning procedure we have previously developed. Results for modeling two systems, whose dynamics are determined by nonlinear Klein-Gordon-equations, are discussed in detail.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124755598","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
On a novel adaptive self organizing network 一种新的自适应自组织网络
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566487
S. Kawahara, T. Saito
{"title":"On a novel adaptive self organizing network","authors":"S. Kawahara, T. Saito","doi":"10.1109/CNNA.1996.566487","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566487","url":null,"abstract":"In this paper a new algorithm is presented in order to overcome the stability vs. formation ability dilemma of competitive learning. This algorithm is based on growing cell structures of self-organizing mapping. The new algorithm is effective for endless learning and automatic classification. Applying the algorithm in the case where the input pattern is changed temporally, we have confirmed that it has much better performance than conventional algorithms.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127927073","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: 7
Recognition of rotating images using an automatic feature extraction technique and neural networks 基于自动特征提取技术和神经网络的旋转图像识别
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566513
B. Verma
{"title":"Recognition of rotating images using an automatic feature extraction technique and neural networks","authors":"B. Verma","doi":"10.1109/CNNA.1996.566513","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566513","url":null,"abstract":"This paper presents a new automatic feature extraction technique and a neural network based classification method for recognition of rotating images. The image processing technique extracts global features of an image and converts a large size image into a one-dimensional small vector. A special advantage of the proposed technique is that the extracted features are the same even if the original image is rotated with rotation angles from 5 to 355 or rotated and little bit distorted. The proposed technique is based on simple co-ordinate geometry fuzzy sets and neural networks. The proposed approach is very easy in implementation and it has implemented in C++ on a Sun workstation. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated and distorted images.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130447034","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: 7
Mapping of one-dimensional Josephson junction arrays onto cellular neural networks 一维Josephson结阵列到细胞神经网络的映射
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566598
L. Finger, V. Tavsanoglu
{"title":"Mapping of one-dimensional Josephson junction arrays onto cellular neural networks","authors":"L. Finger, V. Tavsanoglu","doi":"10.1109/CNNA.1996.566598","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566598","url":null,"abstract":"In this paper it is shown that one-dimensional Josephson junction arrays can be mapped onto Cellular Neural Networks under some restrictions. Analytic expressions to the stability of equilibria of these arrays are derived and applied to the behavior of vortex solutions. Relations between these static solutions and a particular solution of a partial differential equation are shown.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129409757","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
CNN model for identifying colors under different illumination conditions via Land's experiments 通过Land的实验，CNN模型在不同光照条件下识别颜色
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566514
Á. Zarándy, E. Grawes, T. Roska, F. Werblin, L. Chua
{"title":"CNN model for identifying colors under different illumination conditions via Land's experiments","authors":"Á. Zarándy, E. Grawes, T. Roska, F. Werblin, L. Chua","doi":"10.1109/CNNA.1996.566514","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566514","url":null,"abstract":"We present a CNN model for separating colors under different illumination conditions. The color model is based on Land's assumption: the individual monochromatic channels are processed separately. However, we use a different channel processing model. The model was evaluated on a Mondrian image.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130700757","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
A weight-adjustable hardware accelerator board for DTCNN implementation and application 一种用于DTCNN实现与应用的可调重硬件加速板
1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96) Pub Date : 1996-06-24 DOI: 10.1109/CNNA.1996.566564
Liming Zhang, Wei Wang, K. Jiang
{"title":"A weight-adjustable hardware accelerator board for DTCNN implementation and application","authors":"Liming Zhang, Wei Wang, K. Jiang","doi":"10.1109/CNNA.1996.566564","DOIUrl":"https://doi.org/10.1109/CNNA.1996.566564","url":null,"abstract":"A new method which uses only comparison and matching circuits to implement the neural net is introduced. The digital accelerator board combined with FPGA for simulating the behavior of discrete-time cellular neurons is presented in this paper. Via host computer the connected-weights can be modified in the hardware nearly arbitrarily. The network can realize various functions if the weights satisfy some conditions. The experiments show that the computation speed exceeds software implementation by 70-1000 limes. Finally, an application of feature extraction on handwritten characters recognition system shows the efficiency of the hardware with low cost.","PeriodicalId":222524,"journal":{"name":"1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130573229","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
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