Relevant bibliographies by topics / Pulse-Coupled Neural Networks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Pulse-Coupled Neural Networks'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Pulse-Coupled Neural Networks"

1

Wang, Zhaobin, Yide Ma, Feiyan Cheng, and Lizhen Yang. "Review of pulse-coupled neural networks." Image and Vision Computing 28, no. 1 (January 2010): 5–13. http://dx.doi.org/10.1016/j.imavis.2009.06.007.

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Ota, Y., and B. M. Wilamowski. "Analog implementation of pulse-coupled neural networks." IEEE Transactions on Neural Networks 10, no. 3 (May 1999): 539–44. http://dx.doi.org/10.1109/72.761710.

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Ranganath, H. S., and G. Kuntimad. "Object detection using pulse coupled neural networks." IEEE Transactions on Neural Networks 10, no. 3 (May 1999): 615–20. http://dx.doi.org/10.1109/72.761720.

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Olmi, S., A. Politi, and A. Torcini. "Collective chaos in pulse-coupled neural networks." EPL (Europhysics Letters) 92, no. 6 (December 1, 2010): 60007. http://dx.doi.org/10.1209/0295-5075/92/60007.

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Monica Subashini, M., and Sarat Kumar Sahoo. "Pulse coupled neural networks and its applications." Expert Systems with Applications 41, no. 8 (June 2014): 3965–74. http://dx.doi.org/10.1016/j.eswa.2013.12.027.

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WANG, Xin, Yi-de MA, Zhi-jian XU, and Lian-feng LI. "Chaos control based on pulse-coupled neural networks." Journal of Computer Applications 29, no. 12 (March 1, 2010): 3277–79. http://dx.doi.org/10.3724/sp.j.1087.2009.03277.

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Kuntimad, G., and H. S. Ranganath. "Perfect image segmentation using pulse coupled neural networks." IEEE Transactions on Neural Networks 10, no. 3 (May 1999): 591–98. http://dx.doi.org/10.1109/72.761716.

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Kanamaru, Takashi, and Kazuyuki Aihara. "Rewiring-Induced Chaos in Pulse-Coupled Neural Networks." Neural Computation 24, no. 4 (April 2012): 1020–46. http://dx.doi.org/10.1162/neco_a_00252.

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The dependence of the dynamics of pulse-coupled neural networks on random rewiring of excitatory and inhibitory connections is examined. When both excitatory and inhibitory connections are rewired, periodic synchronization emerges with a Hopf-like bifurcation and a subsequent period-doubling bifurcation; chaotic synchronization is also observed. When only excitatory connections are rewired, periodic synchronization emerges with a saddle node–like bifurcation, and chaotic synchronization is also observed. This result suggests that randomness in the system does not necessarily contaminate the sy
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Xu, Xinzheng, Guanying Wang, Shifei Ding, Yuhu Cheng, and Xuesong Wang. "Pulse-coupled neural networks and parameter optimization methods." Neural Computing and Applications 28, S1 (June 4, 2016): 671–81. http://dx.doi.org/10.1007/s00521-016-2397-2.

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He, Changtao, Fangnian Lang, and Hongliang Li. "Medical Image Registration using Cascaded Pulse Coupled Neural Networks." Information Technology Journal 10, no. 9 (August 15, 2011): 1733–39. http://dx.doi.org/10.3923/itj.2011.1733.1739.

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Dissertations / Theses on the topic "Pulse-Coupled Neural Networks"

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Swathanthira, Kumar Murali Murugavel M. "Magnetic Resonance Image segmentation using Pulse Coupled Neural Networks." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-dissertations/280.

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The Pulse Couple Neural Network (PCNN) was developed by Eckhorn to model the observed synchronization of neural assemblies in the visual cortex of small mammals such as a cat. In this dissertation, three novel PCNN based automatic segmentation algorithms were developed to segment Magnetic Resonance Imaging (MRI) data: (a) PCNN image 'signature' based single region cropping; (b) PCNN - Kittler Illingworth minimum error thresholding and (c) PCNN -Gaussian Mixture Model - Expectation Maximization (GMM-EM) based multiple material segmentation. Among other control tests, the proposed algorithms wer
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Wise, Raydiance (Raydiance Raychele). "Optoelectronic implementations of Pulse-Coupled Neural Networks : challenges and limitations." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40539.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>Includes bibliographical references (leaves 76-79).<br>This thesis examines Pulse Coupled Neural Networks (PCNNs) and their applications, and the feasibility of a compact, rugged, cost-efficient optoelectronic implementation. Simulation results are presented. Proposed optical architectures are discussed and analyzed. A new optoelectronic PCNN architecture is also presented. Tradeoffs of optical versus electronic implementations of PCNNs are discussed. This work combines concepts
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Innes, Andrew, and andrew innes@defence gov au. "Genetic Programming for Cephalometric Landmark Detection." RMIT University. Aerospace, Mechanical and Manufacturing Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080221.123310.

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The domain of medical imaging analysis has burgeoned in recent years due to the availability and affordability of digital radiographic imaging equipment and associated algorithms and, as such, there has been significant activity in the automation of the medical diagnostic process. One such process, cephalometric analysis, is manually intensive and it can take an experienced orthodontist thirty minutes to analyse one radiology image. This thesis describes an approach, based on genetic programming, neural networks and machine learning, to automate this process. A cephalometric analysis involves
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Timoszczuk, Antonio Pedro. "Reconhecimento automático do locutor com redes neurais pulsadas." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-26102004-195250/.

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As Redes Neurais Pulsadas são objeto de intensa pesquisa na atualidade. Neste trabalho é avaliado o potencial de aplicação deste paradigma neural, na tarefa de reconhecimento automático do locutor. Após uma revisão dos tópicos considerados importantes para o entendimento do reconhecimento automático do locutor e das redes neurais artificiais, é realizada a implementação e testes do modelo de neurônio com resposta por impulsos. A partir deste modelo é proposta uma nova arquitetura de rede com neurônios pulsados para a implementação de um sistema de reconhecimento automático do locutor. Para a r
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Sandmann, Humberto Rodrigo. "Padrões de pulsos e computação em redes neurais com dinâmica." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-05092012-165022/.

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O processamento de sinais feito pelos sistemas neurais biológicos é altamente eficiente e complexo, por isso desperta grande atenção de pesquisa. Basicamente, todo o processamento de sinais funciona com base em redes de neurônios que emitem e recebem pulsos. Portanto, de forma geral, os estímulos recebidos do sistema sensorial por uma rede neural biológica de algum modo são convertidos em trens de pulsos. Aqui, nesta tese, é apresentada uma nova arquitetura composta por duas camadas: a primeira recebe correntes de estímulos de entrada e os mapeia em trens de pulsos; a segunda recebe esses tren
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Åberg, K. Magnus. "Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation." Doctoral thesis, Stockholm University, Department of Analytical Chemistry, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-283.

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<p>This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods.</p><p>Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules.</p><p>Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating
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Hsiang, Hsi-Bao, and 向錫堡. "An improved image de-noise method based on pulse-coupled neural networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/45991084426879623188.

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碩士<br>輔仁大學<br>資訊工程學系碩士班<br>102<br>Image de-noise is the first step in image processing. Salt and pepper noises are common image noises. There are already many de-noise algorithms， such as the non local means (NL-means)， mean filtering， and median filtering. Although these filters can de-noise images， they may reduce image details at the same time， resulting image blur and distortion. To reduce image blur and distortion after de-noising， we use pulse-coupled neural network PCNN (Pulse Coupled Neural Network) to de-noise images. PCNN can effectively remove noises and preserve image details. PCNN
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Timme, Marc. "Collective Dynamics in Networks of Pulse-Coupled Oscillators." Doctoral thesis, 2002. http://hdl.handle.net/11858/00-1735-0000-0006-B575-5.

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Kirst, Christoph. "Synchronization, Neuronal Excitability, and Information Flow in Networks of Neuronal Oscillators." Doctoral thesis, 2011. http://hdl.handle.net/11858/00-1735-0000-000D-F08D-2.

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Books on the topic "Pulse-Coupled Neural Networks"

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Ma, Yide. Applications of Pulse-Coupled Neural Networks. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. Applications of Pulse-Coupled Neural Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-13745-7.

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1962-, Kinser Jason M., ed. Image processing using pulse-coupled neural networks. London: Springer, 1998.

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Lindblad, Thomas, and Jason M. Kinser. Image Processing using Pulse-Coupled Neural Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36877-6.

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Lindblad, Thomas, and Jason M. Kinser. Image Processing using Pulse-Coupled Neural Networks. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-3617-0.

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Lindblad, Thomas. Image Processing using Pulse-Coupled Neural Networks: Applications in Python. 3rd ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Brain dynamics: Synchronization and activity patterns in pulse-coupled neural nets with delays and noise. Berlin: Springer, 2002.

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Workshop, on Virtual Intelligence/Dynamic Neural Networks (9th 1998 Stockholm Sweden). Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Academic/industrial/NASA/defense technical interchange and tutorials : international conferences on virtual intelligence/dynamic neural networks--neural networks, fuzzy systems, evolutionary systems, and virtual reality/pulse coupled neural networks, 1998. Bellingham, Wash: SPIE, 1999.

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Thomas, Lindblad, Padgett Mary Lou, Kinser Jason M. 1962-, United States. National Aeronautics and Space Administration, Society of Photo-optical Instrumentation Engineers., and IEEE Industry Applications Society, eds. Proceedings, Ninth Workshop on Virtual Intelligence: Dynamic neural networks: academic/industrial/NASA/defense : technical interchange and tutorials : international conferences on virtual intelligence/dynamic neural networks: neural networks, fuzzy systems, evolutionary systems and virtual reality/pulse coupled neural networks, 1998. Bellingham, Wash., USA: SPIE, 1999.

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Image Processing Using Pulse-Coupled Neural Networks. 2nd ed. Springer, 2005.

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Book chapters on the topic "Pulse-Coupled Neural Networks"

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Pulse-Coupled Neural Networks." In Applications of Pulse-Coupled Neural Networks, 1–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_1.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Image Filtering." In Applications of Pulse-Coupled Neural Networks, 11–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_2.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Image Segmentation." In Applications of Pulse-Coupled Neural Networks, 27–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_3.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Image Coding." In Applications of Pulse-Coupled Neural Networks, 43–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_4.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Image Enhancement." In Applications of Pulse-Coupled Neural Networks, 61–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_5.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Image Fusion." In Applications of Pulse-Coupled Neural Networks, 83–109. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_6.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Feature Extraction." In Applications of Pulse-Coupled Neural Networks, 111–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_7.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "Combinatorial Optimization." In Applications of Pulse-Coupled Neural Networks, 147–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_8.

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Ma, Yide, Kun Zhan, and Zhaobin Wang. "FPGA Implementation of PCNN Algorithm." In Applications of Pulse-Coupled Neural Networks, 167–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13745-7_9.

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Li, Min, Wei Cai, and Zheng Tan. "Pulse Coupled Neural Network Based Image Fusion." In Advances in Neural Networks – ISNN 2005, 741–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11427445_119.

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Conference papers on the topic "Pulse-Coupled Neural Networks"

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Johnson, John L. "Pulse-coupled neural networks." In Critical Review Collection. SPIE, 1994. http://dx.doi.org/10.1117/12.171194.

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Timoszczuk, Antonio Pedro, and Euvaldo F. Cabral. "Speaker Recognition Using Pulse Coupled Neural Networks." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371259.

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Johnson, John L. "Pulse-coupled neural networks can benefit ATR." In Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, edited by Thomas Lindblad, Mary Lou Padgett, and Jason M. Kinser. SPIE, 1999. http://dx.doi.org/10.1117/12.343032.

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Ranganath, Heggere S., Michele R. Banish, John R. Karpinsky, Rodney L. Clark, Glynn A. Germany, and Philip G. Richards. "Three applications of pulse-coupled neural networks." In Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, edited by Thomas Lindblad, Mary Lou Padgett, and Jason M. Kinser. SPIE, 1999. http://dx.doi.org/10.1117/12.343055.

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Yourui, Huang, and Wang Shuang. "Image Segmentation Using Pulse Coupled Neural Networks." In 2008 International Conference on MultiMedia and Information Technology (MMIT). IEEE, 2008. http://dx.doi.org/10.1109/mmit.2008.121.

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Inguva, Ramarao, John L. Johnson, and Marius P. Schamschula. "Multifeature fusion using pulse-coupled neural networks." In AeroSense '99, edited by Belur V. Dasarathy. SPIE, 1999. http://dx.doi.org/10.1117/12.341357.

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Ranganath, Heggere S., and Govindaraj Kuntimad. "Iterative segmentation using pulse-coupled neural networks." In Aerospace/Defense Sensing and Controls, edited by Steven K. Rogers and Dennis W. Ruck. SPIE, 1996. http://dx.doi.org/10.1117/12.235943.

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Malkani, Mohan, Mohammad Bodruzzaman, John L. Johnson, and Joel Davis. "Center for Neural Engineering: applications of pulse-coupled neural networks." In Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, edited by Thomas Lindblad, Mary Lou Padgett, and Jason M. Kinser. SPIE, 1999. http://dx.doi.org/10.1117/12.343042.

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Hisamatsu, Kozo, and Toshimichi Saito. "Delay-induced order in pulse-coupled bifurcating neurons." In 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, 2010. http://dx.doi.org/10.1109/ijcnn.2010.5596846.

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Szekely, Geza, and Thomas Lindblad. "Parameter adaptation in a simplified pulse-coupled neural network." In Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, edited by Thomas Lindblad, Mary Lou Padgett, and Jason M. Kinser. SPIE, 1999. http://dx.doi.org/10.1117/12.343046.

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