Pulse-coupled neural networks
Multi focus Image Fusion Algorithm Based on Motivated Pulse Coupled Neural Networks Using Nonsubsampled Contourlet Transform
... motivated pulse coupled neural networks using nonsubsampled contourlet transform (NSCT) is ...the Pulse coupled neural network (PCNN) to obtain the firing times of the low ...
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Medical image fusion based on pulse coupled neural networks and multi feature fuzzy clustering
... on pulse coupled neural networks (PCNN) and multi-feature fuzzy clustering is proposed, which makes use of the multi-feature of image and combines the advantages of the local en- tropy and ...
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Hybrid Multimodality Medical Image Fusion based on Guided Image Filter with Pulse Coupled Neural Network
... subband images changes. Xingbin Liu, Wenbo Mei, et al.[5] proposed a new technique namely Structure tensor and non subsampled shearlet transform (NSST) to extract geometric features. A novel unified optimization model is ...
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Historical Document Preservation Using ICM and Filters
... with pulse-coupled neural network (PCNN) model is used along with ...a neural network, called Eckhorn’s model, to simulate this ...similar neural behavior based on the study of the ...
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The Parameter Learning Method for Similar Image Rating Using Pulse Coupled Neural Network
... using pulse coupled neural networks,” in Proceedings of the international Conference on N eural Networks, Orlando, ...using pulse-coupled neural networks, ...
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Plant Species Classification through New Feature Extraction Model Velocity Clamping Based Intersecting Cortical Model
... Parameters are determined based on firing mechanism of pulse coupled neural networks. Theoretical analysis is needed for representing dynamic behavior of PCNN, which affects the network ...
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Stability of the splay state in networks of pulse-coupled neurons
... in pulse-coupled net- works ...globally- coupled oscillators, there are very few theoretical results and they mostly concern fully-synchronised regime or specific types of neurons ...
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Mathematical frameworks for oscillatory network dynamics in neuroscience
... example, neural mass models of the type described in ...spiking networks directly (usually under some restrictive assumption such as global coupling) as in the spike-density approach [289], which makes ...
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Linear Pulse Coupled Oscillators Model¬—A New Approach for Time Synchronization in Wireless Sensor Networks
... and neural network makes the research of pulse-coupled oscillators again a popular ...the pulse-coupling models proposed by Peskin and Mirollo & Strogatz are not suitable for direct ...
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Adaptive Frequency Neural Networks for Dynamic Pulse and Metre Perception.
... The mode-locking to high order integer ratios, nonlin- ear response, and internal connectivity set GFNNs apart from many linear filtering methods such as the resonating comb filters and Kalman filters used in many signal ...
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Coupled Nonlinear Transmission Lines for Doubling Repetition Rate of Incident Pulse Streams
... NLTL pulse generator using two ...short pulse with 30 ps ...short pulse train using an NLTL connected with an ...periodic pulse train with ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... J. Alamelu Mangai et al presented A Novel Feature Selection Framework for Automatic Web Page Classification [13]. Most of the classification algorithm’s performance depended on the elimination of the noisy and outlier ...
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A novel approach for fusion of panchromatic and multispectral image through neural network
... used to evaluate and merge information from different resource. Feature level is achieved on extraction of various features like direction length, shape and edges. Decision level is a high level fusion which points to a ...
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Automatic red blood cell counting based on particle area
... Other method used for segmentation and counting process by Adagale in 2013 [4] was Pulse Coupled Neural Network PCNN combined with template matching algorithm since PCNN alone cannot cop[r] ...
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BLOOD CELL IMAGE SEGMENTATION AND COUNTING
... In traditional terms, blood cell analysis i.e. complete blood cell count (CBC) is done as a “convention”. In which it measures the red blood cells, white blood cells usually assesses the size and shape of red blood cells ...
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Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... to neural networks, this indicates that we search for a neural net- work and an adaptation algorithm that improves continuously when being trained in a stationary environment but, when confronted ...
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An Introduction to Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... Neural networks are often used for statistical analysis and data modelling, in which their role is perceived as an alternative to standard nonlinear regression or cluster analysis techniques (Cheng & ...
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Data Mining using Neural Networks
... the neural networks can be used for maintaining and exploring new data sciences in order to provide encouraging frameworks in managing infinite volumes of data we have at our ...and neural ...
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Deep Learning as a Frontier of Machine Learning: A Review
... Deep learning, a family of machine learning algorithms, is inspired by the biological process of neural networks is dominating in many applications and proving its advantage over conventional machine ...
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Recognizing Handwritten Alphabets using Neural Networks
... Artificial Neural Networks which mimics the neurons of the human ...by Neural Networks. Neural Networks have been applied to a range of problems like stock market prediction, ...
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