Artificial Neural Networks And Machine Learning Icann 2012
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Artificial Neural Networks And Machine Learning Icann 2012
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Author : Springer
language : en
Publisher:
Release Date : 2012-09-27
Artificial Neural Networks And Machine Learning Icann 2012 written by Springer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-27 with categories.
Artificial Neural Networks And Machine Learning Icann 2012
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Author : Alessandro Villa
language : en
Publisher: Springer
Release Date : 2012-09-19
Artificial Neural Networks And Machine Learning Icann 2012 written by Alessandro Villa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-19 with Computers categories.
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.
Artificial Neural Networks And Machine Learning Icann 2012
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Author :
language : en
Publisher:
Release Date : 2012
Artificial Neural Networks And Machine Learning Icann 2012 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Artificial Neural Networks And Machine Learning Icann 2012
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Author : Alessandro Villa
language : en
Publisher: Springer
Release Date : 2012-09-19
Artificial Neural Networks And Machine Learning Icann 2012 written by Alessandro Villa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-19 with Computers categories.
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.
Artificial Neural Networks And Machine Learning Icann 2013
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Author : Valeri Mladenov
language : en
Publisher: Springer
Release Date : 2013-09-04
Artificial Neural Networks And Machine Learning Icann 2013 written by Valeri Mladenov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-04 with Computers categories.
The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully reviewed and selected from 128 submissions. The focus of the papers is on following topics: neurofinance graphical network models, brain machine interfaces, evolutionary neural networks, neurodynamics, complex systems, neuroinformatics, neuroengineering, hybrid systems, computational biology, neural hardware, bioinspired embedded systems, and collective intelligence.
Artificial Neural Networks
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Author : Petia Koprinkova-Hristova
language : en
Publisher: Springer
Release Date : 2014-09-02
Artificial Neural Networks written by Petia Koprinkova-Hristova and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-02 with Technology & Engineering categories.
The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Proceedings
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Author : Michel Verleysen
language : en
Publisher: Presses universitaires de Louvain
Release Date : 2015
Proceedings written by Michel Verleysen and has been published by Presses universitaires de Louvain this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Artificial Neural Networks And Machine Learning Icann 2021
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Author : Igor Farkaš
language : en
Publisher: Springer Nature
Release Date : 2021-09-10
Artificial Neural Networks And Machine Learning Icann 2021 written by Igor Farkaš and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-10 with Computers categories.
The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as generative neural networks, graph neural networks, hierarchical and ensemble models, human pose estimation, image processing, image segmentation, knowledge distillation, and medical image processing. *The conference was held online 2021 due to the COVID-19 pandemic.
Space Time Computing With Temporal Neural Networks
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Author : James E. Smith
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-05-18
Space Time Computing With Temporal Neural Networks written by James E. Smith and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-18 with Computers categories.
Understanding and implementing the brain's computational paradigm is the one true grand challenge facing computer researchers. Not only are the brain's computational capabilities far beyond those of conventional computers, its energy efficiency is truly remarkable. This book, written from the perspective of a computer designer and targeted at computer researchers, is intended to give both background and lay out a course of action for studying the brain's computational paradigm. It contains a mix of concepts and ideas drawn from computational neuroscience, combined with those of the author. As background, relevant biological features are described in terms of their computational and communication properties. The brain's neocortex is constructed of massively interconnected neurons that compute and communicate via voltage spikes, and a strong argument can be made that precise spike timing is an essential element of the paradigm. Drawing from the biological features, a mathematics-based computational paradigm is constructed. The key feature is spiking neurons that perform communication and processing in space-time, with emphasis on time. In these paradigms, time is used as a freely available resource for both communication and computation. Neuron models are first discussed in general, and one is chosen for detailed development. Using the model, single-neuron computation is first explored. Neuron inputs are encoded as spike patterns, and the neuron is trained to identify input pattern similarities. Individual neurons are building blocks for constructing larger ensembles, referred to as "columns". These columns are trained in an unsupervised manner and operate collectively to perform the basic cognitive function of pattern clustering. Similar input patterns are mapped to a much smaller set of similar output patterns, thereby dividing the input patterns into identifiable clusters. Larger cognitive systems are formed by combining columns into a hierarchical architecture. These higher level architectures are the subject of ongoing study, and progress to date is described in detail in later chapters. Simulation plays a major role in model development, and the simulation infrastructure developed by the author is described.
Model Based Design Of Adaptive Embedded Systems
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Author : Twan Basten
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-15
Model Based Design Of Adaptive Embedded Systems written by Twan Basten and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-15 with Technology & Engineering categories.
This book describes model-based development of adaptive embedded systems, which enable improved functionality using the same resources. The techniques presented facilitate design from a higher level of abstraction, focusing on the problem domain rather than on the solution domain, thereby increasing development efficiency. Models are used to capture system specifications and to implement (manually or automatically) system functionality. The authors demonstrate the real impact of adaptivity on engineering of embedded systems by providing several industrial examples of the models used in the development of adaptive embedded systems.