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Artificial Neural Networks
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, Gest...
Decision Making and Imperfection
Decision making (DM) is ubiquitous in both natural and artificial systems. The decisions made often differ from those recommended by the axiomatically well-grounded normative Bayesian decision theory, in a large part due to limited cognitive and computational resources of decision makers (either artificial units or humans). This state of a airs is often described by saying that decision makers are imperfect and exhibit bounded rationality. The neglected influence of emotional state and personality traits is an additional reason why normative theory fails to model human DM process. The book is a joint effort of the top researchers from different disciplines to identify sources of imperfection...
Time and the Brain
Since the days of Galileo, time has been a fundamental variable in scientific attempts to understand the natural world. Once the first recordings of electrical activity in the brain had been made, it became clear that electrical signals from the brain consist of very complex temporal patterns. This can now be demonstrated by recordings at the single unit level and by electroencephalography (EEG). Time and the Brain explores modern approaches to these temporal aspects of electrical brain activity. The temporal structure as revealed from trains of impulses from single nerve cells and from EEG recordings are discussed in depth together with an exploration of correlations with behaviour and psychology. The single cell and EEG approaches often tend to be segregated as the research occurs in laboratories in different parts of the world. By bringing together modern information acquired using both methods it is hoped that they can become better integrated as complimentary windows on the information processing achieved by the brain.
Advances in Neuro-Information Processing
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
Artificial Neural Networks and Machine Learning -- ICANN 2012
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.
Brain, Vision, and Artificial Intelligence
This book constitutes the refereed proceedings of the First International Symposium on Brain, Vision and Artificial Intelligence, BVAI 2005, held in Naples, Italy in October 2005. The 48 revised papers presented together with 6 invited lectures were carefully reviewed and selected from more than 80 submissions for inclusion in the book. The papers are addressed to the following main topics and sub-topics: brain basics - neuroanatomy and physiology, development, plasticity and learning, synaptic, neuronic and neural network modelling; natural vision - visual neurosciences, mechanisms and model systems, visual perception, visual cognition; artificial vision - shape perception, shape analysis and recognition, shape understanding; artificial inteligence - hybrid intelligent systems, agents, and cognitive models.
The Practice of Data Analysis
This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John W. Tukey, one of the most influential statisticians of the twentieth century, on the occasion of his eightieth birthday. Contributors, some of them Tukey's former students, use his general theoretical work and his specific contributions to Exploratory Data Analysis as the point of departure for their papers. They cover topics from "pure" data analysis, such as gaussianizing transformations and regression estimates, and from "applied" subjects, such as the best way to rank the abilities of chess ...
Artificial Neural Networks-Icann '97
Content Description #Includes bibliographical references and index.
Advances in Cognitive Neurodynamics (IV)
This volume is the proceedings of the 4th International Conference on Cognitive Neurodynamics (ICCN2013) held in Sweden in 2013. The included papers reflect the large span of research presented and are grouped in ten parts that are organized essentially in a top-down structure. The first parts deal with social/interactive (I) and mental (II) aspects of brain functions and their relation to perception and cognition (III). Next, more specific aspects of sensory systems (IV) and neural network dynamics of brain functions (V), including the effects of oscillations, synchronization and synaptic plasticity (VI), are addressed, followed by papers particularly emphasizing the use of neural computation and information processing (VII). With the next two parts, the levels of cellular and intracellular processes (VIII) and finally quantum effects (IX) are reached. The last part (X) is devoted to the contributions invited by the Dynamic Brain Forum (DBF), which was co-organized with ICCN2013.
Artificial Neural Networks and Machine Learning - ICANN 2011
This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.
