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Computational Architectures Integrating Neural and Symbolic Processes

Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently;

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Cognitive Modeling

of human cognition. It covers major approaches and architectures, both neural network and symbolic; major theoretical issues; and specific;

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Computational Learning Theory & Natural Learning Systems V 2 - Intersections Between Theory & Experiment

areas of learning research, computational learning theory, neural network research and symbolic machine learning.;

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Cognitive Sciences at the Leading Edge

of explicit computational theories and models of mental (but not brain) processes analogous to the workings of a digital computer. Connectionist;

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Neural Network Methods in Natural Language Processing

neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures;

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Neural Network Methods in Natural Language Processing

neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures;

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Computational Models of Brain and Behavior

methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models;

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Computational Models Of Cognitive Processes - Proceedings Of The 13th Neural Computation And Psychology Workshop

Computational Models of Cognitive Processes collects refereed versions of papers presented at the 13th Neural Computation and Psychology;

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Modularity Of Mind

. Most psychologists study horizontal processes like memory and information flow; Fodor postulates a vertical and modular psychological;

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Introduction to Neural Networks for Java, Second Edition

. Neural network architectures, such as the feedforward, Hopfield, and self-organizing map architectures are discussed.;

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Recurrent Neural Networks

This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from;

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Supervised and Unsupervised Pattern Recognition

third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional;

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Hardware Architectures for Deep Learning

neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a;

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New Research in Cognitive Sciences

dynamic systems. Symbolic -- holds that cognition can be explained using operations on symbols, by means of explicit computational theories and;

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Artificial Neural Networks in Biological and Environmental Analysis

environmental processes. Artificial Neural Networks in Biological and Environmental Analysis provides an in-depth and timely perspective on the;

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Artificial Neural Networks in Biological and Environmental Analysis

environmental processes. Artificial Neural Networks in Biological and Environmental Analysis provides an in-depth and timely perspective on the;

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Cognitive Sciences Research Progress

of explicit computational theories and models of mental (but not brain) processes analogous to the workings of a digital computer. Connectionist;

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Neural Network Analysis, Architectures and Applications

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter;

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Neural Information Processing

intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing;

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Memristive Devices for Brain-Inspired Computing

architectures and target applicationsCovers a broad range of applications, including brain-inspired computing, computational memory, deep;

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Algorithms and Architectures

This volume is the first diverse and comprehensive treatment of algorithms and architectures for the realization of neural network;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Computational Intelligence

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the;

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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault;

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Neural Networks with Keras Cookbook

multiple neural network architectures such as CNN, RNN, LSTM in Keras Discover tips and tricks for designing a robust neural network to solve real;

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Neurocomputing

execution on a GPU; EEG montages for the diagnosis of Alzheimer's disease; design and training of neural architectures using extreme learning;

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