Advanced Models of Neural Networks, Gerasimos G. Rigatos
Автор: Joe Suzuki; Maomi Ueno Название: Advanced Methodologies for Bayesian Networks ISBN: 3319283782 ISBN-13(EAN): 9783319283784 Издательство: Springer Рейтинг: Цена: 6708.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume constitutes the refereed proceedings of theSecond International Workshop on Advanced Methodologies for Bayesian Networks,AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstractspresented were carefully reviewed and selected from numerous submissions.
Автор: Shuai Li; Yinyan Zhang Название: Neural Networks for Cooperative Control of Multiple Robot Arms ISBN: 9811070369 ISBN-13(EAN): 9789811070365 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples.
Автор: C.H. Dagli Название: Artificial Neural Networks for Intelligent Manufacturing ISBN: 0412480506 ISBN-13(EAN): 9780412480508 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial neural network technology is becoming an integral part of intelligent manufacturing systems and will have a profound impact on the design of autonomous engineering systems over the next few years.
Автор: Jouke Annema Название: Feed-Forward Neural Networks ISBN: 0792395670 ISBN-13(EAN): 9780792395676 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. This book discusses some other alternative algorithms for hardware implemented perception-like neural networks.
Автор: George A. Rovithakis; Manolis A. Christodoulou Название: Adaptive Control with Recurrent High-order Neural Networks ISBN: 1447112016 ISBN-13(EAN): 9781447112013 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ...
Автор: da Silva Название: Artificial Neural Networks ISBN: 3319431617 ISBN-13(EAN): 9783319431611 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios.
Автор: Jayne Название: Engineering Applications of Neural Networks ISBN: 3319441876 ISBN-13(EAN): 9783319441870 Издательство: Springer Рейтинг: Цена: 9503.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016.The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.
Автор: Mohd. Samar Ansari Название: Non-Linear Feedback Neural Networks ISBN: 8132228960 ISBN-13(EAN): 9788132228967 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book details the non-linear synapse neural network (NoSyNN). It also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming.
Автор: Vladimir M. Krasnopolsky Название: The Application of Neural Networks in the Earth System Sciences ISBN: 9401784655 ISBN-13(EAN): 9789401784658 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a unified approach to complex practical problems in Earth Sciences, showing how neural networks are well suited for applications in satellite remote sensing, meteorology, hydrology, oceanography, weather prediction and climate studies.
Автор: Jose G. Delgado-Frias; W.R. Moore Название: VLSI for Neural Networks and Artificial Intelligence ISBN: 0306447223 ISBN-13(EAN): 9780306447228 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence.
Автор: N. Sundararajan; P. Saratchandran; Yan Li Название: Fully Tuned Radial Basis Function Neural Networks for Flight Control ISBN: 1441949151 ISBN-13(EAN): 9781441949158 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications.
Автор: Chengan Guo; Zeng-Guang Hou; Zhigang Zeng Название: Advances in Neural Networks- ISNN 2013 ISBN: 3642390641 ISBN-13(EAN): 9783642390647 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computational Neuroscience and Cognitive Science.- Information Transfer Characteristic in Memristic Neuromorphic Network.- Generation and Analysis of 3D Virtual Neurons Using Genetic Regulatory Network Model.- A Finite-Time Convergent Recurrent Neural Network Based Algorithm for the L Smallest k-Subsets Sum Problem.- Spike Train Pattern and Firing Synchronization in a Model of the Olfactory Mitral Cell.- Efficiency Improvements for Fuzzy Associative Memory.- A Study of Neural Mechanism in Emotion Regulation by Simultaneous Recording of EEG and fMRI Based on ICA.- Emotion Cognitive Reappraisal Research Based on Simultaneous Recording of EEG and BOLD Responses.- Convergence of Chaos Injection-Based Batch Backpropagation Algorithm For Feedforward Neural Networks.- Discovering the Multi-neuronal Firing Patterns Based on a New Binless Spike Trains Measure.- A Study on Dynamic Characteristics of the Hippocampal Two-Dimension Reduced Neuron Model under Current Conductance Changes.- Neural Network Models, Learning Algorithms, Stability and Convergence Analysis.- Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE-MSE Training Method.- Generalized Single-Hidden Layer Feedforward Networks.- An Approach for Designing Neural Cryptography.- Bifurcation of a Discrete-Time Cohen-Grossberg-Type BAM Neural Network with Delays.- Stability Criteria for Uncertain Linear Systems with Time-Varying Delay.- Generalized Function Projective Lag Synchronization between Two Different Neural Networks.- Application of Local Activity Theory of CNN to the Coupled Autocatalator Model.- Passivity Criterion of Stochastic T-S Fuzzy Systems with Time-Varying Delays.- Parallel Computation of a New Data Driven Algorithm for Training Neural Networks.- Stability Analysis of a Class of High Order Fuzzy Cohen-Grossberg Neural Networks with Mixed Delays and Reaction-Diffusion Terms.- A Study on the Randomness Reduction Effect of Extreme Learning Machine with Ridge Regression.- Stability of Nonnegative Periodic Solutions of High-Ordered Neural Networks.- Existence of Periodic Solution for Competitive Neural Networks with Time-Varying and Distributed Delays on Time Scales.- Global Exponential Stability in the Mean Square of Stochastic Cohen-Grossberg Neural Networks with Time-Varying and Continuous Distributed Delays.- A Delay-Partitioning Approach to Stability Analysis of Discrete-Time Recurrent Neural Networks with Randomly Occurred Nonlinearities.- The Universal Approximation Capabilities of Mellin Approximate Identity Neural Networks.- H∞ Filtering of Markovian Jumping Neural Networks with Time Delays.- Convergence Analysis for Feng's MCA Neural Network Learning Algorithm.- Anti-periodic Solutions for Cohen-Grossberg Neural Networks with Varying-Time Delays and Impulses.- Global Robust Exponential Stability in Lagrange Sense for Interval Delayed Neural Networks.- The Binary Output Units of Neural Network.- Kernel Methods, Large Margin Methods and SVM.- Support Vector Machine with Customized Kernel.- Semi-supervised Kernel Minimum Squared Error Based on Manifold Structure.- Noise Effects on Spatial Pattern Data Classification Using Wavelet Kernel PCA: A Monte Carlo Simulation Study.- SVM-SVDD: A New Method to Solve Data Description Problem with Negative Examples.- Applying Wavelet Packet Decomposition and One-Class Support Vector Machine on Vehicle Acceleration Traces for Road Anomaly Detection.- Aeroengine Turbine Exhaust Gas Temperature Prediction Using Process Support Vector Machines.- The Effect of Lateral Inhibitory Connections in Spatial Architecture Neural Network.- Empirical Mode Decomposition Based LSSVM for Ship Motion Prediction.- Optimization Algorithms / Variational Methods.- Optimal Calculation of Tensor Learning Approaches.- Repeatable Optimization Algorithm Based Discrete PSO for Virtual Network Embedding.- An Energy-Efficient Coverage Optimization Method for the Wireless Sensor Networks Based on
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