Neural Networks: Computational Models and Applications

• Κύριοι συγγραφείς: Tang, Huajin (Συγγραφέας), Tan, Kay Chen (Συγγραφέας), Yi, Zhang (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
• Σειρά: Studies in Computational Intelligence, 53
• Θέματα: Computer science.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Computer Science.; Artificial Intelligence (incl. Robotics).; Appl.Mathematics/Computational Methods of Engineering.

Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their ap...

Πίνακας περιεχομένων:

• Feedforward Neural Networks and Training Methods
• New Dynamical Optimal Learning for Linear Multilayer FNN
• Fundamentals of Dynamic Systems
• Various Computational Models and Applications
• Convergence Analysis of Discrete Time RNNs for Linear Variational Inequality Problem
• Parameter Settings of Hopfield Networks Applied to Traveling Salesman Problems
• Competitive Model for Combinatorial Optimization Problems
• Competitive Neural Networks for Image Segmentation
• Columnar Competitive Model for Solving Multi-Traveling Salesman Problem
• Improving Local Minima of Columnar Competitive Model for TSPs
• A New Algorithm for Finding the Shortest Paths Using PCNN
• Qualitative Analysis for Neural Networks with LT Transfer Functions
• Analysis of Cyclic Dynamics for Networks of Linear Threshold Neurons
• LT Network Dynamics and Analog Associative Memory
• Output Convergence Analysis for Delayed RNN with Time Varying Inputs
• Background Neural Networks with Uniform Firing Rate and Background Input.