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Neural and Automata Networks Dynamical Behavior and Applications [Hardcover]

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  • Category: Books (Computers)
  • Author:  Goles, E., Mart?nez, Servet
  • Author:  Goles, E., Mart?nez, Servet
  • ISBN-10:  0792306325
  • ISBN-10:  0792306325
  • ISBN-13:  9780792306320
  • ISBN-13:  9780792306320
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Feb-1990
  • Pub Date:  01-Feb-1990
  • SKU:  0792306325-11-SPRI
  • SKU:  0792306325-11-SPRI
  • Item ID: 100841685
  • List Price: $54.99
  • Seller: ShopSpell
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  • Delivery by: Jul 08 to Jul 10
  • Notes: Brand New Book. Order Now.
1. Automata Networks.- 1.1. Introduction.- 1.2. Definitions Regarding Automata Networks.- 1.3. Cellular Automata.- 1.4. Complexity Results for Automata Networks.- 1.5. Neural Networks.- 1.6. Examples of Automata Networks.- 1.6.1. XOR Networks.- 1.6.2. Next Majority Rule.- 1.6.3. Multithreshold Automaton.- 1.6.4. The Ising Automaton.- 1.6.5. Bounded Neural Network (BNN).- 1.6.6. Bounded Majority Network.- 2. Algebraic Invariants on Neural Networks.- 2.1. Introduction.- 2.2. K-Chains in 0-1 Periodic Sequences.- 2.3. Covariance in Time.- 2.4. Algebraic Invariants of Synchronous Iteration on Neural Networks.- 2.5. Algebraic Invariants of Sequential Iteration on Neural Networks.- 2.6. Block Sequential Iteration on Neural Networks.- 2.7. Iteration with Memory.- 2.8. Synchronous Iteration on Majority Networks.- 3. Lyapunov Functionals Associated to Neural Networks.- 3.1. Introduction.- 3.2. Synchronous Iteration.- 3.3. Sequential Iteration.- 3.4. Tie Rules for Neural Networks.- 3.5. Antisymmetrical Neural Networks.- 3.6. A Class of Symmetric Networks with Exponential Transient Length for Synchronous Iteration.- 3.7. Exponential Transient Classes for Sequential Iteration.- 4. Uniform One and Two Dimensional Neural Networks.- 4.1. Introduction.- 4.2. One-Dimensional Majority Automata.- 4.3. Two-Dimensional Majority Cellular Automata.- 4.3.1. 3-Threshold Case.- 4.3.2. 2-Threshold Case.- 4.4. Non-Symmetric One-Dimensional Bounded Neural Networks.- 4.5. Two-Dimensional Bounded Neural Networks.- 5. Continuous and Cyclically Monotone Networks.- 5.1. Introduction.- 5.2. Positive Networks.- 5.3. Multithreshold Networks.- 5.4. Approximation of Continuous Networks by Multithreshold Networks.- 5.5. Cyclically Monotone Networks.- 5.6. Positive Definite Interactions. The Maximization Problem.- 5.7. Sequential Iteration for Decreasing Real Functions and Optimization Problems.- 5.8. A Generalized Dynamics.- 5.9. Chain-Symmetric Matrices.- 6. Applications on Thermodynamic Limits on the Betl“F
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