Introduction to neural and cognitive modeling
This thoroughly, thoughtfully revised edition of a very successful textbook makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as to others interested in these models. Research since the publication of the first edition has bee...
| Main Author: | Levine, Daniel S. |
|---|---|
| Other Authors: | EBSCOhost. |
| Format: | eBook |
| Language: | English |
| Published: |
Mahwah, N.J. :
Lawrence Erlbaum Associates Publishers,
2000.
|
| Physical Description: |
1 online resource (xix, 491 pages) : illustrations. |
| Edition: | 2nd ed. |
| Subjects: |
Table of Contents:
- Brain and Machine: The Same Principles?
- What Are Neural Networks?
- Is Biological Realism a Virtue?
- What Are Some Principles of Neural Network Theory?
- Methodological Considerations
- Historical Outline
- Digital Approaches
- McCulloch-Pitts Network
- Early Approaches to Modeling Learning: Hull and Hebb
- Rosenblatt's Perceptrons
- Some Experiments With Perceptrons
- Divergence of Artificial Intelligence and Neural Modeling
- Continuous and Random Net Approaches
- Rashevsky's Work
- Early Random Net Models
- Reconciling Randomness and Specificity
- Definitions and Detailed Rules for Rosenblatt's Perceptrons
- Detailed Description: Perceptron to Discriminate Vertical Versus Horizontal
- Associative Learning and Synaptic Plasticity
- Physiological Bases for Learning
- Rules for Associative Learning
- Outstars and Other Early Models of Grossberg
- Anderson's Connection Matrices
- Kohonen's Early Work
- Learning Rules Related to Changes in Node Activities
- Klopf's Hedonistic Neurons and the Sutton-Barto Learning Rule
- Error Correction and Back Propagation
- Differential Hebbian Idea
- Gated Dipole Theory
- Associative Learning of Patterns
- Kohonen's Recent Work: Autoassociation and Heteroassociation
- Kosko's Bidirectional Associative Memory
- Equations for Networks in Chapter 3, and Physiological Details
- Detailed Description: The Gated Dipole
- Competition, Lateral Inhibition, and Short-Term Memory
- Contrast Enhancement, Competition, and Normalization.