Self-Organizing Map Formation: Foundations of Neural Computation Book

	Series Foreword
	Sources
	Introduction
I	Receptive Fields	1
1	Analysis of Linsker's Simulations of Hebbian Rules	3
2	Toward a Theory of the Striate Cortex	19
3	Bayesian Self-Organization Driven by Prior Probability Distributions	39
II	Models of Topographic Maps in the Brain	53
4	Dynamics and Formation of Self-Organizing Maps	55
5	A Unifying Objective Function for Topographic Mappings	69
6	Constrained Optimization for Neural Map Formation: A Unifying Framework for Weight Growth and Normalization	83
7	How to Generate Ordered Maps by Maximizing the Mutual Information between Input and Output Signals	129
III	Models of Cortical Feature Maps	139
8	Models of Orientation and Ocular Dominance Columns in the Visual Cortex: A Critical Comparison	141
9	Development of Oriented Ocular Dominance Bands as a Consequence of Areal Geometry	185
10	The Joint Development of Orientation and Ocular Dominance: Role of Constraints	201
11	A Self-Organizing Model of "Color Blob" Formation	213
12	A Type of Duality between Self-Organizing Maps and Minimal Wiring	235
IV	Self-Organizing Maps for Unsupervised Data Analysis	247
13	A Bayesian Analysis of Self-Organizing Maps	249
14	Hyperparameter Selection for Self-Organizing Maps	277
15	GTM: The Generative Topographic Mapping	291
16	Self-Organization as an Iterative Kernel Smoothing Process	311
V	Extensions of Self-Organizing Maps	325
17	A Stochastic Self-Organizing Map for Proximity Data	327
18	Self-Organized Formation of Various Invariant-Feature Filters in the Adaptive-Subspace SOM	345
19	Faithful Representation of Separable Distributions	369
20	Dynamic Cell Structure Learns Perfectly Topology Preserving Map	385
21	An Analysis of the Elastic Net Approach to the Traveling Salesman Problem	407
22	Sorting with Self-Organizing Maps	419
	Index	423