Holographic Reduced Representation: Distributed Representation for Cognitive Structures Book

	Preface
1	Introduction	1
2	Review of connectionist and distributed memory models	25
3	Holographic reduced representations	93
4	HRRs in the frequency domain	145
5	Using convolution-based storage in systems that learn	153
6	Estimating analogical similarity	175
7	Discussion	221
App. A	Means and variances of similarities between bindings	233
App. B	The capacity of a superposition memory	235
App. C	A lower bound for the capacity of superposition memories	245
App. D	The capacity of convolution-based associative memories	249
App. E	A lower bound for the capacity of convolution memories	259
App. F	Means and variances of a signal	261
App. G	The effect of normalization on dot-products	263
App. H	HRRs with circular vectors	267
App. I	Arithmetic tables: an example of HRRs with many items in memory	273
	References	277
	Subject Index	289
	Author Index	297