C++ Neural Networks and Fuzzy Logic: Preface

Temporal Associative Memory

Another type of associative memory is temporal associative memory. Amari, a pioneer in the field of neural

networks, constructed a Temporal Associative Memory model that has feedback connections between the

input and output layers. The forte of this model is that it can store and retrieve spatiotemporal patterns. An

example of a spatiotemporal pattern is a waveform of a speech segment.

Brain−State−in−a−Box

Introduced by James Anderson and others, this network differs from the single−layer fully connected Hopfield

network in that Brain−State−in−a−Box uses what we call recurrent connections as well. Each neuron has a

connection to itself. With target patterns available, a modified Hebbian learning rule is used. The adjustment

to a connection weight is proportional to the product of the desired output and the error in the computed

output. You will see more on Hebbian learning in Chapter 6. This network is adept at noise tolerance, and it

can accomplish pattern completion. Figure 5.7 shows a Brain−State−in−a−Box network.

Figure 5.7

  A Brain−State−in−a−Box, network.