High capacity associative memories and connection constraints
نویسندگان
چکیده
منابع مشابه
High capacity associative memories and connection constraints
High capacity associative neural networks can be built from networks of perceptrons, trained using simple perceptron training. Such networks perform much better than those trained using the standard Hopfield one shot Hebbian learning. An experimental investigation into how such networks perform when the connection weights are not free to take any value is reported. The three restrictions invest...
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Various algorithms for constructing weight matrices for Hopfield-type associative memories are reviewed, including ones with much higher capacity than the basic model. These alternative algorithms either iteratively approximate the projection weight matrix or use simple perceptron learning. An experimental investigation of the performance of networks trained by these algorithms is presented, in...
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ژورنال
عنوان ژورنال: Connection Science
سال: 2004
ISSN: 0954-0091,1360-0494
DOI: 10.1080/09540090310001659981