Perceptron capacity revisited: classification ability for correlated patterns

Details Perceptron capacity revisited: classification ability for correlated patterns Perceptron capacity revisited: classification ability for correlated patterns

2007-12-25

arxiv.org/abs/0712.4050v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

Scientific paper

10.1088/1751-8113/41/32/324013

In this paper, we address the problem of how many randomly labeled patterns can be correctly classified by a single-layer perceptron when the patterns are correlated with each other. In order to solve this problem, two analytical schemes are developed based on the replica method and Thouless-Anderson-Palmer (TAP) approach by utilizing an integral formula concerning random rectangular matrices. The validity and relevance of the developed methodologies are shown for one known result and two example problems. A message-passing algorithm to perform the TAP scheme is also presented.

Affiliated with

Also associated with

No associations

Rating

Perceptron capacity revisited: classification ability for correlated patterns does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Perceptron capacity revisited: classification ability for correlated patterns, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Perceptron capacity revisited: classification ability for correlated patterns will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-184861