Tham khảo tài liệu 'robotics handbook of computer vision algorithms in image algebra part 14', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | where bz bí 1 bí 2 _ bí V and is the mth column of the transpose of w. Previous Table of Contents Next HOME SUBSCRIBE SEARCH FAQ SITEMAP CONTACT US Products Contact Us About Us Privacy Ad Info Home Use of this site is subject to certain Terms Conditions Copyright 1996-2000 EarthWeb Inc. All rights reserved. Reproduction whole or in part in any form or medium without express written permission of EarthWeb is prohibited. Read EarthWeb s privacy statement. where bz bí 1 bí 2 _ bí V and is the mth column of the transpose of w. Previous Table of Contents Next HOME SUBSCRIBE SEARCH FAQ SITEMAP CONTACT US Products Contact Us About Us Privacy Ad Info Home Use of this site is subject to certain Terms Conditions Copyright 1996-2000 EarthWeb Inc. All rights reserved. Reproduction whole or in part in any form or medium without express written permission of EarthWeb is prohibited. Read EarthWeb s privacy statement. followed by the feedback update of Sa improves the recall accuracy of the net. Continue updating the neurons in Sb followed by those in Sa until further iteration produces no state change for any neuron. At time of convergence t c the association that the BAM has recalled is a b where a ac 1 ac 2 . ac M and b bc 1 bc 2 . bc N . Step 4. Continue classification. To classify another pattern repeat Steps 2 and 3. Example Figure shows the evolution of neuron states in a BAM from initialization to convergence. Three lowercase-uppercase character image associations a A b B and c C were used to create the weight matrix w. The lowercase characters are 12 X 12 images and the uppercase characters are 16 X 16 images. The conversion from image to pattern and vice versa is done as in the example of Section . A corrupted a is input onto the Sa neurons of the net. Image Algebra Formulation Let a 1 I and - I be the image variables used to represent the state for neurons in the sets Sa and Sb respectively. Initialize a with the unknown pattern. The neuron values of Sb are t
