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--- lectures [2011/02/27 22:57] – nick
+++ lectures [2011/09/29 15:52] (current) – nick
@@ Line 9: / Line 9: @@
      * {{:flcases.pdf|fuzzy logic cases}}
   * {{:lecture_4.ppt|Lecture 4 - more roughsets}}
-  * {{:lecture_5a.ppt|Lecture 5 - more roughsets-Various Reducts & Rough Sets Applications}}
+  * {{:lecture_5x.ppt|Lecture 5 - more roughsets-Various Reducts & Rough Sets Applications}}
      * {{:umuai2007_aug31.pdf|application 1}}
      * {{:ohrn_thesis.pdf|application 2}}
@@ Line 24: / Line 24: @@
   * {{:cse4403lec13.pdf|Lecture 13 - Discussion on Bayesian Networks}}
   * {{:lecture_14_copy.ppt|Lecture 14 - Recurrent Neural Networks}}
-     * {{:lecture_14a.ppt|Lecture 14a - The Next Generation Neural Networks - G. Hinton}}
+     * {{:lecture_14aa.ppt|Lecture 14a - The Next Generation Neural Networks - G. Hinton}}
      * {{:lecture_14b.ppt|Lecture 14b - Neural Networks - Single Layer}}
      * {{:lecture_14c.ppt|Lecture 14c - Neural Networks - Probabilistic}}
      * {{:lecture_14d.ppt|Lecture 14d - Neural Networks - Learning}}
      * {{:lecture_14f.ppt|Lecture 14e - Neural Networks - Feed Forward}}
-  * {{|Lecture 15 - Web Intelligence, Brain Informatics and Granular Computing}}
+  * {{:lecture_15.ppt||Lecture 15 - Web Intelligence, Brain Informatics and Granular Computing}}
-  * {{:wimbit.ppt|Lecture 15a - Web Intelligence meet Brain Informatics}}
+     * {{:wimbit.ppt|Lecture 15a - Web Intelligence meet Brain Informatics}}
-  * {{|Lecture 16 - Granular Computing}}
+  * {{:lecture_16.ppt|Lecture 16 - Granular Computing}}
+     * {{:att00207.ppt|Lecture 16a - Zadeh's Granular Computing}}
+     * {{:conceptual_granularity_fuzzy_and_rough_sets.ppt|Lecture 16 - Erich's Granular Computing}}
+     * {{:granular_computing.pdf|Lecture 16c - Skrowon's Granular Computing}}
+  * {{:lecture_17.ppt|Lecture 17 - Introduction to Expert Systems}}
+  * {{:bayesian_network_modeling_for_evolutionary_genetic_structures.ppt|Lecture 18 - Bayesian Network Modeling for evolutionary genetic structures}}
+  * {{:cercone.ppt|Lecture 19 - A graph theory approach to characterize the relationshipbetween protein functions and structure of biological networks}}
+  * {{:lecture_20.ppt|Lecture 20 & 21- Ontology and Representation}}
+  * {{:lecture_22.ppt|Lecture 22 - Course Review}}