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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Beaton, D. Valova, I. MacLean, D. |
| Copyright Year | 2009 |
| Description | Author affiliation: Research and Innovation in Mathematics Education, University of Massachusetts Dartmouth, 200 Mill Rd., Suite 150B, Fairhaven, 02719, USA (Beaton, D.) || Computer and Information Science, University of Massachusett Dartmouth, 285 Old Westport Rd, 02747, USA (Valova, I.; MacLean, D.) |
| Abstract | TurSOM [1], short for Turing Self-Organizing Map, introduces new concepts, responsibilities and mechanisms to the traditional SOM algorithm. It draws its inspiration from Turing Unorganized Machines, competitive learning techniques, and SOM algorithms. Turing's unorganized machines (TUM) were one of the first computational concepts of modeling the cortex. Turing also described these machines as having self-organizing behaviors. The primary difference between Turing's self-organization description, and more traditional models we are familiar with (Grossberg, Kohonen), are that connections, rather than neurons, self-organize. TurSOM adheres to unsupervised, competitive learning techniques, wherein all neurons, and all connections between them are self-organizing and competing. As such, it presents a novel self-organizing neural network algorithm that eliminates the need for post-processing methods for cluster identification. |
| Starting Page | 288 |
| Ending Page | 295 |
| File Size | 1909043 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424435487 |
| ISSN | 10987576 |
| DOI | 10.1109/IJCNN.2009.5178720 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Brain modeling Clustering algorithms Machine learning Neurons Partitioning algorithms Turing machines Computational modeling Artificial neural networks Computational and artificial intelligence Machine intelligence |
| Content Type | Text |
| Resource Type | Article |
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