Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a novel system of interconnected Self- Organizing Maps that can be used to build feedforward and recurrent networks of maps. Prime application of interconnected maps is in modelling systems that operate with multimodal data as for example in visual and auditory cortices and multimodal association areas in cortex. A detailed example of animal categorization in which the feedworward network of self-organizing maps is employed is presented. In the example  operate with 18-dimensional data projected up on the 19-dimensional hyper-sphere so that the “dot-product” learning law can be used. One potential benefit of the multimodal map is that it allows a rich structure of parallel unimodal processing with many maps involved, follod by convergence into multimodal maps. More complex stimuli can therefore be processed without a growing map size.
['Andrew P. Paplinski', 'Lennart Gustafsson']
I am writing a research paper on a idea Multimodal feedforward self-organizing maps
[{"from": "human", "value": "I am writing a research paper on a idea Multimodal feedforward self-organizing maps"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a novel system of interconnected Self- Organizing Maps that can be used to build feedforward and recurrent networks of maps. Prime application of interconnected maps is in modelling systems that operate with multimodal data as for example in visual and auditory cortices and multimodal association areas in cortex. A detailed example of animal categorization in which the feedworward network of self-organizing maps is employed is presented. In the example  operate with 18-dimensional data projected up on the 19-dimensional hyper-sphere so that the \u201cdot-product\u201d learning law can be used. One potential benefit of the multimodal map is that it allows a rich structure of parallel unimodal processing with many maps involved, follod by convergence into multimodal maps. More complex stimuli can therefore be processed without a growing map size."}]