Abstract
Hubel and Wiesel’s hypothesis on the emergence of orientation selectivity of simple cells meets some difficulties. It requires the receptive fields of GC and LGN to be highly similar in size and sub-structure while arranged in perfect order. The strict regularities make the model uneconomical in both evolution and neural computation. Varying from the classical model, we propose a new model based on an algebraic method, which estimates orientation by solving constraint satisfaction problems (CSP). The algebraic model needs not to obey the constraints of Hubel and Wiesel’s hypothesis and it is easily implemented as neural network. We also prove that both precision and efficiency of the model are practicable in mathematics. This study is significant in the aspect of explaining the neural mechanism of orientation detection, as well as of finding the circuit structure and computational route in neural network.
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Wei, H., Dong, Z. (2012). A CSP-Based Orientation Detection Model. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2012. Lecture Notes in Computer Science(), vol 7366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31561-9_6
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DOI: https://doi.org/10.1007/978-3-642-31561-9_6
Publisher Name: Springer, Berlin, Heidelberg
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