Abstract
In this paper, a collaborative neurodynamic approach is proposed for sparse coding. As the formulated sparse coding optimization problem with l0 -norm objective function is NP-hard, it is reformulated as a global optimization problem based on an inverted Gaussian function. A group of neurodynamic optimization models is employed to solve the reformulated problem by gradually decreasing the value of the parameter of the inverted Gaussian function. The experimental results show the superior performance of the proposed approach.
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CITATION STYLE
Che, H., Wang, J., & Zhang, W. (2019). A Collaborative Neurodynamic Approach to Sparse Coding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11554 LNCS, pp. 454–462). Springer Verlag. https://doi.org/10.1007/978-3-030-22796-8_48
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