Hsu T C, Wang S D
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei.
IEEE Trans Neural Netw. 1997;8(6):1557-61. doi: 10.1109/72.641477.
In this article we present a k-winners-take-all (k-WTA) neural net that is established based on the concept of the constant time sorting machine by Hsu and Wang. It fits some specific applications, such as real-time processing, since its Theta(1) time complexity is independent to the problem size. The proposed k-WTA neural net produces the solution in constant time while the Hopfield network requires a relatively long transient to converge to the solution from some initial states.
在本文中，我们提出了一种基于许和王的恒定时间排序机概念建立的k胜者全得（k-WTA）神经网络。它适用于一些特定应用，如实时处理，因为其Theta(1)时间复杂度与问题规模无关。所提出的k-WTA神经网络在恒定时间内产生解决方案，而霍普菲尔德网络从某些初始状态收敛到解决方案需要相对较长的暂态时间。
