OSNet: A neural network implementation of order statistic filters

A neural network model, called OSNet (order statistic network), which finds the k^th largest element in an array of integers is proposed. There are four layers of neurons in OSNet, thus the total processing time is four times the processing time of one single neuron. As the number of the elements in the input array increases, only the number of neurons in each layer increases. Therefore, the processing time of OSNet is constant irrespective of the number of elements in the input array. By changing the constant k, different networks can be developed for finding various order statistics. By a meaningful combination, any member of the OSF family can be implemented. The value of the constant k in the selection networks can also be changed adaptively. By doing so, an adaptive OSNet can be obtained which can be used to implement adaptive order statistic filters. The construction of OSNet is shown, and some examples of using OSNet to implement order statistic filters are considered