Assuming adaptation of the visual cortex to its environment, we analyse the invariance found in natural images to explain the selective response of visual cortical neurons. We argue that the invariant structure of images can be formally expressed by dot-products. Utilizing the specific structure of the proposed model we show how non-linear functions can be learned efficiently from natural image...

The rank statistics Sn(t) = 1 n ∑n i=1 ciRi(t) (t ∈ R), with Ri(t) being the rank of ei−txi, i = 1, . . . , n and e1, . . . , en being the random sample from the basic distribution with the cdf F , are considered as a random process with t in the role of parameter. Under some assumptions on ci, xi and on the underlying distribution, it is proved that the process {Sn( t √n)− Sn(0)− ESn(t), |t|2 ...

We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis...

This letter describes algorithms for global thresholding of grey-tone images which use second-order grey level statistics. Two measures of interaction between classes of intensity levels are defined on simple co-occurance matrices and are used to evaluate and select thresholds. One of these measures is seen to be independent of the grey level histogram and effective in selecting thresholds for ...

This article discusses a method that can aid in diagnosing root causes of product and process variability in complex manufacturing processes, when large amounts of multivariate in-process measurement data are available. A linear structured model, similar to the standard factor analysis model, is used to generically represent the variation patterns that result from the root causes. Blind source ...