In this paper we analyze the vibrational spectra of a large ensemble of non-homologous protein structures by means of a novel tool, that we coin Hierarchical Network Model (HNM). Our coarse-grained scheme accounts for the intrinsic heterogeneity of force constants displayed by protein arrangements and also incorporates side chain degrees of freedom. Our analysis shows that vibrational entropy p...

This writing discusses the appearance of peaks and valleys in Allan deviation plots (also known as sigma-tau, root Avar, or Adev plots). This distinctly oscillatory pattern, especially at long-term T-values, usually means the presence of quasi-sinusoidal frequency modulation of an oscillator’s signal. However, quasi-sinusoidal oscillatory behavior in sigma-tau plots at long 7 may be due t o sta...

Information in the nervous system has often been considered as being represented by simultaneous discharge of a large set of neurons. We propose a learning mechanism for neural information processing in a simulated cortex model. Also, a new paradigm for pattern recognition by oscillatory neural networks is proposed. The relaxation time of the oscillatory networks is used as a criterion for nove...

In this paper we show that an unsupervised two-layered oscillatory neural network with intralayer connections, and a learning rule based on stimulus difference can behave as a Dynamic Link Matching Machine for invariant pattern recognition. We show that this architecture is robust to affine transformations. We call this architecture Oscillatory Dynamic Link Matching (ODLM).

Oscillatory dynamics of complex networks has recently attracted great attention. In this paper we study pattern formation in oscillatory complex networks consisting of excitable nodes. We find that there exist a few center nodes and small skeletons for most oscillations. Complicated and seemingly random oscillatory patterns can be viewed as well-organized target waves propagating from center no...