Optoelectronic Reservoir Computing

Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-electronic implementation of reservoir computing based on a recently proposed architecture consisting of a single non linear node and a delay line. Our implementation is sufficiently fast for real time information processing. We illustrate its performance on tasks of practical importance such as nonlinear channel equalization and speech recognition, and obtain results comparable to state of the art digital implementations.Comment: Contains main paper and two Supplementary Material

Creep motion in a granular pile exhibiting steady surface flow

We investigate experimentally granular piles exhibiting steady surface flow. Below the surface flow, it has been believed exisitence of a `frozen' bulk region, but our results show absence of such a frozen bulk. We report here that even the particles in deep layers in the bulk exhibit very slow flow and that such motion can be detected at an arbitrary depth. The mean velocity of the creep motion decays exponentially with depth, and the characteristic decay length is approximately equal to the particle-size and independent of the flow rate. It is expected that the creep motion we have seeen is observable in all sheared granular systems.Comment: 3 pages, 4 figure

Towards a neural hierarchy of time scales for motor control

Animals show remarkable rich motion skills which are still far from realizable with robots. Inspired by the neural circuits which generate rhythmic motion patterns in the spinal cord of all vertebrates, one main research direction points towards the use of central pattern generators in robots. On of the key advantages of this, is that the dimensionality of the control problem is reduced. In this work we investigate this further by introducing a multi-timescale control hierarchy with at its core a hierarchy of recurrent neural networks. By means of some robot experiments, we demonstrate that this hierarchy can embed any rhythmic motor signal by imitation learning. Furthermore, the proposed hierarchy allows the tracking of several high level motion properties (e.g.: amplitude and offset), which are usually observed at a slower rate than the generated motion. Although these experiments are preliminary, the results are promising and have the potential to open the door for rich motor skills and advanced control

A Model for Force Fluctuations in Bead Packs

We study theoretically the complex network of forces that is responsible for the static structure and properties of granular materials. We present detailed calculations for a model in which the fluctuations in the force distribution arise because of variations in the contact angles and the constraints imposed by the force balance on each bead of the pile. We compare our results for force distribution function for this model, including exact results for certain contact angle probability distributions, with numerical simulations of force distributions in random sphere packings. This model reproduces many aspects of the force distribution observed both in experiment and in numerical simulations of sphere packings

Escaping from nonhyperbolic chaotic attractors

We study the noise-induced escape process from chaotic attractors in nonhyperbolic systems. We provide a general mechanism of escape in the low noise limit, employing the theory of large fluctuations. Specifically, this is achieved by solving the variational equations of the auxiliary Hamiltonian system and by incorporating the initial conditions on the chaotic attractor unambiguously. Our results are exemplified with the H{\'e}non and the Ikeda map and can be implemented straightforwardly to experimental data.Comment: replaced with published versio

Clustering and Non-Gaussian Behavior in Granular Matter

We investigate the properties of a model of granular matter consisting of $N$ Brownian particles on a line subject to inelastic mutual collisions. This model displays a genuine thermodynamic limit for the mean values of the energy and the energy dissipation. When the typical relaxation time $\tau$ associated with the Brownian process is small compared with the mean collision time $\tau_c$ the spatial density is nearly homogeneous and the velocity probability distribution is gaussian. In the opposite limit $\tau \gg \tau_c$ one has strong spatial clustering, with a fractal distribution of particles, and the velocity probability distribution strongly deviates from the gaussian one.Comment: 4 pages including 3 eps figures, LaTex, added references, corrected typos, minimally changed contents and abstract, to published in Phys.Rev.Lett. (tentatively on 28th of October, 1998

STREAM: Static Thermodynamic REgulAtory Model of transcription

Motivation: Understanding the transcriptional regulation of a gene in detail is a crucial step towards uncovering and ultimately utilizing the regulatory grammar of the genome. Modeling transcriptional regulation using thermodynamic equations has become an increasingly important approach towards this goal

Instability of dilute granular flow on rough slope

We study numerically the stability of granular flow on a rough slope in collisional flow regime in the two-dimension. We examine the density dependence of the flowing behavior in low density region, and demonstrate that the particle collisions stabilize the flow above a certain density in the parameter region where a single particle shows an accelerated behavior. Within this parameter regime, however, the uniform flow is only metastable and is shown to be unstable against clustering when the particle density is not high enough.Comment: 4 pages, 6 figures, submitted to J. Phys. Soc. Jpn.; Fig. 2 replaced; references added; comments added; misprints correcte

Silicates in D-type symbiotic stars: an ISO overview

We investigate the IR spectral features of a sample of D-type symbiotic stars. Analyzing unexploited ISO-SWS data, deriving the basic observational parameters of dust bands and comparing them with respect to those observed in other astronomical sources, we try to highlight the effect of environment on grain chemistry and physic. We find strong amorphous silicate emission bands at 10 micron and 18 micron in a large fraction of the sample. The analysis of the 10 micron band, along with a direct comparison with several astronomical sources, reveals that silicate dust in symbiotic stars shows features between the characteristic circumstellar environments and the interstellar medium. This indicates an increasing reprocessing of grains in relation to specific symbiotic behavior of the objects. A correlation between the central wavelength of the 10 and 18 micron dust bands is found. By the modeling of IR spectral lines we investigate also dust grains conditions within the shocked nebulae. Both the unusual depletion values and the high sputtering efficiency might be explained by the formation of SiO moleculae, which are known to be a very reliable shock tracer. We conclude that the signature of dust chemical disturbance due to symbiotic activity should be looked for in the outer, circumbinary, expanding shells where the environmental conditions for grain processing might be achieved. Symbiotic stars are thus attractive targets for new mid-infrared and mm observations.Comment: 24 pages, 6 figures, 5 tables - to be published in A

Force Distribution in a Granular Medium

We report on systematic measurements of the distribution of normal forces exerted by granular material under uniaxial compression onto the interior surfaces of a confining vessel. Our experiments on three-dimensional, random packings of monodisperse glass beads show that this distribution is nearly uniform for forces below the mean force and decays exponentially for forces greater than the mean. The shape of the distribution and the value of the exponential decay constant are unaffected by changes in the system preparation history or in the boundary conditions. An empirical functional form for the distribution is proposed that provides an excellent fit over the whole force range measured and is also consistent with recent computer simulation data.Comment: 6 pages. For more information, see http://mrsec.uchicago.edu/granula