Properties of convergence of a class of iterative processes generated by sequences of self-mappings with applications to switched dynamic systems

This article investigates the convergence properties of iterative processes involving sequences of self-mappings of metric or Banach spaces. Such sequences are built from a set of primary self-mappings which are either expansive or non-expansive self-mappings and some of the non-expansive ones can be contractive including the case of strict contractions. The sequences are built subject to switching laws which select each active self-mapping on a certain activation interval in such a way that essential properties of boundedness and convergence of distances and iterated sequences are guaranteed. Applications to the important problem of stability of dynamic switched systems are also given.

Dynamic storage performance of two cyanine dye films and optimization design for a recordable compact disk

The optical constants of two cyanine dye films that we prepared were measured with a RAP-1-type (RAP is rotating analyzer and polarizer) spectroscopic ellipsometer. Toward making a simplified model for the wafers of a recordable compact disk (CD-R), we give their optimization designs developed with the cyanine dye films. in addition, the dynamic storage performances of two sample disks were tested by our dynamic storage testing system. Measurement results of the sample disks were obtained to test and verify our film designs. (C) 2000 Optical Society of America. OCIS codes: 160.4890, 160.4760, 210.4810.

Dynamic readout of subdiffraction-limited pit arrays with a silver superlens

Recent theoretical and experimental results suggested that the silver superlens could be constructed through controlling silver thin film thickness and preparation conditions, and applied in subdiffraction-limited optical imaging and optical lithography. In this work, we report another significant application of silver superlens-ultrahigh density optical data storage. With the silver superlens the subdiffraction-limited pit arrays on an optical disk are dynamically read out and the carrier-to-noise ratio can reach 25 dB for the thin film thickness of 46 nm. The readout laser power and readout velocity have little effect on the carrier-to-noise ratio. Additionally, in our experiment the silver thin film thickness needs to be controlled in the range from 20 to 80 nm.

On the dynamic readout of sub-diffraction-limit pit arrays with a silver thin film

Fast moving arrays of periodic sub-diffraction-limit pits were dynamically read out via a silver thin film. The mechanism of the dynamic readout is analysed and discussed in detail, both experimentally and theoretically. The analysis and experiment show that, in the course of readout, surface plasmons can be excited at the silver/air interface by the focused laser beam and amplified by the silver thin film. The surface plasmons are transmitted into the substrate/silver interface with a large enhancement. The surface waves at the substrate/silver interface are scattered by the sinusoidal pits of sub-diffraction-limit size. The scattered waves are collected by a converging lens and guided into the detector for the readout.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.