Parallel, self-organizing, hierarchical neural networks. II

For pt.I see IEEE Trans. Neural Networks, vol.1, p.167-78 (1990). Parallel, self-organizing, hierarchical neural networks (PSHNNs) involve a number of stages with error detection at the end of each stage, i.e., rejection of error-causing vectors, which are then fed into the next stage after a nonlinear transformation. The stages operate in parallel during testing. Statistical properties and the mechanisms of vector rejection of the PSHNN are discussed in comparison to the maximum likelihood method and the backpropagation network. The PSHNN is highly fault tolerant and robust against errors in the weight values due to the adjustment of the error detection bounds to compensate errors in the weight values. These properties are exploited to develop architectures for programmable implementations in which the programmable parts are reduced to on-off or bipolar switching operations for bulk computations and attenuators for pointwise operations     

Towards a generalized TLM algorithm for solving arbitraryreciprocal and nonreciprocal planar structures

A generalized transmission line matrix (TLM) algorithm is developed in the frequency domain to tackle arbitrary both reciprocal and nonreciprocal anisotropic waveguiding problems. In particular, the modeling issue for arbitrary planar structures is stressed in this work. A new three-dimensional (3-D) condensed node is used to consider the effect of both electric and magnetic constitutive tensors. Various results indicate how the modal dispersive behavior can be manipulated by changing not only the anisotropic characteristics of the substrate, but also the strip/slot geometry as well as the magnitude and orientation of the applied static magnetic field. The present algorithm is useful for CAD and simulation of a large class of gyrotropic waveguide-based microwave and millimeter-wave circuits     

A time-domain approach to transmission network equivalents viaProny analysis for electromagnetic transients analysis

This paper presents a method of obtaining transmission network equivalents from the network's response to a pulse excitation signal. The proposed method is based on modal decomposition representation for the large-scale interconnected system. In this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple first-order systems. As a result the network function of the transmission network can be identified easily, and a Thevenin-type of discrete-time filter model can be generated. It can reproduce the driving-point impedance characteristic of the network. Furthermore, the proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement     

Transdermal Iontophoretic Delivery of Thyrotropin-Releasing Hormone Across Excised Rabbit Pinna Skin

Enhanced transport of a model peptide drug thyrotropin-releasing hormone (TRH), a tripeptide of molar mass 362 g and a pK_a 6.2, through excised rabbit pinna skin was achieved by means of iontophoresis with continuous current or monophase periodically pulsed current. The resulting flux in the steady state was proportional to the applied current density. In the transdermal iontophoretic delivery of TRH, the pulsed iontophoretic flux exceeded that obtained with a continuous current. At a low ionic strength, an increased degree of protonation in TRH increased the rate of permeation. The flux of TRH in a buffer at pH 4 is greater than that at pH 8 when the ionic strength is 0.1 M. At a greater ionic strength, the trend is reversed. The enhanced flux of unprotonated TRH during transdermal iontophoresis is attributed largely to electro-osmotic volume flow. An increased rate of permeation of TRH crossing the skin is achieved at low ionic strength, moderate pH, and a large duly cycle of current; the frequency of pulsed current had no significant influence on the rate of transdermal iontophoretic delivery of TRH.     

新取代苯基荧光酮试剂的合成及其性质的研究Ⅱ．新型取代苯基荧光酮与金属离子显色反应的研究

研究了３，５－二溴－４－氨基苯基荧光酮、３，５－二溴－４－偶氮变色酸等８种苯基荧光酮在酸性介质中与高价金属离子Ｚｒ（Ⅳ）、Ｍｏ（Ⅵ）、Ｗ（Ⅵ）、Ａｌ（Ⅲ）、Ｇａ（Ⅲ）等的显色反应。３，５－位二溴取代的试剂的灵敏度高于未取代的灵敏度，摩尔吸光系数绝大多数在１０５Ｌ·ｍｏｌ－１·ｃｍ－１以上。     

超薄SiO2层的热生长

隧道小孔中超薄ＳｉＯ２的生长是ＥＥＰＲＯＭ电路制造的关键工艺之一。采用ＳＵＰＲＥＭ－Ⅲ工艺模拟程序对超薄ＳｉＯ２的热生长进行了工艺模拟，经过大量的工艺实验及优化，确定了超薄ＳｉＯ２的最佳生长条件，生长出的ＳｉＯ２性能良好，完全可满足ＥＥＰＲＯＭ研制的要求。     

Strain analysis of moving objects using a Fourier transform grid method

There is no good method to measure the shape and the strain distributions of a structure changing with time. We have previously proposed the Fourier transform grid method (FTGM) to measure the three-dimensional shape and surface strain distributions of stationary objects by analysing the two-dimensional grating images recorded with two cameras. In the stereoscopic method, it is very important to determine the accurate geometric parameters of the camera system. In this paper, the positions and the directions of cameras are accurately determined using the FTGM applied to images of a reference object on which a two-dimensional grating is drawn. Applications for analysing shape and strain distributions of vibrating rubber plates and a moving human skin are shown.     

Electrical properties and positron annihilation study of (Ba<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Ho<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>)TiO<Subscript>3</Subscript> ceramics

DC resistivity, dielectric constant, dielectric loss and positron annihilation spectra of (Ba_1−x Ho _x )TiO₃ ceramics have been measured as a function of holmium concentration x. It has been found that the DC resistivity of (Ba_1−x Ho _x )TiO₃ is strongly dependent on the Ho content: it decreases three orders of magnitude and reaches a minimum at x = 0.4%. Doping with 0.6% holmium increases the permittivity of BaTiO₃ by approximately three times (from ∼1,300 to ∼4,000), with only a slight increase in the corresponding dielectric loss. The local electron density and defect concentration estimated using positron annihilation technique conforms well to the features found in the dielectric and resistivity measurements. The results have been discussed in terms of a mixed compensation model.     

Enhancement of power system data debugging using GSA-based data-mining technique

In this paper, a gap-statistic-algorithm (GSA)-based data-mining technique is applied to enhance the data debugging in power system operations. In the proposed approach, the GSA technique is embedded into a neural network frame in anticipation of improving the detection capability of bad data. Thanks to the clustering capability exhibited by GSA in which the number of clusters can be optimally determined, the proposed approach becomes highly effective to localize the group of abnormal data. This proposed approach has been tested through the data collected from different scenarios made on an IEEE 30-bus system and 118-bus systems. Test results reveal the feasibility of the method for the data diagnosis applications.