Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

Investigation of the polyetherketone guest-host DR1/PEK-c polymer films by real-time monitoring of the second-harmonic generation

The real-time monitoring of the second-harmonic generation (SHG) was used to optimize the poling condition and to study the nonlinear optical (NLO) properties of the polyetherketone (PEK-c) guest-host polymer films. The high second-order NLO coefficient chi(33)((2)) = 11.02 pm/v measured at 1.064 mu m was achieved when the weight percent of DR1 guest in the polymer system is 20%. The NLO activity of the poled DR1/PEK-c polymer film can maintain more than 80% of its initial value when temperature is under 100 degrees C, and the normalized second-order NLO coefficient can maintain more than 85% after 2400 s at 80 degrees C. (C) 2000 Elsevier Science Ltd. All rights reserved.

A voltage-adjustable three-phase rectifier with constant power flow

An three phase adjustable output voltage rectifier with constant power flow based on waveform gap patching principle is resented. By patching the gapes in the phase currents in parallel way as well as the ripple of the output voltage in series way, it implements the constant power flow from the three-phase line to the DC output without using any line frequency (and its harmonics) energy storage components. Principally, by treating only 22.4% power of the needed power output, this rectifier can supply constant power flow with adjustable output voltages without bring about any harmonic interferences to the power utility and achieve unite power factor.

A NEW METHOD FOR MEASURING THE EFFECTIVE DIFFUSION CONSTANT OF 2-DIMENSIONAL ELECTRONS IN THE PRESENCE OF MAGNETIC-FIELDS

The transient charge response Q(t) of a two-dimensional electron gas (2DEG) in GaAs/AlxGa1-xAs heterostructures to a small pulse of the gate voltage, applied between the top gate and source electrodes in a Corbino structure, was employed to directly measure the effective diffusion constant of a 2DEG in the quantum Hall regime. The measured diffusion constant D showed a drastic change as the magnetic field was swept through the integer fillings of the Landau levels.

SHEAR-DEFORMATION-POTENTIAL CONSTANT OF THE CONDUCTION-BAND MINIMA OF SI - EXPERIMENTAL-DETERMINATION BY THE DEEP-LEVEL CAPACITANCE TRANSIENT METHOD

The shear-deformation-potential constant XI-u of the conduction-band minima of Si has been measured by a method which we called deep-level capacitance transient under uniaxial stress. The uniaxial-stress (F) dependence of the electron emission rate e(n) from deep levels to the split conduction-band minima of Si has been analyzed. Theoretical curves are in good agreement with experimental data for the S0 and S+ deep levels in Si. The values of XI-u obtained by the method are 11.1 +/- 0.3 eV at 148.9 K and 11.3 +/- 0.3 eV at 223.6 K. The analysis and the XI-u values obtained are also valuable for symmetry determination of deep electron traps in Si.

Modulation of Photonic Bandgap and Localized States by Dielectric Constant Contrast and Filling Factor in Photonic Crystals

The band structure of 2D photonic crystals (PCs) and localized states resulting from defects are analyzed by finite-difference time-domain (FDTD) technique and Pade approximation. The effect of dielectric constant contrast and filling factor on photonic bandgap (PBG) for perfect PCs and localized states in PCs with point defects are investigated. The resonant frequencies and quality factors are calculated for PCs with different defects. The numerical results show that it is possible to modulate the location, width and number of PBGs and frequencies of the localized states only by changing the dielectric constant contrast and filling factor.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.