Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

A new method based on the construction of hypothetical symmetrical networks for fixture calibration in network analyzers

At least three known standards are normally required for the full two-port test fixture calibration in vector network analyzers (VNA). In this paper, a calibration procedure using only one standard, based on establishing two hypothetical symmetrical fixtures using triple-through method, is shown. The results using the calibrating method to subtract the influence of fixtures are in accord with the directly measured data of the device-under-test (DUT) without the fixtures very well, which shows that the proposed method is very simple and accurate.

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

The image coding scheme based on neural network and SVM

This paper applies data coding thought, which based on the virtual information source modeling put forward by the author, to propose the image coding (compression) scheme based on neural network and SVM. This scheme is composed by "the image coding (compression) scheme based oil SVM" embedded "the lossless data compression scheme based oil neural network". The experiments show that the scheme has high compression ratio under the slightly damages condition, partly solve the contradiction which 'high fidelity' and 'high compression ratio' cannot unify in image coding system.

Lossless data compression scheme based on neural network and SVM

First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.

Investigation progress on key photonic integration for application in optical communication network

Proceeding from the consideration of the demands from the functional architecture of high speed, high capacity optical communication network, this paper points out that photonic integrated devices, including high speed response laser source, narrow band response photodetector high speed wavelength converter, dense wavelength multi/demultiplexer, low loss high speed response photo-switch and multi-beam coupler are the key components in the system. The, investigation progress in the laboratory will be introduced.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Optoelectronic Smart Pixels Comprising Flip-Chip-Bonded GaAs/AlGaAs MQW Detectors and Modulators on Silicon CMOS Circuit

于2010-11-23批量导入

Investigation on integrated high speed DFB light source and narrow bandwidth RCE photodetector for WDM fiber communication network application

Electroabsorption (EA) modulator integrated with partially gain coupling distributed feedback (DFB) lasers have been fabricated and shown high single mode yield and wavelength stability. The small signal bandwidth is about 7.5 GHz. Strained Si1-chiGechi/Si multiple quantum well (MQW) resonant-cavity enhanced (RCE) photodetectors with SiO2/Si distributed Bragg reflector (DBR) as the mirrors have been fabricated and shown a clear narrow bandwidth response. The external quantum efficiency at 1.3 mum is measured to be about 3.5% under reverse bias of 16 V. A novel GaInNAs/GaAs MQW RCE p-i-n photodetector with high reflectance GaAs/ALAs DBR mirrors has also been demonstrated and shown the selectively detecting function with the FWHM of peak response of 12 nm.

Wide-band underwater acoustic absorption based on locally resonant unit and interpenetrating network structure

The interpenetrating network structure provides an interesting avenue to novel materials. Locally resonant phononic crystal (LRPC) exhibits excellent sound attenuation performance based on the periodical arrangement of sound wave scatters. Combining the LRPC concept and interpenetrating network glassy structure, this paper has developed a new material which can achieve a wide band underwater strong acoustic absorption. Underwater absorption coefficients of different samples were measured by the pulse tube. Measurement results show that the new material possesses excellent underwater acoustic effects in a wide frequency range. Moreover, in order to investigate impacts of locally resonant units, some defects are introduced into the sample. The experimental result and the theoretical calculation both show that locally resonant units being connected to a network structure play an important role in achieving a wide band strong acoustic absorption.

Injection by hydrostatic pressure in conjunction with electrokinetic force on a microfluidic chip

A simple method was developed for injecting a sample on a cross-form microfluidic chip by means of hydrostatic pressure combined with electrokinetic forces. The hydrostatic pressure was generated simply by adjusting the liquid level in different reservoirs without any additional driven equipment such as a pump. Two dispensing strategies using a floating injection and a gated injection, coupled with hydrostatic pressure loading, were tested. The fluorescence observation verified the feasibility of hydrostatic pressure loading in the separation of a mixture of fluorescein sodium salt and fluorescein isothiocyanate. This method was proved to be effective in leading cells to a separation channel for single cell analysis.